2024
Dang, C., Valdebenito, M. A., Wei, P., Song, J., & Beer, M. (2024). Bayesian active learning line sampling with log-normal process for rare-event probability estimation. Reliability Engineering & System Safety, 246, 110053. doi:10.1016/j.ress.2024.110053DOI: 10.1016/j.ress.2024.110053
Wang, C., Beer, M., Faes, M. G. R., & Feng, D. -C. (2024). Resilience Assessment under Imprecise Probability. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10(2). doi:10.1061/ajrua6.rueng-1244DOI: 10.1061/ajrua6.rueng-1244
Jiang, Y., Zhang, X., Beer, M., Zhou, H., & Leng, Y. (2024). An efficient method for reliability-based design optimization of structures under random excitation by mapping between reliability and operator norm. Reliability Engineering and System Safety, 245. doi:10.1016/j.ress.2024.109972DOI: 10.1016/j.ress.2024.109972
Hong, F., Wei, P., & Beer, M. (2024). Parallelization of adaptive Bayesian cubature using multimodal optimization algorithms. Engineering Computations, 41(2), 413-437. doi:10.1108/ec-12-2023-0957DOI: 10.1108/ec-12-2023-0957
Zhuang, J., Jia, M., Huang, C. G., Beer, M., & Feng, K. (2024). Health prognosis of bearings based on transferable autoregressive recurrent adaptation with few-shot learning. Mechanical Systems and Signal Processing, 211. doi:10.1016/j.ymssp.2024.111186DOI: 10.1016/j.ymssp.2024.111186
Wang, R., Li, S., Liu, Y., Hu, X., Lai, X., & Beer, M. (2024). Peridynamics-based large-deformation simulations for near-fault landslides considering soil uncertainty. Computers and Geotechnics, 168. doi:10.1016/j.compgeo.2024.106128DOI: 10.1016/j.compgeo.2024.106128
Wang, L., Hu, Z., Dang, C., & Beer, M. (2024). Refined parallel adaptive Bayesian quadrature for estimating small failure probabilities. Reliability Engineering & System Safety, 244, 109953. doi:10.1016/j.ress.2024.109953DOI: 10.1016/j.ress.2024.109953
Bittner, M., Behrendt, M., & Beer, M. (2024). Relaxed evolutionary power spectral density functions: A probabilistic approach to model uncertainties of non-stationary stochastic signals. Mechanical Systems and Signal Processing, 211. doi:10.1016/j.ymssp.2024.111210DOI: 10.1016/j.ymssp.2024.111210
Dang, C., Cicirello, A., Valdebenito, M. A., Faes, M. G. R., Wei, P., & Beer, M. (2024). Structural reliability analysis with extremely small failure probabilities: A quasi-Bayesian active learning method. Probabilistic Engineering Mechanics, 76, 103613. doi:10.1016/j.probengmech.2024.103613DOI: 10.1016/j.probengmech.2024.103613
Li, J., Shao, F., He, Z., Ma, J., Qiu, Y., & Beer, M. (2024). Multiaxial fatigue life prediction using an improved Smith‐Watson‐Topper model. Fatigue & Fracture of Engineering Materials & Structures. doi:10.1111/ffe.14285DOI: 10.1111/ffe.14285
Li, S., Ji, J. C., Xu, Y., Feng, K., Zhang, K., Feng, J., . . . Wang, Y. (2024). Dconformer: A denoising convolutional transformer with joint learning strategy for intelligent diagnosis of bearing faults. Mechanical Systems and Signal Processing, 210, 111142. doi:10.1016/j.ymssp.2024.111142DOI: 10.1016/j.ymssp.2024.111142
Dang, C., Faes, M. G. R., Valdebenito, M. A., Wei, P., & Beer, M. (2024). Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities. Computer Methods in Applied Mechanics and Engineering, 422. doi:10.1016/j.cma.2024.116828DOI: 10.1016/j.cma.2024.116828
Wang, Z. -W., Lu, X. -F., Zhang, W. -M., Fragkoulis, V. C., Zhang, Y. -F., & Beer, M. (2024). Deep learning-based prediction of wind-induced lateral displacement response of suspension bridge decks for structural health monitoring. Journal of Wind Engineering and Industrial Aerodynamics, 247, 105679. doi:10.1016/j.jweia.2024.105679DOI: 10.1016/j.jweia.2024.105679
Wang, R., Ouyang, J., Fragkoulis, V. C., Liu, Y., & Beer, M. (2024). Experimental model updating of slope considering spatially varying soil properties and dynamic loading. Earthquake Engineering and Resilience, 3(1), 33-53. doi:10.1002/eer2.70DOI: 10.1002/eer2.70
Liu, J., Shi, Y., Ding, C., & Beer, M. (2024). Hybrid uncertainty propagation based on multi-fidelity surrogate model. Computers & Structures, 293, 107267. doi:10.1016/j.compstruc.2023.107267DOI: 10.1016/j.compstruc.2023.107267
Hu, Y., Wang, Y., Phoon, K. -K., & Beer, M. (2024). Similarity quantification of soil spatial variability between two cross-sections using auto-correlation functions. Engineering Geology, 331, 107445. doi:10.1016/j.enggeo.2024.107445DOI: 10.1016/j.enggeo.2024.107445
Behrendt, M., Lyu, M. -Z., Luo, Y., Chen, J. -B., & Beer, M. (2024). Failure probability estimation of dynamic systems employing relaxed power spectral density functions with dependent frequency modeling and sampling. Probabilistic Engineering Mechanics, 75, 103592. doi:10.1016/j.probengmech.2024.103592DOI: 10.1016/j.probengmech.2024.103592
You, Z., Miao, H., Shi, Y., & Beer, M. (2024). Improving the performance of low-frequency magnetic energy harvesters using an internal magnetic-coupled mechanism. Journal of Applied Physics, 135(8). doi:10.1063/5.0195091DOI: 10.1063/5.0195091
Ding, C., Dang, C., Broggi, M., & Beer, M. (2024). Estimation of Response Expectation Bounds under Parametric P-Boxes by Combining Bayesian Global Optimization with Unscented Transform. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10(2). doi:10.1061/ajrua6.rueng-1169DOI: 10.1061/ajrua6.rueng-1169
Behrendt, M., Dang, C., & Beer, M. (2024). Data-driven and physics-based interval modelling of power spectral density functions from limited data. Mechanical Systems and Signal Processing, 208, 111078. doi:10.1016/j.ymssp.2023.111078DOI: 10.1016/j.ymssp.2023.111078
Jerez, D. J., Fragkoulis, V. C., Ni, P., Mitseas, I. P., Valdebenito, M. A., Faes, M. G. R., & Beer, M. (2024). Operator norm-based determination of failure probability of nonlinear oscillators with fractional derivative elements subject to imprecise stationary Gaussian loads. Mechanical Systems and Signal Processing, 208, 111043. doi:10.1016/j.ymssp.2023.111043DOI: 10.1016/j.ymssp.2023.111043
Lyu, M., Feng, D., Cao, X., & Beer, M. (2024). A full‐probabilistic cloud analysis for structural seismic fragility via decoupled M‐PDEM. Earthquake Engineering & Structural Dynamics. doi:10.1002/eqe.4093DOI: 10.1002/eqe.4093
Feng, D. -C., Ding, J. -Y., Xie, S. -C., Li, Y., Akiyama, M., Lu, Y., . . . Li, J. (2024). Climate Change Impacts on the Risk Assessment of Concrete Civil Infrastructures. ASCE OPEN: Multidisciplinary Journal of Civil Engineering, 2(1). doi:10.1061/aomjah.aoeng-0026DOI: 10.1061/aomjah.aoeng-0026
Shi, Y., Behrensdorf, J., Zhou, J., Hu, Y., Broggi, M., & Beer, M. (2024). Network reliability analysis through survival signature and machine learning techniques. Reliability Engineering & System Safety, 242, 109806. doi:10.1016/j.ress.2023.109806DOI: 10.1016/j.ress.2023.109806
Jerez, D. J., Chwała, M., Jensen, H. A., & Beer, M. (2024). Optimal borehole placement for the design of rectangular shallow foundation systems under undrained soil conditions: A stochastic framework. Reliability Engineering & System Safety, 242, 109771. doi:10.1016/j.ress.2023.109771DOI: 10.1016/j.ress.2023.109771
Mao, W., Zhang, W., Feng, K., Beer, M., & Yang, C. (2024). Tensor representation-based transferability analytics and selective transfer learning of prognostic knowledge for remaining useful life prediction across machines. Reliability Engineering and System Safety, 242, 109695. doi:10.1016/j.ress.2023.109695DOI: 10.1016/j.ress.2023.109695
Lai, J., Wang, K., Shi, Y., Xu, J., Chen, J., Wang, P., & Beer, M. (2024). Reliability assessment of freight wagon passing through railway turnouts using adaptive Kriging surrogate model. International Journal of Rail Transportation, 1-20. doi:10.1080/23248378.2024.2304000DOI: 10.1080/23248378.2024.2304000
Hong, F., Wei, P., Fu, J., & Beer, M. (2024). A sequential sampling-based Bayesian numerical method for reliability-based design optimization. Reliability Engineering & System Safety, 244, 109939. doi:10.1016/j.ress.2024.109939DOI: 10.1016/j.ress.2024.109939
Yuan, P., Yuen, K. -V., Beer, M., Cai, C. S., & Yan, W. (2024). A non-iterative partitioned computational method with the energy conservation property for time-variant dynamic systems. Mechanical Systems and Signal Processing, 209, 111105. doi:10.1016/j.ymssp.2024.111105DOI: 10.1016/j.ymssp.2024.111105
Feng, C., Valdebenito, M. A., Chwała, M., Liao, K., Broggi, M., & Beer, M. (2024). Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments. Journal of Rock Mechanics and Geotechnical Engineering, 16(4), 1140-1152. doi:10.1016/j.jrmge.2023.09.006DOI: 10.1016/j.jrmge.2023.09.006
Zheng, Z., Beer, M., & Nackenhorst, U. (n.d.). Efficient stochastic modal decomposition methods for structural stochastic static and dynamic analyses. International Journal for Numerical Methods in Engineering. doi:10.1002/nme.7469DOI: 10.1002/nme.7469
Huang, Z., Chen, G., & Beer, M. (2024). Multi-taper S-transform method for estimating Wigner-Ville and Loève spectra of quasi-stationary harmonizable processes. Mechanical Systems and Signal Processing, 206, 110880. doi:10.1016/j.ymssp.2023.110880DOI: 10.1016/j.ymssp.2023.110880
Hu, Z., Dang, C., Wang, L., & Beer, M. (2024). Parallel Bayesian probabilistic integration for structural reliability analysis with small failure probabilities. Structural Safety, 106, 102409. doi:10.1016/j.strusafe.2023.102409DOI: 10.1016/j.strusafe.2023.102409
Sarvari, H., Asaadsamani, P., Olawumi, T. O., Chan, D. W. M., Rashidi, A., & Beer, M. (n.d.). Perceived barriers to implementing building information modeling in Iranian Small and Medium-Sized Enterprises (SMEs): a Delphi survey of construction experts. Architectural Engineering and Design Management, 1-21. doi:10.1080/17452007.2024.2329687DOI: 10.1080/17452007.2024.2329687
Huang, Z., & Beer, M. (2024). Probability distributions for dynamic and extreme responses of linear elastic structures under quasi-stationary harmonizable loads. Probabilistic Engineering Mechanics, 75, 103590. doi:10.1016/j.probengmech.2024.103590DOI: 10.1016/j.probengmech.2024.103590
2023
Wang, C., Ayyub, B. M., Zhang, H., & Beer, M. (2023). Time-Dependent Resilience in the Presence of Interacting Multiple Hazards in a Changing Climate. ASCE OPEN: Multidisciplinary Journal of Civil Engineering, 1. doi:10.1061/aomjah.aoeng-0024DOI: 10.1061/aomjah.aoeng-0024
Cao, X. -Y., Feng, D. -C., & Beer, M. (2023). A KDE-based non-parametric cloud approach for efficient seismic fragility estimation of structures under non-stationary excitation. Mechanical Systems and Signal Processing, 205, 110873. doi:10.1016/j.ymssp.2023.110873DOI: 10.1016/j.ymssp.2023.110873
Imprecise Survival Signature Approximation Using Interval Predictor Models (Conference Paper)
Behrensdorf, J., Broggi, M., & Beer, M. (2023). Imprecise Survival Signature Approximation Using Interval Predictor Models. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE. doi:10.1109/ssci52147.2023.10371939DOI: 10.1109/ssci52147.2023.10371939
Lai, J., Wang, K., Xu, J., Wang, P., Chen, R., Wang, S., & Beer, M. (2023). A failure probability assessment method for train derailments in railway yards based on IFFTA and NGBN. Engineering Failure Analysis, 154. doi:10.1016/j.engfailanal.2023.107675DOI: 10.1016/j.engfailanal.2023.107675
Hong, F., Wei, P., Song, J., Valdebenito, M. A., Faes, M. G. R., & Beer, M. (2023). Collaborative and Adaptive Bayesian Optimization for bounding variances and probabilities under hybrid uncertainties. Computer Methods in Applied Mechanics and Engineering, 417, 116410. doi:10.1016/j.cma.2023.116410DOI: 10.1016/j.cma.2023.116410
Chwała, M., Jerez, D. J., Jensen, H. A., & Beer, M. (2023). Performance assessment of borehole arrangements for the design of rectangular shallow foundation systems. Journal of Rock Mechanics and Geotechnical Engineering, 15(12), 3291-3304. doi:10.1016/j.jrmge.2023.05.009DOI: 10.1016/j.jrmge.2023.05.009
Stochastic Model Updating with Uncertainty Quantification: An Overview and Tutorial (Journal article)
Bi, S., Beer, M., Cogan, S., & Mottershead, J. (2023). Stochastic Model Updating with Uncertainty Quantification: An Overview and Tutorial. Mechanical Systems and Signal Processing, 204. doi:10.1016/j.ymssp.2023.110784DOI: 10.1016/j.ymssp.2023.110784
Chen, G., Yang, J., Wang, R., Li, K., Liu, Y., & Beer, M. (2023). Response to discussion of “Seismic damage analysis due to near‐fault multipulse ground motion”. Earthquake Engineering & Structural Dynamics. doi:10.1002/eqe.4046DOI: 10.1002/eqe.4046
Mei, L. -F., Yan, W. -J., Yuen, K. -V., Ren, W. -X., & Beer, M. (2023). Transmissibility-based damage detection with hierarchical clustering enhanced by multivariate probabilistic distance accommodating uncertainty and correlation. Mechanical Systems and Signal Processing, 203, 110702. doi:10.1016/j.ymssp.2023.110702DOI: 10.1016/j.ymssp.2023.110702
Machine Learning Assisted Network Resilience Design (Conference Paper)
Shi, Y., & Beer, M. (2023). Machine Learning Assisted Network Resilience Design. In ASCE Inspire 2023. American Society of Civil Engineers. doi:10.1061/9780784485163.079DOI: 10.1061/9780784485163.079
Resilience Capacity of Civil Structures and Infrastructure Systems (Conference Paper)
Wang, C., Ayyub, B. M., & Beer, M. (2023). Resilience Capacity of Civil Structures and Infrastructure Systems. In ASCE Inspire 2023. American Society of Civil Engineers. doi:10.1061/9780784485163.055DOI: 10.1061/9780784485163.055
The Concept of Diagonal Approximated Signature: New Surrogate Modeling Approach for Continuous-State Systems (Conference Paper)
Winnewisser, N. R., Salomon, J., Broggi, M., & Beer, M. (2023). The Concept of Diagonal Approximated Signature: New Surrogate Modeling Approach for Continuous-State Systems. In ASCE Inspire 2023. American Society of Civil Engineers. doi:10.1061/9780784485163.031DOI: 10.1061/9780784485163.031
Shi, Y., Huang, H. -Z., Liu, Y., & Beer, M. (2023). Adaptive decoupled robust design optimization. Structural Safety, 105, 102378. doi:10.1016/j.strusafe.2023.102378DOI: 10.1016/j.strusafe.2023.102378
Chen, Y., Patelli, E., Edwards, B., & Beer, M. (2023). A Bayesian Augmented-Learning framework for spectral uncertainty quantification of incomplete records of stochastic processes. Mechanical Systems and Signal Processing, 200, 110573. doi:10.1016/j.ymssp.2023.110573DOI: 10.1016/j.ymssp.2023.110573
Xu, Y., Ji, J. C., Ni, Q., Feng, K., Beer, M., & Chen, H. (2023). A graph-guided collaborative convolutional neural network for fault diagnosis of electromechanical systems. Mechanical Systems and Signal Processing, 200, 110609. doi:10.1016/j.ymssp.2023.110609DOI: 10.1016/j.ymssp.2023.110609
Zhang, K., Chen, N., Liu, J., Yin, S., & Beer, M. (2023). An efficient meta-model-based method for uncertainty propagation problems involving non-parameterized probability-boxes. Reliability Engineering & System Safety, 238, 109477. doi:10.1016/j.ress.2023.109477DOI: 10.1016/j.ress.2023.109477
Zheng, Z., Beer, M., & Nackenhorst, U. (2023). An iterative multi-fidelity scheme for simulating multi-dimensional non-Gaussian random fields. Mechanical Systems and Signal Processing, 200, 110643. doi:10.1016/j.ymssp.2023.110643DOI: 10.1016/j.ymssp.2023.110643
Liao, K., Wu, Y., Miao, F., Pan, Y., & Beer, M. (n.d.). Probabilistic risk assessment of earth dams with spatially variable soil properties using random adaptive finite element limit analysis. Engineering with Computers. doi:10.1007/s00366-022-01752-0DOI: 10.1007/s00366-022-01752-0
Weng, L. -L., Yang, J. -S., Chen, J. -B., & Beer, M. (2023). Structural design optimization under dynamic reliability constraints based on probability density evolution method and quantum-inspired optimization algorithm. Probabilistic Engineering Mechanics, 74, 103494. doi:10.1016/j.probengmech.2023.103494DOI: 10.1016/j.probengmech.2023.103494
Chen, G., Yang, J., Wang, R., Li, K., Liu, Y., & Beer, M. (2023). Seismic damage analysis due to near‐fault multipulse ground motion. Earthquake Engineering & Structural Dynamics. doi:10.1002/eqe.4003DOI: 10.1002/eqe.4003
Special Section on Community Resilience to Disruptive Events: Models and Analyses, Lessons Learned, and Case Studies (Journal article)
Wang, C., Faes, M. G. R., Beer, M., Zio, E., & van de Lindt, J. W. (2023). Special Section on Community Resilience to Disruptive Events: Models and Analyses, Lessons Learned, and Case Studies. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 9(3). doi:10.1115/1.4062982DOI: 10.1115/1.4062982
Dang, C., Valdebenito, M. A., Faes, M. G. R., Song, J., Wei, P., & Beer, M. (2023). Structural reliability analysis by line sampling: A Bayesian active learning treatment. Structural Safety, 104, 102351. doi:10.1016/j.strusafe.2023.102351DOI: 10.1016/j.strusafe.2023.102351
Behrendt, M., de Angelis, M., & Beer, M. (2023). Uncertainty Propagation of Missing Data Signals with the Interval Discrete Fourier Transform. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 9(3). doi:10.1061/ajrua6.rueng-1048DOI: 10.1061/ajrua6.rueng-1048
Chen, G., Liu, Y., & Beer, M. (2023). Effects of response spectrum of pulse-like ground motion on stochastic seismic response of tunnel. Engineering Structures, 289, 116274. doi:10.1016/j.engstruct.2023.116274DOI: 10.1016/j.engstruct.2023.116274
Wang, C., Ayyub, B. M., & Beer, M. (2023). From Reliability-Based Design to Resilience-Based Design. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 9(3). doi:10.1115/1.4062997DOI: 10.1115/1.4062997
Wang, Z. -W., Lu, X. -F., Zhang, W. -M., Fragkoulis, V. C., Beer, M., & Zhang, Y. -F. (2023). Deep learning-based reconstruction of missing long-term girder-end displacement data for suspension bridge health monitoring. Computers & Structures, 284, 107070. doi:10.1016/j.compstruc.2023.107070DOI: 10.1016/j.compstruc.2023.107070
Feng, C., Faes, M., Broggi, M., & Beer, M. (2023). Application of Interval Field Method to the Stability Analysis of Slopes in the Presence of Uncertainties. In GEO-RISK 2023: ADVANCES IN MODELING UNCERTAINTY AND VARIABILITY Vol. 347 (pp. 287-297). Retrieved from https://www.webofscience.com/
Cao, X. -Y., Feng, D. -C., & Beer, M. (2023). Consistent seismic hazard and fragility analysis considering combined capacity-demand uncertainties via probability density evolution method. Structural Safety, 103, 102330. doi:10.1016/j.strusafe.2023.102330DOI: 10.1016/j.strusafe.2023.102330
Dang, C., Valdebenito, M. A., Song, J., Wei, P., & Beer, M. (2023). Estimation of small failure probabilities by partially Bayesian active learning line sampling: Theory and algorithm. Computer Methods in Applied Mechanics and Engineering, 412, 116068. doi:10.1016/j.cma.2023.116068DOI: 10.1016/j.cma.2023.116068
Zheng, Z., Valdebenito, M., Beer, M., & Nackenhorst, U. (2023). Simulation of random fields on random domains. Probabilistic Engineering Mechanics, 73, 103455. doi:10.1016/j.probengmech.2023.103455DOI: 10.1016/j.probengmech.2023.103455
Chen, Y. -L., Shi, Y., Huang, H. -Z., Sun, D., & Beer, M. (2023). Uncertainty analysis of structural output with closed-form expression based on surrogate model. PROBABILISTIC ENGINEERING MECHANICS, 73. doi:10.1016/j.probengmech.2023.103482DOI: 10.1016/j.probengmech.2023.103482
Distribution-free stochastic model updating with staircase density functions (Chapter)
Kitahara, M., Kitahara, T., Bi, S., Broggi, M., & Beer, M. (2023). Distribution-free stochastic model updating with staircase density functions. In Life-Cycle of Structures and Infrastructure Systems (pp. 670-677). CRC Press. doi:10.1201/9781003323020-81DOI: 10.1201/9781003323020-81
Efficient posterior estimation for stochastic SHM using transport maps (Chapter)
Grashorn, J., Broggi, M., Chamoin, L., & Beer, M. (2023). Efficient posterior estimation for stochastic SHM using transport maps. In Life-Cycle of Structures and Infrastructure Systems (pp. 678-685). CRC Press. doi:10.1201/9781003323020-82DOI: 10.1201/9781003323020-82
Environmental influence on structural health monitoring systems (Chapter)
Bartels, J. -H., Kitahara, M., Marx, S., & Beer, M. (2023). Environmental influence on structural health monitoring systems. In Life-Cycle of Structures and Infrastructure Systems (pp. 662-669). CRC Press. doi:10.1201/9781003323020-80DOI: 10.1201/9781003323020-80
Persoons, A., Wei, P., Broggi, M., & Beer, M. (2023). A new reliability method combining adaptive Kriging and active variance reduction using multiple importance sampling. Structural and Multidisciplinary Optimization, 66(6). doi:10.1007/s00158-023-03598-6DOI: 10.1007/s00158-023-03598-6
Hong, F., Wei, P., Song, J., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2023). Combining data and physical models for probabilistic analysis: A Bayesian Augmented Space Learning perspective. PROBABILISTIC ENGINEERING MECHANICS, 73. doi:10.1016/j.probengmech.2023.103474DOI: 10.1016/j.probengmech.2023.103474
Liao, K., Wu, Y., Miao, F., Zhang, L., & Beer, M. (2023). Efficient System Reliability Analysis for Layered Soil Slopes with Multiple Failure Modes Using Sequential Compounding Method. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 9(2). doi:10.1061/ajrua6.rueng-1022DOI: 10.1061/ajrua6.rueng-1022
Hong, X., Song, Y., Kong, F., & Beer, M. (2023). The Typhoon Wind Hazard Assessment Considering the Correlation among the Key Random Variables Using the Copula Method. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 9(2). doi:10.1061/ajrua6.rueng-1018DOI: 10.1061/ajrua6.rueng-1018
Grashorn, J., Urrea-Quintero, J. -H., Broggi, M., Chamoin, L., & Beer, M. (2023). Transport map Bayesian parameter estimation for dynamical systems. PAMM, 23(1). doi:10.1002/pamm.202200136DOI: 10.1002/pamm.202200136
Zhang, Y., Ren, Z., Feng, K., Yu, K., Beer, M., & Liu, Z. (2023). Universal source-free domain adaptation method for cross-domain fault diagnosis of machines. Mechanical Systems and Signal Processing, 191, 110159. doi:10.1016/j.ymssp.2023.110159DOI: 10.1016/j.ymssp.2023.110159
Yuan, X., Valdebenito, M. A., Zhang, B., Faes, M. G. R., & Beer, M. (2023). Efficient decoupling approach for reliability-based optimization based on augmented Line Sampling and combination algorithm. Computers and Structures, 280, 107003. doi:10.1016/j.compstruc.2023.107003DOI: 10.1016/j.compstruc.2023.107003
Chen, G., Liu, Y., & Beer, M. (2023). Identification of near-fault multi-pulse ground motion. Applied Mathematical Modelling, 117, 609-624. doi:10.1016/j.apm.2023.01.002DOI: 10.1016/j.apm.2023.01.002
Bai, Y., Li, X., Zhou, X., Li, P., & Beer, M. (2023). Soil-expended seismic metamaterial with ultralow and wide bandgap. Mechanics of Materials, 180, 104601. doi:10.1016/j.mechmat.2023.104601DOI: 10.1016/j.mechmat.2023.104601
Winnewisser, N. R., Salomon, J., Broggi, M., & Beer, M. (n.d.). The concept of diagonal approximated signature: new surrogate modeling approach for continuous-state systems in the context of resilience optimization. Disaster Prevention and Resilience, 3(2), 4. doi:10.20517/dpr.2023.03DOI: 10.20517/dpr.2023.03
Ma, J., Dai, C., Wang, B., Beer, M., & Wang, A. (2023). Random dynamic responses of solar array under thermal-structural coupling based on the isogeometric analysis. Acta Mechanica Sinica, 39(4). doi:10.1007/s10409-023-22338-xDOI: 10.1007/s10409-023-22338-x
Behrendt, M., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2023). Estimation of an imprecise power spectral density function with optimised bounds from scarce data for epistemic uncertainty quantification. Mechanical Systems and Signal Processing, 189, 110072. doi:10.1016/j.ymssp.2022.110072DOI: 10.1016/j.ymssp.2022.110072
Zhang, Y., Xu, J., & Beer, M. (2023). A single-loop time-variant reliability evaluation via a decoupling strategy and probability distribution reconstruction. Reliability Engineering & System Safety, 232, 109031. doi:10.1016/j.ress.2022.109031DOI: 10.1016/j.ress.2022.109031
Wang, C., Yang, L., Xie, M., Valdebenito, M., & Beer, M. (2023). Bayesian maximum entropy method for stochastic model updating using measurement data and statistical information. Mechanical Systems and Signal Processing, 188, 110012. doi:10.1016/j.ymssp.2022.110012DOI: 10.1016/j.ymssp.2022.110012
Mo, J., Yan, W. -J., Yuen, K. -V., & Beer, M. (2023). Efficient inner-outer decoupling scheme for non-probabilistic model updating with high dimensional model representation and Chebyshev approximation. Mechanical Systems and Signal Processing, 188, 110040. doi:10.1016/j.ymssp.2022.110040DOI: 10.1016/j.ymssp.2022.110040
Ni, P., Fragkoulis, V. C., Kong, F., Mitseas, I. P., & Beer, M. (2023). Non-stationary response of nonlinear systems with singular parameter matrices subject to combined deterministic and stochastic excitation. Mechanical Systems and Signal Processing, 188, 110009. doi:10.1016/j.ymssp.2022.110009DOI: 10.1016/j.ymssp.2022.110009
Bai, Y., Wang, S., Zhou, X., & Beer, M. (2023). Three-dimensional ori-kirigami metamaterials with multistability.. Physical review. E, 107(3-2), 035004. doi:10.1103/physreve.107.035004DOI: 10.1103/physreve.107.035004
Chen, Y., Patelli, E., Edwards, B., & Beer, M. (2023). A physics-informed Bayesian framework for characterizing ground motion process in the presence of missing data. EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS. doi:10.1002/eqe.3877DOI: 10.1002/eqe.3877
Feng, K., Ji, J. C., Zhang, Y., Ni, Q., Liu, Z., & Beer, M. (2023). Digital twin-driven intelligent assessment of gear surface degradation. Mechanical Systems and Signal Processing, 186, 109896. doi:10.1016/j.ymssp.2022.109896DOI: 10.1016/j.ymssp.2022.109896
Yuan, X., Qian, Y., Chen, J., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2023). Global failure probability function estimation based on an adaptive strategy and combination algorithm. RELIABILITY ENGINEERING & SYSTEM SAFETY, 231. doi:10.1016/j.ress.2022.108937DOI: 10.1016/j.ress.2022.108937
Zeng, D., Zhang, H., Dai, H., & Beer, M. (2023). Scalable risk assessment of large infrastructure systems with spatially correlated components. Structural Safety, 101, 102311. doi:10.1016/j.strusafe.2022.102311DOI: 10.1016/j.strusafe.2022.102311
Dai, H., Zhang, R., & Beer, M. (2023). A new method for stochastic analysis of structures under limited observations. Mechanical Systems and Signal Processing, 185, 109730. doi:10.1016/j.ymssp.2022.109730DOI: 10.1016/j.ymssp.2022.109730
Zheng, Z., Valdebenito, M., Beer, M., & Nackenhorst, U. (2023). A stochastic finite element scheme for solving partial differential equations defined on random domains. Computer Methods in Applied Mechanics and Engineering, 405, 115860. doi:10.1016/j.cma.2022.115860DOI: 10.1016/j.cma.2022.115860
Ding, C., Dang, C., Valdebenito, M. A., Faes, M. G. R., Broggi, M., & Beer, M. (2023). First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach. Mechanical Systems and Signal Processing, 185, 109775. doi:10.1016/j.ymssp.2022.109775DOI: 10.1016/j.ymssp.2022.109775
Chen, G., Yang, J., Liu, Y., Kitahara, T., & Beer, M. (2023). An energy-frequency parameter for earthquake ground motion intensity measure. EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS, 52(2), 271-284. doi:10.1002/eqe.3752DOI: 10.1002/eqe.3752
Zheng, Z., Dai, H., & Beer, M. (2023). Efficient structural reliability analysis via a weak-intrusive stochastic finite element method. Probabilistic Engineering Mechanics, 71, 103414. doi:10.1016/j.probengmech.2023.103414DOI: 10.1016/j.probengmech.2023.103414
A Two-Phase Sampling Approach for Reliability-Based Optimization in Structural Engineering (Chapter)
Jerez, D. J., Jensen, H. A., & Beer, M. (2023). A Two-Phase Sampling Approach for Reliability-Based Optimization in Structural Engineering. In Springer Series in Reliability Engineering (pp. 21-48). Springer Nature Switzerland. doi:10.1007/978-3-031-28859-3_2DOI: 10.1007/978-3-031-28859-3_2
Feng, K., Ji, J. C., Ni, Q., & Beer, M. (2023). A review of vibration-based gear wear monitoring and prediction techniques. Mechanical Systems and Signal Processing, 182, 109605. doi:10.1016/j.ymssp.2022.109605DOI: 10.1016/j.ymssp.2022.109605
Liu, W., Ye, T., Yuan, P., Beer, M., & Tong, X. (2023). An explicit integration method with third-order accuracy for linear and nonlinear dynamic systems. Engineering Structures, 274, 115013. doi:10.1016/j.engstruct.2022.115013DOI: 10.1016/j.engstruct.2022.115013
Kitahara, M., Dang, C., & Beer, M. (2023). Bayesian updating with two-step parallel Bayesian optimization and quadrature. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 403. doi:10.1016/j.cma.2022.115735DOI: 10.1016/j.cma.2022.115735
Fourier Transform and Other Quadratic Problems Under Interval Uncertainty (Chapter)
Galindo, O., Ibarra, C., Kreinovich, V., & Beer, M. (2023). Fourier Transform and Other Quadratic Problems Under Interval Uncertainty. In Studies in Systems, Decision and Control (pp. 251-256). Springer International Publishing. doi:10.1007/978-3-031-16415-6_37DOI: 10.1007/978-3-031-16415-6_37
Fuzzy Probability Theory (Chapter)
Beer, M. (2023). Fuzzy Probability Theory. In Encyclopedia of Complexity and Systems Science Series (pp. 51-75). Springer US. doi:10.1007/978-1-0716-2628-3_237DOI: 10.1007/978-1-0716-2628-3_237
Regression Models for Machine Learning (Chapter)
Wei, P., & Beer, M. (2023). Regression Models for Machine Learning. In Computational Methods in Engineering & the Sciences (pp. 341-371). Springer International Publishing. doi:10.1007/978-3-031-36644-4_9DOI: 10.1007/978-3-031-36644-4_9
Jiang, Y., Li, Z., Zhou, H., Wang, F., Beer, M., & Zheng, J. (2023). Reliability Evaluation of RC Columns with Wind-Dominated Combination Considering Random Biaxial Eccentricity. Journal of Structural Engineering, 149(1). doi:10.1061/(asce)st.1943-541x.0003507DOI: 10.1061/(asce)st.1943-541x.0003507
Resilience of structural infrastructure (Journal article)
Beer, M. (2023). Resilience of structural infrastructure. Bauingenieur, 98(5), A-3.
Bartels, J. H., Potthast, T., Kitahara, M., Marx, S., & Beer, M. (2023). Robust SHM Systems Using Bayesian Model Updating. In Proceedings of the International Offshore and Polar Engineering Conference (pp. 272-278).
Chen, Y., Patelli, E., Edwards, B., & Beer, M. (2023). SPECTRAL DENSITY ESTIMATION OF STOCHASTIC PROCESSES UNDER MISSING DATA AND UNCERTAINTY QUANTIFICATION WITH BAYESIAN DEEP LEARNING. In UNCECOMP Proceedings.
Yuan, X., Wang, S., Valdebenito, M. A., Faes, M. G. R., & Beer, M. (2023). Sample regeneration algorithm for structural failure probability function estimation. PROBABILISTIC ENGINEERING MECHANICS, 71. doi:10.1016/j.probengmech.2022.103387DOI: 10.1016/j.probengmech.2022.103387
UNCERTAINTYQUANTIFICATION.JL: A NEW FRAMEWORK FOR UNCERTAINTY QUANTIFICATION IN JULIA (Conference Paper)
Behrensdorf, J., Gray, A., Broggi, M., & Beer, M. (2023). UNCERTAINTYQUANTIFICATION.JL: A NEW FRAMEWORK FOR UNCERTAINTY QUANTIFICATION IN JULIA. In 5th International Conference on Uncertainty Quantification in Computational Sciences and Engineering. Institute of Structural Analysis and Antiseismic Research National Technical University of Athens. doi:10.7712/120223.10347.19810DOI: 10.7712/120223.10347.19810
Goeing, J., Seehausen, H., Stania, L., Nuebel, N., Salomon, J., Ignatidis, P., . . . Friedrichs, J. (n.d.). Virtual process for evaluating the influence of real combined module variations on the overall performance of an aircraft engine. Journal of the Global Power and Propulsion Society, 7, 95-112. doi:10.33737/jgpps/160055DOI: 10.33737/jgpps/160055
2022
Rafieyan, A., Sarvari, H., Beer, M., & Chan, D. W. M. (2022). Determining the effective factors leading to incidence of human error accidents in industrial parks construction projects: results of a fuzzy Delphi survey. International Journal of Construction Management, 1-13. doi:10.1080/15623599.2022.2159630DOI: 10.1080/15623599.2022.2159630
Mei, L. -F., Yan, W. -J., Yuen, K. -V., & Beer, M. (2022). Structural novelty detection with Laplace asymptotic expansion of the Bhattacharyya distance of transmissibility and Bayesian resampling scheme. Journal of Sound and Vibration, 540, 117277. doi:10.1016/j.jsv.2022.117277DOI: 10.1016/j.jsv.2022.117277
Zhang, K., Chen, N., Zeng, P., Liu, J., & Beer, M. (2022). An efficient reliability analysis method for structures with hybrid time-dependent uncertainty. RELIABILITY ENGINEERING & SYSTEM SAFETY, 228. doi:10.1016/j.ress.2022.108794DOI: 10.1016/j.ress.2022.108794
New Cycle of the ASCE Journals’ Early Career Editorial Board (Journal article)
Beer, M. (2022). New Cycle of the ASCE Journals’ Early Career Editorial Board. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 8(4). doi:10.1061/ajrua6.0001268DOI: 10.1061/ajrua6.0001268
Han, R., Fragkoulis, V. C., Kong, F., Beer, M., & Peng, Y. (2022). Non-stationary response determination of nonlinear systems subjected to combined deterministic and evolutionary stochastic excitations. INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS, 147. doi:10.1016/j.ijnonlinmec.2022.104192DOI: 10.1016/j.ijnonlinmec.2022.104192
Special Section on Decommissioning and Life Extension of Complex Industrial Assets (Journal article)
Moura, R., Beer, M., de Souza, G. F. M., & Patelli, E. (2022). Special Section on Decommissioning and Life Extension of Complex Industrial Assets. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 8(4). doi:10.1115/1.4055799DOI: 10.1115/1.4055799
Wang, C., Zhang, H., & Beer, M. (2022). Structural Time-Dependent Reliability Assessment: Advanced Approaches for Engineered Structures. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 9(1). doi:10.1061/AJRUA6.RUENG-1010DOI: 10.1061/AJRUA6.RUENG-1010
Salomon, J., Behrensdorf, J., Winnewisser, N., Broggi, M., & Beer, M. (2022). Multidimensional resilience decision-making for complex and substructured systems. Resilient Cities and Structures, 1(3), 61-78. doi:10.1016/j.rcns.2022.10.005DOI: 10.1016/j.rcns.2022.10.005
Kougioumtzoglou, I. A., Ni, P., Mitseas, I. P., Fragkoulis, V. C., & Beer, M. (2022). An approximate stochastic dynamics approach for design spectrum based response analysis of nonlinear structural systems with fractional derivative elements. International Journal of Non-Linear Mechanics, 146, 104178. doi:10.1016/j.ijnonlinmec.2022.104178DOI: 10.1016/j.ijnonlinmec.2022.104178
Yang, J. -S., Chen, J. -B., Beer, M., & Jensen, H. (2022). An efficient approach for dynamic-reliability-based topology optimization of braced frame structures with probability density evolution method. Advances in Engineering Software, 173, 103196. doi:10.1016/j.advengsoft.2022.103196DOI: 10.1016/j.advengsoft.2022.103196
Dang, C., Valdebenito, M. A., Faes, M. G. R., Wei, P., & Beer, M. (2022). Structural reliability analysis: A Bayesian perspective. STRUCTURAL SAFETY, 99. doi:10.1016/j.strusafe.2022.102259DOI: 10.1016/j.strusafe.2022.102259
Feng, C., Faes, M., Broggi, M., Dang, C., Yang, J., Zheng, Z., & Beer, M. (2022). Application of interval field method to the stability analysis of slopes in presence of uncertainties. Computers and Geotechnics, 105060. doi:10.1016/j.compgeo.2022.105060DOI: 10.1016/j.compgeo.2022.105060
Jiang, Y., Zheng, J., Yang, K., Zhou, H., & Beer, M. (2022). Probabilistic analysis of resistance for RC columns with wind-dominated combination considering random biaxial eccentricity. Structure and Infrastructure Engineering, 1-11. doi:10.1080/15732479.2022.2131842DOI: 10.1080/15732479.2022.2131842
Feng, K., Ni, Q., Beer, M., Du, H., & Li, C. (2022). A novel similarity-based status characterization methodology for gear surface wear propagation monitoring. TRIBOLOGY INTERNATIONAL, 174. doi:10.1016/j.triboint.2022.107765DOI: 10.1016/j.triboint.2022.107765
Feng, D. -C., Cao, X. -Y., & Beer, M. (2022). An enhanced PDEM-based framework for reliability analysis of structures considering multiple failure modes and limit states. Probabilistic Engineering Mechanics, 70, 103367. doi:10.1016/j.probengmech.2022.103367DOI: 10.1016/j.probengmech.2022.103367
Dang, C., Wei, P., Faes, M. G. R., & Beer, M. (2022). Bayesian probabilistic propagation of hybrid uncertainties: Estimation of response expectation function, its variable importance and bounds. COMPUTERS & STRUCTURES, 270. doi:10.1016/j.compstruc.2022.106860DOI: 10.1016/j.compstruc.2022.106860
Behrendt, M., Kitahara, M., Kitahara, T., Comerford, L., & Beer, M. (2022). Data-driven reliability assessment of dynamic structures based on power spectrum classification. ENGINEERING STRUCTURES, 268. doi:10.1016/j.engstruct.2022.114648DOI: 10.1016/j.engstruct.2022.114648
Jerez, D. J., Jensen, H. A., Valdebenito, M. A., Misraji, M. A., Mayorga, F., & Beer, M. (2022). On the use of Directional Importance Sampling for reliability-based design and optimum design sensitivity of linear stochastic structures. Probabilistic Engineering Mechanics, 103368. doi:10.1016/j.probengmech.2022.103368DOI: 10.1016/j.probengmech.2022.103368
Goeing, J., Seehausen, H., Stania, L., Nuebel, N., Salomon, J., Ignatidis, P., . . . Friedrichs, J. (2022). Virtual Process for Evaluating the Influence of Real Combined Module Variations on the Overall Performance of an Aircraft Engine. In Proceedings of Global Power & Propulsion Society. GPPS. doi:10.33737/gpps22-tc-89DOI: 10.33737/gpps22-tc-89
Zheng, Z., Beer, M., Dai, H., & Nackenhorst, U. (2022). A weak-intrusive stochastic finite element method for stochastic structural dynamics analysis. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 399. doi:10.1016/j.cma.2022.115360DOI: 10.1016/j.cma.2022.115360
Jerez, D. J., Jensen, H. A., & Beer, M. (2022). An effective implementation of reliability methods for Bayesian model updating of structural dynamic models with multiple uncertain parameters. RELIABILITY ENGINEERING & SYSTEM SAFETY, 225. doi:10.1016/j.ress.2022.108634DOI: 10.1016/j.ress.2022.108634
Chen, G., Beer, M., & Liu, Y. (2022). Modeling response spectrum compatible pulse-like ground motion. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 177. doi:10.1016/j.ymssp.2022.109177DOI: 10.1016/j.ymssp.2022.109177
Dang, C., Wei, P., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2022). Parallel adaptive Bayesian quadrature for rare event estimation. RELIABILITY ENGINEERING & SYSTEM SAFETY, 225. doi:10.1016/j.ress.2022.108621DOI: 10.1016/j.ress.2022.108621
Zheng, Z., Beer, M., & Nackenhorst, U. (2022). An efficient reduced-order method for stochastic eigenvalue analysis. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING. doi:10.1002/nme.7092DOI: 10.1002/nme.7092
Hazard-Resilient Infrastructure: Analysis and Design (Journal article)
Beer, M. (2022). Hazard-Resilient Infrastructure: Analysis and Design. NATURAL HAZARDS REVIEW, 23(3). doi:10.1061/(ASCE)NH.1527-6996.0000562DOI: 10.1061/(ASCE)NH.1527-6996.0000562
Dang, C., Wei, P., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2022). Interval uncertainty propagation by a parallel Bayesian global optimization method. Applied Mathematical Modelling, 108, 220-235. doi:10.1016/j.apm.2022.03.031DOI: 10.1016/j.apm.2022.03.031
Faes, M. G. R., Broggi, M., Chen, G., Phoon, K. -K., & Beer, M. (2022). Distribution-free P-box processes based on translation theory: Definition and simulation. Probabilistic Engineering Mechanics, 69, 103287. doi:10.1016/j.probengmech.2022.103287DOI: 10.1016/j.probengmech.2022.103287
Kitahara, M., Bi, S., Broggi, M., & Beer, M. (2022). Distribution-free stochastic model updating of dynamic systems with parameter dependencies. Structural Safety, 97, 102227. doi:10.1016/j.strusafe.2022.102227DOI: 10.1016/j.strusafe.2022.102227
Faes, M. G. R., Broggi, M., Spanos, P. D., & Beer, M. (2022). Elucidating appealing features of differentiable auto-correlation functions: A study on the modified exponential kernel. Probabilistic Engineering Mechanics, 69, 103269. doi:10.1016/j.probengmech.2022.103269DOI: 10.1016/j.probengmech.2022.103269
Jensen, H., Beer, M., Chen, J., & Spence, S. (2022). Special issue on Advances in performance-based design optimization of stochastic dynamical systems. Mechanical Systems and Signal Processing, 173, 108972. doi:10.1016/j.ymssp.2022.108972DOI: 10.1016/j.ymssp.2022.108972
Bi, S., Beer, M., & Mottershead, J. (2022). Editorial: Recent advances in stochastic model updating. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 172. doi:10.1016/j.ymssp.2022.108971DOI: 10.1016/j.ymssp.2022.108971
Behrendt, M., de Angelis, M., Comerford, L., Zhang, Y., & Beer, M. (2022). Projecting interval uncertainty through the discrete Fourier transform: An application to time signals with poor precision. Mechanical Systems and Signal Processing, 172, 108920. doi:10.1016/j.ymssp.2022.108920DOI: 10.1016/j.ymssp.2022.108920
Dai, H., Zhang, R., & Beer, M. (2022). A new perspective on the simulation of cross-correlated random fields. Structural Safety, 96, 102201. doi:10.1016/j.strusafe.2022.102201DOI: 10.1016/j.strusafe.2022.102201
Zhang, H., Bittner, M., & Beer, M. (2022). Method to generate artificial earthquake accelerations with time domain enhancement and attenuation characteristics. AIN SHAMS ENGINEERING JOURNAL, 13(3). doi:10.1016/j.asej.2021.09.031DOI: 10.1016/j.asej.2021.09.031
Pasparakis, G. D., Kougioumtzoglou, I. A., Fragkoulis, V. C., Kong, F., & Beer, M. (2022). Excitation–response relationships for linear structural systems with singular parameter matrices: A periodized harmonic wavelet perspective. Mechanical Systems and Signal Processing, 169, 108701. doi:10.1016/j.ymssp.2021.108701DOI: 10.1016/j.ymssp.2021.108701
Zhang, K., Chen, N., Liu, J., & Beer, M. (2022). A GRU-based ensemble learning method for time-variant uncertain structural response analysis. Computer Methods in Applied Mechanics and Engineering, 391, 114516. doi:10.1016/j.cma.2021.114516DOI: 10.1016/j.cma.2021.114516
Fragkoulis, V. C., Kougioumtzoglou, I. A., Pantelous, A. A., & Beer, M. (2022). Joint Statistics of Natural Frequencies Corresponding to Structural Systems with Singular Random Parameter Matrices. JOURNAL OF ENGINEERING MECHANICS, 148(3). doi:10.1061/(ASCE)EM.1943-7889.0002081DOI: 10.1061/(ASCE)EM.1943-7889.0002081
Jerez, D. J., Jensen, H. A., & Beer, M. (2022). Reliability-based design optimization of structural systems under stochastic excitation: An overview. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 166. doi:10.1016/j.ymssp.2021.108397DOI: 10.1016/j.ymssp.2021.108397
Zhang, H., Bittner, M., & Beer, M. (2022). Seismic Response Meta-model of High-Rise Fame Structure Based on Time-Delay Neural Network. KSCE Journal of Civil Engineering. doi:10.1007/s12205-022-0878-7DOI: 10.1007/s12205-022-0878-7
Behrendt, M., Bittner, M., Comerford, L., Beer, M., & Chen, J. (2022). Relaxed power spectrum estimation from multiple data records utilising subjective probabilities. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 165. doi:10.1016/j.ymssp.2021.108346DOI: 10.1016/j.ymssp.2021.108346
Bi, S., He, K., Zhao, Y., Moens, D., Beer, M., & Zhang, J. (2022). Towards the NASA UQ Challenge 2019: Systematically forward and inverse approaches for uncertainty propagation and quantification. Mechanical Systems and Signal Processing, 165, 108387. doi:10.1016/j.ymssp.2021.108387DOI: 10.1016/j.ymssp.2021.108387
Wan, Z., Chen, J., Tao, W., Wei, P., Beer, M., & Jiang, Z. (2023). A feature mapping strategy of metamodelling for nonlinear stochastic dynamical systems with low to high-dimensional input uncertainties. Mechanical Systems and Signal Processing, 184, 109656. doi:10.1016/j.ymssp.2022.109656DOI: 10.1016/j.ymssp.2022.109656
Morais, C., Yung, K. L., Johnson, K., Moura, R., Beer, M., & Patelli, E. (2022). Identification of human errors and influencing factors: A machine learning approach. Safety Science, 146, 105528. doi:10.1016/j.ssci.2021.105528DOI: 10.1016/j.ssci.2021.105528
Morais, C., Estrada-Lugo, H. D., Tolo, S., Jacques, T., Moura, R., Beer, M., & Patelli, E. (2022). Robust data-driven human reliability analysis using credal networks. Reliability Engineering & System Safety, 218, 107990. doi:10.1016/j.ress.2021.107990DOI: 10.1016/j.ress.2021.107990
Cheng, M., Dang, C., Frangopol, D. M., Beer, M., & Yuan, X. -X. (2022). Transfer prior knowledge from surrogate modelling: A meta-learning approach. Computers & Structures, 260, 106719. doi:10.1016/j.compstruc.2021.106719DOI: 10.1016/j.compstruc.2021.106719
Kitahara, M., Bi, S., Broggi, M., & Beer, M. (2022). Nonparametric Bayesian stochastic model updating with hybrid uncertainties. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 163. doi:10.1016/j.ymssp.2021.108195DOI: 10.1016/j.ymssp.2021.108195
Kitahara, M., Song, J., Wei, P., Broggi, M., & Beer, M. (2022). A Distributionally Robust Approach for Mixed Aleatory and Epistemic Uncertainties Propagation. AIAA JOURNAL, 60(7), 4471-4477. doi:10.2514/1.J061394DOI: 10.2514/1.J061394
Assessing the Severity of Missing Data Problems with the Interval Discrete Fourier Transform Algorithm (Conference Paper)
Behrendt, M., Angelis, M. D., Comerford, L., & Beer, M. (2022). Assessing the Severity of Missing Data Problems with the Interval Discrete Fourier Transform Algorithm. In Book of Extended Abstracts for the 32nd European Safety and Reliability Conference. Research Publishing Services. doi:10.3850/978-981-18-5183-4_s14-05-243-cdDOI: 10.3850/978-981-18-5183-4_s14-05-243-cd
Jerez, D. J., Jensen, H. A., Beer, M., & Chen, J. (2022). Asymptotic Bayesian Optimization: A Markov sampling-based framework for design optimization. PROBABILISTIC ENGINEERING MECHANICS, 67. doi:10.1016/j.probengmech.2021.103178DOI: 10.1016/j.probengmech.2021.103178
Yang, L., Bi, S., Faes, M. G. R., Broggi, M., & Beer, M. (2022). Bayesian inversion for imprecise probabilistic models using a novel entropy-based uncertainty quantification metric. Mechanical Systems and Signal Processing, 162, 107954. doi:10.1016/j.ymssp.2021.107954DOI: 10.1016/j.ymssp.2021.107954
Capturing Epistemic Uncertainties in the Power Spectral Density for Limited Data Sets (Conference Paper)
Behrendt, M., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2022). Capturing Epistemic Uncertainties in the Power Spectral Density for Limited Data Sets. In Probabilistic Safety Assessment and Management, PSAM 2022.
Epistemic Uncertainty Quantification of Localised Seismic Power Spectral Densities (Conference Paper)
Bittner, M., Behrendt, M., Behrensdorf, J., & Beer, M. (2022). Epistemic Uncertainty Quantification of Localised Seismic Power Spectral Densities. In Probabilistic Safety Assessment and Management, PSAM 2022.
Physic-informed probabilistic analysis with Bayesian machine learning in augmented space (Conference Paper)
Hong, F., Wei, P., Song, J., G.R. Faes, M., Valdebenito, M. A., & Beer, M. (2022). Physic-informed probabilistic analysis with Bayesian machine learning in augmented space. In 8th International Symposium on Reliability Engineering and Risk Management. Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-06-055-cdDOI: 10.3850/978-981-18-5184-1_ms-06-055-cd
Wang, Q., Feng, Y., Wu, D., Yang, C., Yu, Y., Li, G., . . . Gao, W. (2022). Polyphase uncertainty analysis through virtual modelling technique. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 162. doi:10.1016/j.ymssp.2021.108013DOI: 10.1016/j.ymssp.2021.108013
Jensen, H. A., Jerez, D. J., & Beer, M. (2022). Structural synthesis considering mixed discrete-continuous design variables: A Bayesian framework. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 162. doi:10.1016/j.ymssp.2021.108042DOI: 10.1016/j.ymssp.2021.108042
Pasparakis, G. D., dos Santos, K. R. M., Kougioumtzoglou, I. A., & Beer, M. (2022). Wind data extrapolation and stochastic field statistics estimation via compressive sampling and low rank matrix recovery methods. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 162. doi:10.1016/j.ymssp.2021.107975DOI: 10.1016/j.ymssp.2021.107975
2021
Uncertainty: Ideas Behind Neural Networks Lead Us Beyond KL-Decomposition and Interval Fields (Conference Paper)
Beer, M., Kosheleva, O., & Kreinovich, V. (2021). Uncertainty: Ideas Behind Neural Networks Lead Us Beyond KL-Decomposition and Interval Fields. In 2021 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2021). doi:10.1109/SSCI50451.2021.9660145DOI: 10.1109/SSCI50451.2021.9660145
Salomon, J., Winnewisser, N., Wei, P., Broggi, M., & Beer, M. (2021). Efficient reliability analysis of complex systems in consideration of imprecision. Reliability Engineering & System Safety, 216, 107972. doi:10.1016/j.ress.2021.107972DOI: 10.1016/j.ress.2021.107972
Ni, P., Fragkoulis, V. C., Kong, F., Mitseas, I. P., & Beer, M. (2021). Response Determination of Nonlinear Systems with Singular Matrices Subject to Combined Stochastic and Deterministic Excitations. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(4), 04021049. doi:10.1061/ajrua6.0001167DOI: 10.1061/ajrua6.0001167
Wang, C., Beer, M., & Ayyub, B. M. (2021). Time-Dependent Reliability of Aging Structures: Overview of Assessment Methods. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(4), 03121003. doi:10.1061/ajrua6.0001176DOI: 10.1061/ajrua6.0001176
Yuan, X., Liu, S., Faes, M., Valdebenito, M. A., & Beer, M. (2021). An efficient importance sampling approach for reliability analysis of time-variant structures subject to time-dependent stochastic load. Mechanical Systems and Signal Processing, 159, 107699. doi:10.1016/j.ymssp.2021.107699DOI: 10.1016/j.ymssp.2021.107699
Jerez, D. J., Jensen, H. A., Beer, M., & Broggi, M. (2021). Contaminant source identification in water distribution networks: A Bayesian framework. Mechanical Systems and Signal Processing, 159, 107834. doi:10.1016/j.ymssp.2021.107834DOI: 10.1016/j.ymssp.2021.107834
Yuan, X., Liu, S., Valdebenito, M. A., Gu, J., & Beer, M. (2021). Efficient procedure for failure probability function estimation in augmented space. Structural Safety, 92, 102104. doi:10.1016/j.strusafe.2021.102104DOI: 10.1016/j.strusafe.2021.102104
Valdebenito, M. A., Wei, P., Song, J., Beer, M., & Broggi, M. (2021). Failure probability estimation of a class of series systems by multidomain Line Sampling. RELIABILITY ENGINEERING & SYSTEM SAFETY, 213. doi:10.1016/j.ress.2021.107673DOI: 10.1016/j.ress.2021.107673
Zhao, M. -Y., Yan, W. -J., Yuen, K. -V., & Beer, M. (2021). Non-probabilistic uncertainty quantification for dynamic characterization functions using complex ratio interval arithmetic operation of multidimensional parallelepiped model. Mechanical Systems and Signal Processing, 156, 107559. doi:10.1016/j.ymssp.2020.107559DOI: 10.1016/j.ymssp.2020.107559
Sensitivity Analysis of an Aircraft Engine Model Under Consideration of Dependent Variables (Conference Paper)
Salomon, J., Göing, J., Lück, S., Broggi, M., Friedrichs, J., & Beer, M. (2021). Sensitivity Analysis of an Aircraft Engine Model Under Consideration of Dependent Variables. In Volume 1: Aircraft Engine; Fans and Blowers; Marine; Wind Energy; Scholar Lecture. American Society of Mechanical Engineers. doi:10.1115/gt2021-58905DOI: 10.1115/gt2021-58905
Valdebenito, M. A., Jensen, H. A., Wei, P., Beer, M., & Beck, A. T. (2021). Application of a Reduced Order Model for Fuzzy Analysis of Linear Static Systems. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 7(2). doi:10.1115/1.4050159DOI: 10.1115/1.4050159
Yuan, X., Faes, M. G. R., Liu, S., Valdebenito, M. A., & Beer, M. (2021). Efficient imprecise reliability analysis using the Augmented Space Integral. RELIABILITY ENGINEERING & SYSTEM SAFETY, 210. doi:10.1016/j.ress.2021.107477DOI: 10.1016/j.ress.2021.107477
Bi, S., Beer, M., Zhang, J., Yang, L., & He, K. (2021). Optimization or Bayesian Strategy? Performance of the Bhattacharyya Distance in Different Algorithms of Stochastic Model Updating. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 7(2). doi:10.1115/1.4050168DOI: 10.1115/1.4050168
Faes, M. G. R., Moens, D., Beer, M., Zhang, H., & Phoon, K. -K. (2021). Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis. ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg, 7(2). doi:10.1115/1.4050256DOI: 10.1115/1.4050256
Faes, M. G. R., Valdebenito, M. A., Yuan, X., Wei, P., & Beer, M. (2021). Augmented reliability analysis for estimating imprecise first excursion probabilities in stochastic linear dynamics. ADVANCES IN ENGINEERING SOFTWARE, 155. doi:10.1016/j.advengsoft.2021.102993DOI: 10.1016/j.advengsoft.2021.102993
Wei, P., Hong, F., Phoon, K. -K., & Beer, M. (2021). Bounds optimization of model response moments: a twin-engine Bayesian active learning method. COMPUTATIONAL MECHANICS, 67(5), 1273-1292. doi:10.1007/s00466-021-01977-8DOI: 10.1007/s00466-021-01977-8
Faes, M. G. R., Valdebenito, M. A., Moens, D., & Beer, M. (2021). Operator norm theory as an efficient tool to propagate hybrid uncertainties and calculate imprecise probabilities. Mechanical Systems and Signal Processing, 152, 107482. doi:10.1016/j.ymssp.2020.107482DOI: 10.1016/j.ymssp.2020.107482
Gong, Z., DiazDelaO, F. A., Hristov, P., & Beer, M. (2021). History Matching and Robust Design through Subset Simulation. International Journal for Uncertainty Quantification. doi:10.1615/int.j.uncertaintyquantification.2021033543DOI: 10.1615/int.j.uncertaintyquantification.2021033543
Bai, Y., Li, Y., Tang, Z., Bittner, M., Broggi, M., & Beer, M. (2021). Seismic collapse fragility of low-rise steel moment frames with mass irregularity based on shaking table test. Bulletin of Earthquake Engineering. doi:10.1007/s10518-021-01076-2DOI: 10.1007/s10518-021-01076-2
Wan, Z., Chen, J., & Beer, M. (2021). Functional perspective of uncertainty quantification for stochastic parametric systems and global sensitivity analysis. Lixue Xuebao/Chinese Journal of Theoretical and Applied Mechanics, 53(3), 837-854. doi:10.6052/0459-1879-20-336DOI: 10.6052/0459-1879-20-336
Zhu, W., Chen, N., Liu, J., & Beer, M. (2021). A probability-box-based method for propagation of multiple types of epistemic uncertainties and its application on composite structural-acoustic system. Mechanical Systems and Signal Processing, 149, 107184. doi:10.1016/j.ymssp.2020.107184DOI: 10.1016/j.ymssp.2020.107184
Wei, P., Liu, F., Valdebenito, M., & Beer, M. (2021). Bayesian probabilistic propagation of imprecise probabilities with large epistemic uncertainty. Mechanical Systems and Signal Processing, 149, 107219. doi:10.1016/j.ymssp.2020.107219DOI: 10.1016/j.ymssp.2020.107219
Pasparakis, G. D., Fragkoulis, V. C., & Beer, M. (2021). Harmonic wavelets based response evolutionary power spectrum determination of linear and nonlinear structural systems with singular matrices. Mechanical Systems and Signal Processing, 149, 107203. doi:10.1016/j.ymssp.2020.107203DOI: 10.1016/j.ymssp.2020.107203
Siju, K. C., Kumar, M., & Beer, M. (2021). Classical and Bayesian estimation of stress-strength reliability of a component having multiple states. INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT, 38(2), 528-535. doi:10.1108/IJQRM-01-2020-0009DOI: 10.1108/ijqrm-01-2020-0009
Song, J., Wei, P., Valdebenito, M., & Beer, M. (2021). Active learning line sampling for rare event analysis. Mechanical Systems and Signal Processing, 147. doi:10.1016/j.ymssp.2020.107113DOI: 10.1016/j.ymssp.2020.107113
Wan, Z. Q., Chen, J. B., & Beer, M. (2021). A PDEM-COM framework for uncertainty quantification of backward issues involving both aleatory and epistemic uncertainties. In IOP Conference Series: Materials Science and Engineering Vol. 1043 (pp. 052058). IOP Publishing. doi:10.1088/1757-899x/1043/5/052058DOI: 10.1088/1757-899x/1043/5/052058
Jensen, H., Jerez, D., & Beer, M. (2021). A general two-phase Markov chain Monte Carlo approach for constrained design optimization: Application to stochastic structural optimization. Computer Methods in Applied Mechanics and Engineering, 373, 113487. doi:10.1016/j.cma.2020.113487DOI: 10.1016/j.cma.2020.113487
Handling the Uncertainty with Confidence in Human Reliability Analysis (Conference Paper)
Morais, C., Ferson, S., Moura, R., Tolo, S., Beer, M., & Patelli, E. (2021). Handling the Uncertainty with Confidence in Human Reliability Analysis. In Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021). Research Publishing Services. doi:10.3850/978-981-18-2016-8_575-cdDOI: 10.3850/978-981-18-2016-8_575-cd
STOCHASTIC NONLINEAR RESPONSE OF STRUCTURAL SYSTEMS ENDOWED WITH SINGULAR MATRICES SUBJECT TO COMBINED PERIODIC AND STOCHASTIC EXCITATIONS (Conference Paper)
Ni, P., Fragkoulis, V. C., Kong, F., Mitseas, I. P., Beer, M., & Fragiadakis, M. (2021). STOCHASTIC NONLINEAR RESPONSE OF STRUCTURAL SYSTEMS ENDOWED WITH SINGULAR MATRICES SUBJECT TO COMBINED PERIODIC AND STOCHASTIC EXCITATIONS. In Proceedings of the 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2015). Institute of Structural Analysis and Antiseismic Research National Technical University of Athens. doi:10.7712/120121.8872.20780DOI: 10.7712/120121.8872.20780
2020
Song, J., Wei, P., Valdebenito, M., & Beer, M. (2020). Adaptive reliability analysis for rare events evaluation with global imprecise line sampling. Computer Methods in Applied Mechanics and Engineering, 372, 113344. doi:10.1016/j.cma.2020.113344DOI: 10.1016/j.cma.2020.113344
He, L., Liu, Y., Bi, S., Wang, L., Broggi, M., & Beer, M. (2020). Estimation of failure probability in braced excavation using Bayesian networks with integrated model updating. Underground Space, 5(4), 315-323. doi:10.1016/j.undsp.2019.07.001DOI: 10.1016/j.undsp.2019.07.001
Yan, W. -J., Zhao, M. -Y., Beer, M., Ren, W. -X., & Chronopoulos, D. (2020). A unified scheme to solving arbitrary complex-valued ratio distribution with application to statistical inference for raw frequency response functions and transmissibility functions. Mechanical Systems and Signal Processing, 145, 106886. doi:10.1016/j.ymssp.2020.106886DOI: 10.1016/j.ymssp.2020.106886
Sarvari, H., Chan, D. W. M., Banaitiene, N., Noor, N. M., & Beer, M. (2020). Barriers to development of private sector investment in water and sewage industry. Built Environment Project and Asset Management, ahead-of-print(ahead-of-print). doi:10.1108/bepam-11-2019-0110DOI: 10.1108/bepam-11-2019-0110
Faes, M. G. R., Valdebenito, M. A., Moens, D., & Beer, M. (2020). Bounding the first excursion probability of linear structures subjected to imprecise stochastic loading. Computers & Structures, 239. doi:10.1016/j.compstruc.2020.106320DOI: 10.1016/j.compstruc.2020.106320
Chen, J., Wan, Z., & Beer, M. (2020). A global sensitivity index based on Fréchet derivative and its efficient numerical analysis. Probabilistic Engineering Mechanics, 62, 103096. doi:10.1016/j.probengmech.2020.103096DOI: 10.1016/j.probengmech.2020.103096
Special Section on Uncertainty Management in Complex Multiphysics Structural Dynamics (Edited special journal issue)
Special Section on Uncertainty Management in Complex Multiphysics Structural Dynamics (2020). (Vol. 6).DOI: 10.1115/1.4047097
Bai, Y., Ma, X., Wang, B., Cao, G., & Beer, M. (2020). Cumulative Component Damages on Collapse Capacity of Ductile Steel and CFT Moment Resisting Frames under Over-design Ground Motions. Journal of Earthquake Engineering, 1-22. doi:10.1080/13632469.2020.1784315DOI: 10.1080/13632469.2020.1784315
Feng, C., Tian, B., Lu, X., Beer, M., Broggi, M., Bi, S., . . . He, T. (n.d.). Bayesian Updating of Soil–Water Character Curve Parameters Based on the Monitor Data of a Large-Scale Landslide Model Experiment. Applied Sciences, 10(16), 5526. doi:10.3390/app10165526DOI: 10.3390/app10165526
Wei, P., Zhang, X., & Beer, M. (2020). Adaptive experiment design for probabilistic integration. Computer Methods in Applied Mechanics and Engineering, 365, 113035. doi:10.1016/j.cma.2020.113035DOI: 10.1016/j.cma.2020.113035
Feng, G., Beer, M., Coolen, F. P. A., Ayyub, B. M., & Phoon, K. K. (2020). Guest Editorial. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 6(2).
Nieto-Cerezo, O., Wenzelburger, J., Patelli, E., & Beer, M. (2020). Optimal Regulation of the Construction of Reliable Sea Defenses. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 6(2), 04020023. doi:10.1061/ajrua6.0001065DOI: 10.1061/ajrua6.0001065
Feng, G., Beer, M., Coolen, F. P. A., Ayyub, B. M., & Phoon, K. -K. (2020). Special Section on Resilience of Engineering Systems. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 6(2). doi:10.1115/1.4046473
Song, J., Valdebenito, M., Wei, P., Beer, M., & Lu, Z. (2020). Non-intrusive imprecise stochastic simulation by line sampling. Structural Safety, 84, 101936. doi:10.1016/j.strusafe.2020.101936DOI: 10.1016/j.strusafe.2020.101936
Morais, C., Moura, R., Beer, M., & Patelli, E. (2020). Analysis and Estimation of Human Errors From Major Accident Investigation Reports. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 6(1). doi:10.1115/1.4044796DOI: 10.1115/1.4044796
Valdebenito, M. A., Beer, M., Jensen, H. A., Chen, J., & Wei, P. (2020). Fuzzy failure probability estimation applying intervening variables. Structural Safety, 83, 101909. doi:10.1016/j.strusafe.2019.101909DOI: 10.1016/j.strusafe.2019.101909
Moura, R., Beer, M., & Podofillini, L. (2020). Special Issue on Human Performance and Decision-Making in Complex Industrial Environments. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 6(1). doi:10.1115/1.4045557DOI: 10.1115/1.4045557
A PDEM-COM framework for quantification of epistemic uncertainty (Conference Paper)
Wan, Z., Chen, J., Li, J., & Beer, M. (2020). A PDEM-COM framework for quantification of epistemic uncertainty. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2622-2627). doi:10.3850/978-981-11-2724-30969-cdDOI: 10.3850/978-981-11-2724-30969-cd
BAYESIAN MODEL UPDATING FOR EXISTING SEISMIC-ISOLATED BRIDGES USING OBSERVED ACCELERATION RESPONSE DATA (Conference Paper)
Kitahara, M., Broggi, M., & Beer, M. (2020). BAYESIAN MODEL UPDATING FOR EXISTING SEISMIC-ISOLATED BRIDGES USING OBSERVED ACCELERATION RESPONSE DATA. In XI International Conference on Structural Dynamics. EASD. doi:10.47964/1120.9291.18937DOI: 10.47964/1120.9291.18937
Breaking the Double Loop: Operator Norm Theory as a Tool to Compute with Imprecise Probabilities (Conference Paper)
Faes, M. G. R., Valdebenito, M. A., Moens, D., & Beer, M. (2020). Breaking the Double Loop: Operator Norm Theory as a Tool to Compute with Imprecise Probabilities. In Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference. Research Publishing Services. doi:10.3850/978-981-14-8593-0_5707-cdDOI: 10.3850/978-981-14-8593-0_5707-cd
Common cause failure importance analysis for aerospace systems (Conference Paper)
Mi, J., Beer, M., Li, Y. F., Broggi, M., & Cheng, Y. (2020). Common cause failure importance analysis for aerospace systems. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2325-2331). doi:10.3850/978-981-11-2724-30855-cdDOI: 10.3850/978-981-11-2724-30855-cd
Components Importance Ranking Considering the Effect of Epistemic Uncertainty (Conference Paper)
Song, J., Lu, Z., & Beer, M. (2019). Components Importance Ranking Considering the Effect of Epistemic Uncertainty. In Proceedings of the 29th European Safety and Reliability Conference (ESREL). Research Publishing Services. doi:10.3850/978-981-11-2724-3_0724-cdDOI: 10.3850/978-981-11-2724-3_0724-cd
Decision Making for Optimal Primary-Support Selection to Minimise Tunnel- Squeezing Risk (Conference Paper)
Chen, Y., Patelli, E., Zeng, P., Edwards, B., Li, T., & Beer, M. (2020). Decision Making for Optimal Primary-Support Selection to Minimise Tunnel- Squeezing Risk. In Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference. Research Publishing Services. doi:10.3850/978-981-14-8593-0_4170-cdDOI: 10.3850/978-981-14-8593-0_4170-cd
Decision making for optimal primary-support selection to minimise tunnel-squeezing risk (Conference Paper)
Chen, Y., Patelli, E., Zeng, P., Edwards, B., Li, T., & Beer, M. (2020). Decision making for optimal primary-support selection to minimise tunnel-squeezing risk. In 30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020 (pp. 2257-2264).
Efficient Reliability Analysis of an Axial Compressor in Consideration of Epistemic Uncertainty (Conference Paper)
Salomon, J., Winnewisser, N., Wei, P., Broggi, M., & Beer, M. (2020). Efficient Reliability Analysis of an Axial Compressor in Consideration of Epistemic Uncertainty. In Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference. Research Publishing Services. doi:10.3850/978-981-14-8593-0_3685-cdDOI: 10.3850/978-981-14-8593-0_3685-cd
Efficient propagation of imprecise probability models by imprecise line sampling (Conference Paper)
Wei, P., Song, J., Valdebenito, M. A., & Beer, M. (2020). Efficient propagation of imprecise probability models by imprecise line sampling. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2072-2077). doi:10.3850/978-981-11-0745-00994-cdDOI: 10.3850/978-981-11-0745-00994-cd
Efficient reliability analysis of an axial compressor in consideration of epistemic uncertainty (Conference Paper)
Salomon, J., Winnewisser, N., Wei, P., Broggi, M., & Beer, M. (2020). Efficient reliability analysis of an axial compressor in consideration of epistemic uncertainty. In 30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020 (pp. 4791-4798).
Mi, J., Li, Y. -F., Beer, M., Broggi, M., & Cheng, Y. (2020). IMPORTANCE MEASURE OF PROBABILISTIC COMMON CAUSE FAILURES UNDER SYSTEM HYBRID UNCERTAINTY BASED ON BAYESIAN NETWORK. EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 22(1), 112-120. doi:10.17531/ein.2020.1.13DOI: 10.17531/ein.2020.1.13
Imprecise stochastic dynamics via operator norm theory (Conference Paper)
Faes, M. G. R., Valdebenito, M. A., Beer, M., & Moens, D. (2020). Imprecise stochastic dynamics via operator norm theory. In PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2020) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2020) (pp. 3707-3717). Retrieved from https://www.webofscience.com/
Measuring systemic risk for mechanical structures using conditional probability (Conference Paper)
Eckert, C., & Beer, M. (2020). Measuring systemic risk for mechanical structures using conditional probability. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 4316-4320). doi:10.3850/978-981-11-0745-0-1137-cdDOI: 10.3850/978-981-11-0745-0-1137-cd
Model updating of model parameters and model form error in a uniform framework (Conference Paper)
Bi, S., Wagner, N., Beer, M., & Ouisse, M. (2020). Model updating of model parameters and model form error in a uniform framework. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2679-2684). doi:10.3850/978-981-11-2724-30972-cdDOI: 10.3850/978-981-11-2724-30972-cd
Multidimensional resilience decision-making on a multistage high-speed axial compressor (Conference Paper)
Salomon, J., Behrensdorf, J., Broggi, M., Weber, S., & Beer, M. (2020). Multidimensional resilience decision-making on a multistage high-speed axial compressor. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 1357-1364). doi:10.3850/978-981-11-2724-30992-cdDOI: 10.3850/978-981-11-2724-30992-cd
PARAMETER INVESTIGATION OF RELAXED UNCERTAIN POWER SPECTRA FOR STOCHASTIC DYNAMIC SYSTEMS (Conference Paper)
Behrendt, M., Bittner, M., Comerford, L., Broggi, M., & Beer, M. (2020). PARAMETER INVESTIGATION OF RELAXED UNCERTAIN POWER SPECTRA FOR STOCHASTIC DYNAMIC SYSTEMS. In XI International Conference on Structural Dynamics. EASD. doi:10.47964/1120.9311.18861DOI: 10.47964/1120.9311.18861
Preface (Conference Paper)
Beer, M., & Zio, E. (2020). Preface. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019.
Probabilistic modelling for frequency response functions and transmissibility functions with complex ratio statistics (Conference Paper)
Zhao, M. Y., Yan, W. J., Ren, W. X., & Beer, M. (2020). Probabilistic modelling for frequency response functions and transmissibility functions with complex ratio statistics. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2714-2718). doi:10.3850/978-981-11-2724-30827-cdDOI: 10.3850/978-981-11-2724-30827-cd
Rare event modelling for stochastic dynamic systems approximated by the probability density evolution method (Conference Paper)
Bittner, M., Broggi, M., & Beer, M. (2020). Rare event modelling for stochastic dynamic systems approximated by the probability density evolution method. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2719-2726). doi:10.3850/978-981-11-2724-30735-cdDOI: 10.3850/978-981-11-2724-30735-cd
Jiang, Y., Peng, S., Beer, M., Wang, L., & Zhang, J. (2020). Reliability evaluation of reinforced concrete columns designed by Eurocode for wind-dominated combination considering random loads eccentricity. ADVANCES IN STRUCTURAL ENGINEERING, 23(1), 146-159. doi:10.1177/1369433219866089DOI: 10.1177/1369433219866089
Tackling the lack of data for human error probability with Credal network (Conference Paper)
Morais, C., Tolo, S., Moura, R., Beer, M., & Patelli, E. (2020). Tackling the lack of data for human error probability with Credal network. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 382-386). doi:10.3850/978-981-11-2724-30746-cdDOI: 10.3850/978-981-11-2724-30746-cd
Beer, M., Urenda, J., Kosheleva, O., & Kreinovich, V. (2020). Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria. In Unknown Conference (pp. 70-79). Springer International Publishing. doi:10.1007/978-3-030-50146-4_6DOI: 10.1007/978-3-030-50146-4_6
Beer, M., Urenda, J., Kosheleva, O., & Kreinovich, V. (n.d.). Why Spiking Neural Networks Are Efficient: A Theorem. In Unknown Conference (pp. 59-69). Springer International Publishing. doi:10.1007/978-3-030-50146-4_5DOI: 10.1007/978-3-030-50146-4_5
2019
Development of a Relaxed Stationary Power Spectrum using Imprecise Probabilities with Application to High-rise Buildings (Conference Paper)
Behrendt, M., Comerford, L., & Beer, M. (2019). Development of a Relaxed Stationary Power Spectrum using Imprecise Probabilities with Application to High-rise Buildings. In 2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019) (pp. 784-790). Retrieved from https://www.webofscience.com/
Zhang, Y., Gomes, A. T., Beer, M., Neumann, I., Nackenhorst, U., & Kim, C. -W. (2019). Modeling asymmetric dependences among multivariate soil data for the geotechnical analysis - The asymmetric copula approach. SOILS AND FOUNDATIONS, 59(6), 1960-1979. doi:10.1016/j.sandf.2019.09.001DOI: 10.1016/j.sandf.2019.09.001
Faes, M., Sadeghi, J., Broggi, M., de AngDelis, M., Patelli, E., Beer, M., & Moens, D. (2019). On the Robust Estimation of Small Failure Probabilities for Strong Nonlinear Models. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 5(4). doi:10.1115/1.4044044DOI: 10.1115/1.4044044
Sensitivity analysis of prior beliefs in advanced Bayesian networks (Conference Paper)
He, L., Beer, M., Broggi, M., Wei, P., & Gomes, A. T. (2019). Sensitivity analysis of prior beliefs in advanced Bayesian networks. In 2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019) (pp. 776-783). Retrieved from https://www.webofscience.com/
Wang, C., Zhang, H., & Beer, M. (2019). Structural Time-Dependent Reliability Assessment with New Power Spectral Density Function. JOURNAL OF STRUCTURAL ENGINEERING, 145(12). doi:10.1061/(ASCE)ST.1943-541X.0002476DOI: 10.1061/(ASCE)ST.1943-541X.0002476
Rasani, M. R., Moria, H., Beer, M., & Ariffin, A. K. (2019). Vibration Performance of a Flow Energy Converter behind Two Side-By-Side Cylinders. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 7(12). doi:10.3390/jmse7120435DOI: 10.3390/jmse7120435
Mitseas, I. P., & Beer, M. (2019). Fragility analysis of nonproportionally damped inelastic MDOF structural systems exposed to stochastic seismic excitation. Computers and Structures. doi:10.1016/j.compstruc.2019.106129DOI: 10.1016/j.compstruc.2019.106129
Beer, M. (2019). Resilience Decision-Making for Complex Systems. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering. doi:10.1115/1.4044907DOI: 10.1115/1.4044907
Computation of Hybrid Uncertainty and Dependent Failure in System Reliability Analysis and Assessment (Conference Paper)
Song, Y. -F., Mi, J., Cheng, Y., Beer, M., & Broggi, M. (2019). Computation of Hybrid Uncertainty and Dependent Failure in System Reliability Analysis and Assessment. In 2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE). IEEE. doi:10.1109/qr2mse46217.2019.9021202DOI: 10.1109/qr2mse46217.2019.9021202
Fragkoulis, V. C., Kougioumtzoglou, I. A., Pantelous, A. A., & Beer, M. (2019). Non-stationary response statistics of nonlinear oscillators with fractional derivative elements under evolutionary stochastic excitation. Nonlinear Dynamics. doi:10.1007/s11071-019-05124-0DOI: 10.1007/s11071-019-05124-0
Wei, P., Song, J., Bi, S., Broggi, M., Beer, M., Lu, Z., & Yue, Z. (2019). Non-intrusive stochastic analysis with parameterized imprecise probability models: II. Reliability and rare events analysis. Mechanical Systems and Signal Processing, 126, 227-247. doi:10.1016/j.ymssp.2019.02.015DOI: 10.1016/j.ymssp.2019.02.015
He, L., Gomes, A. T., Broggi, M., & Beer, M. (2019). Failure Analysis of Soil Slopes with Advanced Bayesian Networks. PERIODICA POLYTECHNICA-CIVIL ENGINEERING, 63(3), 763-774. doi:10.3311/PPci.14092DOI: 10.3311/PPci.14092
Zhang, Y., Gomes, A. T., Beer, M., Neumann, I., Nackenhorst, U., & Kim, C. -W. (2019). Reliability analysis with consideration of asymmetrically dependent variables: Discussion and application to geotechnical examples. RELIABILITY ENGINEERING & SYSTEM SAFETY, 185, 261-277. doi:10.1016/j.ress.2018.12.025DOI: 10.1016/j.ress.2018.12.025
Bi, S., Broggi, M., Wei, P., & Beer, M. (2019). The Bhattacharyya distance: Enriching the P-box in stochastic sensitivity analysis. Mechanical Systems and Signal Processing, 129, 265-281. doi:10.1016/j.ymssp.2019.04.035DOI: 10.1016/j.ymssp.2019.04.035
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). A multivariate interval approach for inverse uncertainty quantification with limited experimental data. Mechanical Systems and Signal Processing, 118, 534-548. doi:10.1016/j.ymssp.2018.08.050DOI: 10.1016/j.ymssp.2018.08.050
Approaches to Risk Identification in Public–Private Partnership Projects: Malaysian Private Partners’ Overview (Journal article)
Sarvari, H., Valipour, A., Yahya, N., Noor, N. M. D., Beer, M., & Banaitiene, N. (2019). Approaches to Risk Identification in Public-Private Partnership Projects: Malaysian Private Partners' Overview. ADMINISTRATIVE SCIENCES, 9(1). doi:10.3390/admsci9010017DOI: 10.3390/admsci9010017
Bi, S., Broggi, M., & Beer, M. (2019). The role of the Bhattacharyya distance in stochastic model updating. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 117, 437-452. doi:10.1016/j.ymssp.2018.08.017DOI: 10.1016/j.ymssp.2018.08.017
Chen, N., Xia, S., Yu, D., Liu, J., & Beer, M. (2019). Hybrid interval and random analysis for structural-acoustic systems including periodical composites and multi-scale bounded hybrid uncertain parameters. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 115, 524-544. doi:10.1016/j.ymssp.2018.06.016DOI: 10.1016/j.ymssp.2018.06.016
A collocation scheme for deep uncertainty treatment (Conference Paper)
Dannert, M. M., Fau, A., Fleury, R. M. N., Broggi, M., Nackenhorst, U., & Beer, M. (2019). A collocation scheme for deep uncertainty treatment. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
A collocation scheme for deep uncertainty treatment (Conference Paper)
Dannert, M. M., Fau, A., Fleury, R. M. N., Broggi, M., Nackenhorst, U., & Beer, M. (2019). A collocation scheme for deep uncertainty treatment. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
A collocation scheme for deep uncertainty treatment (Conference Paper)
Dannert, M. M., Fau, A., Fleury, R. M. N., Broggi, M., Nackenhorst, U., & Beer, M. (2019). A collocation scheme for deep uncertainty treatment. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
A collocation scheme for deep uncertainty treatment (Conference Paper)
Dannert, M. M., Fau, A., Fleury, R. M. N., Broggi, M., Nackenhorst, U., & Beer, M. (2019). A collocation scheme for deep uncertainty treatment. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis (Conference Paper)
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2019). An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis (Conference Paper)
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2019). An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis (Conference Paper)
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2019). An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis (Conference Paper)
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2019). An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Identification of system matrices based on experimental modal analysis and its application in structural health monitoring (Conference Paper)
Bi, S., Beer, M., Ouisse, M., & Foltête, E. (2019). Identification of system matrices based on experimental modal analysis and its application in structural health monitoring. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Identification of system matrices based on experimental modal analysis and its application in structural health monitoring (Conference Paper)
Bi, S., Beer, M., Ouisse, M., & Foltête, E. (2019). Identification of system matrices based on experimental modal analysis and its application in structural health monitoring. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Identification of system matrices based on experimental modal analysis and its application in structural health monitoring (Conference Paper)
Bi, S., Beer, M., Ouisse, M., & Foltête, E. (2019). Identification of system matrices based on experimental modal analysis and its application in structural health monitoring. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Identification of system matrices based on experimental modal analysis and its application in structural health monitoring (Conference Paper)
Bi, S., Beer, M., Ouisse, M., & Foltête, E. (2019). Identification of system matrices based on experimental modal analysis and its application in structural health monitoring. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach? (Conference Paper)
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach? (Conference Paper)
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach? (Conference Paper)
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach? (Conference Paper)
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Pathways for uncertainty quantification through stochastic damage constitutive models of concrete (Conference Paper)
Wan, Z., Chen, J., & Beer, M. (2019). Pathways for uncertainty quantification through stochastic damage constitutive models of concrete. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Pathways for uncertainty quantification through stochastic damage constitutive models of concrete (Conference Paper)
Wan, Z., Chen, J., & Beer, M. (2019). Pathways for uncertainty quantification through stochastic damage constitutive models of concrete. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Pathways for uncertainty quantification through stochastic damage constitutive models of concrete (Conference Paper)
Wan, Z., Chen, J., & Beer, M. (2019). Pathways for uncertainty quantification through stochastic damage constitutive models of concrete. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Pathways for uncertainty quantification through stochastic damage constitutive models of concrete (Conference Paper)
Wan, Z., Chen, J., & Beer, M. (2019). Pathways for uncertainty quantification through stochastic damage constitutive models of concrete. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
RELAXED STATIONARY POWER SPECTRUM MODEL USING IMPRECISE PROBABILITIES (Conference Paper)
Behrendt, M., Comerford, L., & Beer, M. (2019). RELAXED STATIONARY POWER SPECTRUM MODEL USING IMPRECISE PROBABILITIES. In Proceedings of the 7th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2015). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120119.6941.19045DOI: 10.7712/120119.6941.19045
Rare failure event analysis of structures under mixed uncertainties (Conference Paper)
Wei, P., Bi, S., Zhang, Y., & Beer, M. (2019). Rare failure event analysis of structures under mixed uncertainties. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Rare failure event analysis of structures under mixed uncertainties (Conference Paper)
Wei, P., Bi, S., Zhang, Y., & Beer, M. (2019). Rare failure event analysis of structures under mixed uncertainties. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Rare failure event analysis of structures under mixed uncertainties (Conference Paper)
Wei, P., Bi, S., Zhang, Y., & Beer, M. (2019). Rare failure event analysis of structures under mixed uncertainties. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Rare failure event analysis of structures under mixed uncertainties (Conference Paper)
Wei, P., Bi, S., Zhang, Y., & Beer, M. (2019). Rare failure event analysis of structures under mixed uncertainties. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Stochastic processes identification from data ensembles via power spectrum classification (Conference Paper)
Behrendt, M., Comerford, L., & Beer, M. (2019). Stochastic processes identification from data ensembles via power spectrum classification. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Stochastic processes identification from data ensembles via power spectrum classification (Conference Paper)
Behrendt, M., Comerford, L., & Beer, M. (2019). Stochastic processes identification from data ensembles via power spectrum classification. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Stochastic processes identification from data ensembles via power spectrum classification (Conference Paper)
Behrendt, M., Comerford, L., & Beer, M. (2019). Stochastic processes identification from data ensembles via power spectrum classification. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Stochastic processes identification from data ensembles via power spectrum classification (Conference Paper)
Behrendt, M., Comerford, L., & Beer, M. (2019). Stochastic processes identification from data ensembles via power spectrum classification. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Tightening the bound estimate of structural reliability under imprecise probability information (Conference Paper)
Wang, C., Zhang, H., & Beer, M. (2019). Tightening the bound estimate of structural reliability under imprecise probability information. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Tightening the bound estimate of structural reliability under imprecise probability information (Conference Paper)
Wang, C., Zhang, H., & Beer, M. (2019). Tightening the bound estimate of structural reliability under imprecise probability information. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Tightening the bound estimate of structural reliability under imprecise probability information (Conference Paper)
Wang, C., Zhang, H., & Beer, M. (2019). Tightening the bound estimate of structural reliability under imprecise probability information. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Tightening the bound estimate of structural reliability under imprecise probability information (Conference Paper)
Wang, C., Zhang, H., & Beer, M. (2019). Tightening the bound estimate of structural reliability under imprecise probability information. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
2018
Chen, N., Hu, Y., Yu, D., Liu, J., & Beer, M. (2018). A polynomial expansion approach for response analysis of periodical composite structural-acoustic problems with multi-scale mixed aleatory and epistemic uncertainties. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 342, 509-531. doi:10.1016/j.cma.2018.08.021DOI: 10.1016/j.cma.2018.08.021
George-Williams, H., Feng, G., Coolen, F. P. A., Beer, M., & Patelli, E. (2018). Extending the survival signature paradigm to complex systems with non-repairable dependent failures. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. doi:10.1177/1748006X18808085DOI: 10.1177/1748006X18808085
Surface crack growth prediction under fatigue load using probabilistic S-version finite element model (Journal article)
Akramin, M. R. M., Ariffin, A. K., Kikuchi, M., Beer, M., Shaari, M. S., & Husnain, M. N. M. (2018). Surface crack growth prediction under fatigue load using probabilistic S-version finite element model. JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 40(11). doi:10.1007/s40430-018-1442-8DOI: 10.1007/s40430-018-1442-8
Wang, C., Zhang, H., & Beer, M. (2018). Computing tight bounds of structural reliability under imprecise probabilistic information. COMPUTERS & STRUCTURES, 208, 92-104. doi:10.1016/j.compstruc.2018.07.003DOI: 10.1016/j.compstruc.2018.07.003
Regenhardt, T. E., Azad, M. S., Punurai, W., & Beer, M. (2018). A Novel Application of System Survival Signature in Reliability Assessment of Offshore Structures. In Advances in Intelligent Systems and Computing Vol. 866 (pp. 11-20). doi:10.1007/978-3-030-00979-3_2DOI: 10.1007/978-3-030-00979-3_2
Efficient Reliability and Risk Analysis of Complex Interconnected Systems (Conference Paper)
Behrensdorf, J., Broggi, M., & Beer, M. (2018). Efficient Reliability and Risk Analysis of Complex Interconnected Systems. In RESILIENCE ENGINEERING FOR URBAN TUNNELS (pp. 43-54). Retrieved from https://www.webofscience.com/
Reliability of Critical Infrastructure Networks: Challenges (Conference Paper)
Zuev, K. M., & Beer, M. (2018). Reliability of Critical Infrastructure Networks: Challenges. In RESILIENCE ENGINEERING FOR URBAN TUNNELS (pp. 71-82). Retrieved from https://www.webofscience.com/
Comerford, L., Mannis, A., DeAngelis, M., Kougioumtzoglou, I. A., & Beer, M. (2018). Utilising database-driven interactive software to enhance independent home-study in a flipped classroom setting: going beyond visualising engineering concepts to ensuring formative assessment. EUROPEAN JOURNAL OF ENGINEERING EDUCATION, 43(4), 522-537. doi:10.1080/03043797.2017.1293617DOI: 10.1080/03043797.2017.1293617
An efficient reliability analysis on complex non-repairable systems with common-cause failures (Conference Paper)
Feng, G., George-Williams, H., Patelli, E., Coolen, F. P. A., & Beer, M. (2018). An efficient reliability analysis on complex non-repairable systems with common-cause failures. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 2531-2537). Retrieved from https://www.webofscience.com/
Application of fuzzy finite element method in addressing the presence of uncertainties (Conference Paper)
Yusmye, A. Y. N., Ariffin, A. K., Abdullah, S., Singh, S. S. K., & Beer, M. (2018). Application of fuzzy finite element method in addressing the presence of uncertainties. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 2701-2706). Retrieved from https://www.webofscience.com/
Morais, C., Moura, R., Beer, M., & Patelli, E. (2018). Human reliability analysis-accounting for human actions and external factors through the project life cycle. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 329-338). Retrieved from https://www.webofscience.com/
Imprecise reliability analysis of complex interconnected networks (Conference Paper)
Behrensdorf, J., Broggi, M., & Beer, M. (2018). Imprecise reliability analysis of complex interconnected networks. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 2589-2594). Retrieved from https://www.webofscience.com/
Mitseas, I. P., Kougioumtzoglou, I. A., Giaralis, A., & Beer, M. (2018). A novel stochastic linearization framework for seismic demand estimation of hysteretic MDOF systems subject to linear response spectra. STRUCTURAL SAFETY, 72, 84-98. doi:10.1016/j.strusafe.2017.12.008DOI: 10.1016/j.strusafe.2017.12.008
Zhong, S., Pantelous, A. A., Beer, M., & Zhou, J. (2018). Constrained non-linear multi-objective optimisation of preventive maintenance scheduling for offshore wind farms. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 104, 347-369. doi:10.1016/j.ymssp.2017.10.035DOI: 10.1016/j.ymssp.2017.10.035
Chen, N., Yu, D., Xia, B., & Beer, M. (2018). Hybrid Uncertain Analysis for Exterior Acoustic Field Prediction with Interval Random Parameters. INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS, 15(2). doi:10.1142/S0219876218500068DOI: 10.1142/S0219876218500068
Zhang, Y., Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2018). <i>L<sub>p</sub></i>-norm minimization for stochastic process power spectrum estimation subject to incomplete data. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 101, 361-376. doi:10.1016/j.ymssp.2017.08.017DOI: 10.1016/j.ymssp.2017.08.017
Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure (Conference Paper)
Broggi, M., Faes, M., Patelli, E., Govers, Y., Moens, D., & Beer, M. (2017). Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE. doi:10.1109/ssci.2017.8280882DOI: 10.1109/ssci.2017.8280882
How Accurate Are Expert Estimations of Correlation? (Conference Paper)
Beer, M., Gong, Z., Diaz De La, O. F. A., & Kreinovich, V. (2017). How Accurate Are Expert Estimations of Correlation?. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE. doi:10.1109/ssci.2017.8280790DOI: 10.1109/ssci.2017.8280790
Revealing prediction uncertainty in artificial neural network based reconstruction of missing data in stochastic process records utilizing extreme learning machines (Conference Paper)
Comerford, L., Beer, M., & Lu, N. (2017). Revealing prediction uncertainty in artificial neural network based reconstruction of missing data in stochastic process records utilizing extreme learning machines. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE. doi:10.1109/ssci.2017.8285295DOI: 10.1109/ssci.2017.8285295
Tolo, S., Patelli, E., & Beer, M. (2018). An open toolbox for the reduction, inference computation and sensitivity analysis of Credal Networks. ADVANCES IN ENGINEERING SOFTWARE, 115, 126-148. doi:10.1016/j.advengsoft.2017.09.003DOI: 10.1016/j.advengsoft.2017.09.003
Morais, C., Moura, R., Beer, M., & Patelli, E. (2018). Attempt to predict human error probability in different industry sectors using data from major accidents and Bayesian networks. In PSAM 2018 - Probabilistic Safety Assessment and Management.
Bayesian model updating using stochastic distances as uncertainty quantification metrics (Conference Paper)
Bi, S., Broggi, M., Beer, M., & Zhang, Y. (2018). Bayesian model updating using stochastic distances as uncertainty quantification metrics. In PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2018) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2018) (pp. 5157-5167). Retrieved from https://www.webofscience.com/
Lu, N., Liu, Y., & Beer, M. (2018). Extrapolation of extreme traffic load effects on a cable-stayed bridge based on weigh-in-motion measurements. In International Journal of Reliability and Safety Vol. 12 (pp. 69). Inderscience Publishers. doi:10.1504/ijrs.2018.092504DOI: 10.1504/IJRS.2018.092504
What If We Do Not Know Correlations? (Chapter)
Beer, M., Gong, Z., Neumann, I., Sriboonchitta, S., & Kreinovich, V. (2018). What If We Do Not Know Correlations?. In ECONOMETRICS FOR FINANCIAL APPLICATIONS (Vol. 760, pp. 78-85). doi:10.1007/978-3-319-73150-6_5DOI: 10.1007/978-3-319-73150-6_5
2017
Attarzadeh, M., Chua, D. K. H., Beer, M., & Abbott, E. L. S. (2017). Options-based negotiation management of PPP-BOT infrastructure projects. CONSTRUCTION MANAGEMENT AND ECONOMICS, 35(11-12), 676-692. doi:10.1080/01446193.2017.1325962DOI: 10.1080/01446193.2017.1325962
Yan, D., Luo, Y., Lu, N., Yuan, M., & Beer, M. (2017). Fatigue Stress Spectra and Reliability Evaluation of Short- to Medium-Span Bridges under Stochastic and Dynamic Traffic Loads. JOURNAL OF BRIDGE ENGINEERING, 22(12). doi:10.1061/(ASCE)BE.1943-5592.0001137DOI: 10.1061/(ASCE)BE.1943-5592.0001137
Tolo, S., Patelli, E., & Beer, M. (2017). Robust vulnerability analysis of nuclear facilities subject to external hazards. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 31(10), 2733-2756. doi:10.1007/s00477-016-1360-1DOI: 10.1007/s00477-016-1360-1
Zhang, Y., Comerford, L., Kougioumtzoglou, I. A., Patelli, E., & Beer, M. (2017). Uncertainty Quantification of Power Spectrum and Spectral Moments Estimates Subject to Missing Data. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 3(4). doi:10.1061/AJRUA6.0000925DOI: 10.1061/AJRUA6.0000925
Learning from accidents: interactions between human factors, technology and organisations as a central element to validate risk studies (Journal article)
Moura, R., beer, M., Patelli, E., Lewis, J., & Knoll, F. (2017). Learning from accidents: interactions between human factors, technology and organisations as a central element to validate risk studies. Safety Science, 99(Part B), 196-214. doi:10.1016/j.ssci.2017.05.001DOI: 10.1016/j.ssci.2017.05.001
Moura, R., Beer, M., Patelli, E., & Lewis, J. (2017). Learning from major accidents: Graphical representation and analysis of multi-attribute events to enhance risk communication. SAFETY SCIENCE, 99, 58-70. doi:10.1016/j.ssci.2017.03.005DOI: 10.1016/j.ssci.2017.03.005
Lu, N., Beer, M., Noori, M., & Liu, Y. (2017). Lifetime Deflections of Long-Span Bridges under Dynamic and Growing Traffic Loads. JOURNAL OF BRIDGE ENGINEERING, 22(11). doi:10.1061/(ASCE)BE.1943-5592.0001125DOI: 10.1061/(ASCE)BE.1943-5592.0001125
Attarzadeh, M., Chua, D. K. H., Beer, M., & Abbott, E. L. S. (2017). Fuzzy Randomness Simulation of Long-Term Infrastructure Projects. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 3(3), 04017002. doi:10.1061/AJRUA6.0000902DOI: 10.1061/AJRUA6.0000902
Zhang, H., Ha, L., Li, Q., & Beer, M. (2017). Imprecise probability analysis of steel structures subject to atmospheric corrosion. Structural Safety, 67, 62-69. doi:10.1016/j.strusafe.2017.04.001DOI: 10.1016/j.strusafe.2017.04.001
de Angelis, M., Patelli, E., & Beer, M. (2017). Forced Monte Carlo Simulation Strategy for the Design of Maintenance Plans with Multiple Inspections. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 3(2). doi:10.1061/AJRUA6.0000868DOI: 10.1061/AJRUA6.0000868
Tolo, S., Patelli, E., & Beer, M. (2017). Risk Assessment of Spent Nuclear Fuel Facilities Considering Climate Change. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 3(2). doi:10.1061/AJRUA6.0000874DOI: 10.1061/AJRUA6.0000874
Special Issue on Complex Engineered Networks: Reliability, Risk, and Uncertainty (Journal article)
Zuev, K. M., & Beer, M. (2017). Special Issue on Complex Engineered Networks: Reliability, Risk, and Uncertainty. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 3(2). doi:10.1115/1.4036240DOI: 10.1115/1.4036240
Comerford, L., Jensen, H. A., Mayorga, F., Beer, M., & Kougioumtzoglou, I. A. (2017). Compressive sensing with an adaptive wavelet basis for structural system response and reliability analysis under missing data. COMPUTERS & STRUCTURES, 182, 26-40. doi:10.1016/j.compstruc.2016.11.012DOI: 10.1016/j.compstruc.2016.11.012
Jiang, Y., Zhou, H., Beer, M., Wang, L., Zhang, J., & Zhao, L. (2017). Robustness of Load and Resistance Design Factors for RC Columns with Wind-Dominated Combination Considering Random Eccentricity. JOURNAL OF STRUCTURAL ENGINEERING, 143(4). doi:10.1061/(ASCE)ST.1943-541X.0001720DOI: 10.1061/(ASCE)ST.1943-541X.0001720
Bayesian model calibration using subset simulation (Conference Paper)
Gong, Z. T., DiazDelaO, F. A., & Beer, M. (2017). Bayesian model calibration using subset simulation. In RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE (pp. 293-298). Retrieved from https://www.webofscience.com/
Bayesian model calibration using subset simulation (Conference Paper)
Gong, Z. T., DiazDelaO, F. A., & Beer, M. (2017). Bayesian model calibration using subset simulation. In Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 (pp. 50).
Comparison of Bayesian and Interval Uncertainty Quantification: Application to the AIRMOD Test Structure (Conference Paper)
Broggi, M., Faes, M., Patelli, E., Govers, Y., Moens, D., & Beer, M. (2017). Comparison of Bayesian and Interval Uncertainty Quantification: Application to the AIRMOD Test Structure. In 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) (pp. 1684-1691). Retrieved from https://www.webofscience.com/
Feng, G., Patelli, E., Beer, M., & Coolen, F. P. A. (2017). Component importance measures for complex repairable system. In Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 (pp. 252).
Feng, G., Reed, S., Patelli, E., Beer, M., & Coolen, F. P. A. (2017). EFFICIENT RELIABILITY AND UNCERTAINTY ASSESSMENT ON LIFELINE NETWORKS USING THE SURVIVAL SIGNATURE. In Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120217.5354.16865DOI: 10.7712/120217.5354.16865
How Accurate Are Expert Estimations of Correlation? (Conference Paper)
Beer, M., Gong, Z., Diaz De La, F. A. O., & Kreinovich, V. (2017). How Accurate Are Expert Estimations of Correlation?. In 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) (pp. 883-891). Retrieved from https://www.webofscience.com/
Moura, R., Patelli, E., Lewis, J., Morais, C., & Beer, M. (2017). Human factors influencing decision-making: Tendencies from first-line management decisions and implications to reduce major accidents. In Safety and Reliability – Theory and Applications. CRC Press. doi:10.1201/9781315210469-34DOI: 10.1201/9781315210469-34
Learning from accidents: Investigating the genesis of human errors in multi-attribute settings to improve the organisation of design (Conference Paper)
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2017). Learning from accidents: Investigating the genesis of human errors in multi-attribute settings to improve the organisation of design. In Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 (pp. 38).
Brandt, S., Broggi, M., Haefele, J., Gebhardt, C. G., Rolfes, R., & Beer, M. (2017). Meta-models for fatigue damage estimation of offshore wind turbines jacket substructures. In X INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2017) Vol. 199 (pp. 1158-1163). doi:10.1016/j.proeng.2017.09.292DOI: 10.1016/j.proeng.2017.09.292
Jiang, Y., Zhao, L., Beer, M., Patelli, E., Broggi, M., Luo, J., . . . Zhang, J. (2017). Multiple response surfaces method with advanced classification of samples for structural failure function fitting. STRUCTURAL SAFETY, 64, 87-97. doi:10.1016/j.strusafe.2016.10.002DOI: 10.1016/j.strusafe.2016.10.002
Numerically efficient reliability analysis of interdependent networks (Conference Paper)
Behrensdorf, J., Broggi, M., Brandt, S., & Beer, M. (2017). Numerically efficient reliability analysis of interdependent networks. In Safety and Reliability – Theory and Applications. CRC Press. doi:10.1201/9781315210469-298DOI: 10.1201/9781315210469-298
Revealing Prediction Uncertainty in Artificial Neural Network Based Reconstruction of Missing Data in Stochastic Process Records utilizing Extreme Learning Machines (Conference Paper)
Comerford, L., Beer, M., & Lu, N. (2017). Revealing Prediction Uncertainty in Artificial Neural Network Based Reconstruction of Missing Data in Stochastic Process Records utilizing Extreme Learning Machines. In 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) (pp. 871-877). Retrieved from https://www.webofscience.com/
SAMPLING SCHEMES FOR HISTORY MATCHING USING SUBSET SIMULATION (Conference Paper)
Gong, Z., Díaz De la O, F. A., & Beer, M. (2017). SAMPLING SCHEMES FOR HISTORY MATCHING USING SUBSET SIMULATION. In Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120217.5359.16948DOI: 10.7712/120217.5359.16948
Glisic, A., Schaumann, P., Broggi, M., & Beer, M. (2017). Sensitivity Analysis of Material and Load Parameters to Fatigue Stresses of an Offshore Wind Turbine Monopile Substructure. In X INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2017) Vol. 199 (pp. 1228-1233). doi:10.1016/j.proeng.2017.09.255DOI: 10.1016/j.proeng.2017.09.255
Sensitivity analysis for bayesian networks with interval probabilities (Conference Paper)
Tolo, S., Patelli, E., & Beer, M. (2017). Sensitivity analysis for bayesian networks with interval probabilities. In Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 (pp. 52).
Survival signature approach for the reliability analysis of an axial compressor (Conference Paper)
Miro, S., Broggi, M., Beer, M., Willeke, T., & Seume, J. (2017). Survival signature approach for the reliability analysis of an axial compressor. In Safety and Reliability – Theory and Applications. CRC Press. doi:10.1201/9781315210469-300DOI: 10.1201/9781315210469-300
2016
Duy, M. D., Gao, W., Song, C., & Beer, M. (2016). Interval spectral stochastic finite element analysis of structures with aggregation of random field and bounded parameters. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 108(10), 1198-1229. doi:10.1002/nme.5251DOI: 10.1002/nme.5251
Chen, N., Yu, D., Xia, B., & Beer, M. (2016). Uncertainty analysis of a structural-acoustic problem using imprecise probabilities based on p-box representations. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 80, 45-57. doi:10.1016/j.ymssp.2016.04.009DOI: 10.1016/j.ymssp.2016.04.009
Component importance measures for complex repairable system (Conference Paper)
Feng, G., Patelli, E., Beer, M., & Coolen, F. P. A. (2017). Component importance measures for complex repairable system. In RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE (pp. 1580-1585). Retrieved from https://www.webofscience.com/
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2017). Learning from accidents: Investigating the genesis of human errors in multi-attribute settings to improve the organisation of design. In RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE (pp. 228-236). Retrieved from https://www.webofscience.com/
Sensitivity analysis for Bayesian networks with interval probabilities (Conference Paper)
Tolo, S., Patelli, E., & Beer, M. (2017). Sensitivity analysis for Bayesian networks with interval probabilities. In RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE (pp. 306-312). Retrieved from https://www.webofscience.com/
Zhang, M. Q., Beer, M., Koh, C. G., & Jensen, H. A. (2016). Nuanced Robustness Analysis with Limited Information. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 2(3). doi:10.1061/AJRUA6.0000821DOI: 10.1061/AJRUA6.0000821
Nonlinear MDOF system Survival Probability Determination Subject to Evolutionary Stochastic Excitation (Journal article)
Mitseas, I. P., Kougioumtzoglou, I. A., Spanos, P. D., & Beer, M. (2016). Nonlinear MDOF system Survival Probability Determination Subject to Evolutionary Stochastic Excitation. STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING, 62(7-8), 440-451. doi:10.5545/sv-jme.2016.3752DOI: 10.5545/sv-jme.2016.3752
Feng, G., Patelli, E., Beer, M., & Coolen, F. P. A. (2016). Imprecise system reliability and component importance based on survival signature. RELIABILITY ENGINEERING & SYSTEM SAFETY, 150, 116-125. doi:10.1016/j.ress.2016.01.019DOI: 10.1016/j.ress.2016.01.019
Kougioumtzoglou, I. A., Zhang, Y., & Beer, M. (2016). Softening Duffing Oscillator Reliability Assessment Subject to Evolutionary Stochastic Excitation. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 2(2). doi:10.1061/AJRUA6.0000828DOI: 10.1061/AJRUA6.0000828
Feng, G., Patelli., & Beer. (2016). Reliability Analysis of Complex Systems with Uncertainties by Monte Carlo Simulation Method. In Tongji University Press (pp. 353-358). Shanghai, China.
An approximate stochastic dynamics approach for nonlinear structural system performance-based multi-objective optimum design (Journal article)
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2016). An approximate stochastic dynamics approach for nonlinear structural system performance-based multi-objective optimum design. STRUCTURAL SAFETY, 60, 67-76. doi:10.1016/j.strusafe.2016.01.003DOI: 10.1016/j.strusafe.2016.01.003
Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2016). Compressive sensing based stochastic process power spectrum estimation subject to missing data. In PROBABILISTIC ENGINEERING MECHANICS Vol. 44 (pp. 66-76). doi:10.1016/j.probengmech.2015.09.015DOI: 10.1016/j.probengmech.2015.09.015
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2016). Learning from major accidents to improve system design. Safety Science, 84, 37-45. doi:10.1016/j.ssci.2015.11.022DOI: 10.1016/j.ssci.2015.11.022
Why Modified exponential covariance kernel is empirically successful: A theoretical explanation (Journal article)
Kosheleva, O., & Beer, M. (2016). Why Modified exponential covariance kernel is empirically successful: A theoretical explanation. Journal of Uncertain Systems, 10(1), 10-14.
Approximate fuzzy analysis of linear structural systems applying intervening variables (Journal article)
Valdebenito, M. A., Perez, C. A., Jensen, H. A., & Beer, M. (2016). Approximate fuzzy analysis of linear structural systems applying intervening variables. COMPUTERS & STRUCTURES, 162, 116-129. doi:10.1016/j.compstruc.2015.08.020DOI: 10.1016/j.compstruc.2015.08.020
2015
Special Issue: Civil-Comp (Journal article)
Tsompanakis, Y., Ivanyi, P., Beck, A. T., Beer, M., Costa Neves, L. F., Girardi, M., . . . Topping, B. H. V. (2015). Special Issue: Civil-Comp. ADVANCES IN ENGINEERING SOFTWARE, 89, 1-2. doi:10.1016/j.advengsoft.2015.08.007DOI: 10.1016/j.advengsoft.2015.08.007
Compressive Sensing for power spectrum estimation of multi-dimensional processes under missing data (Conference Paper)
Zhang, Y., Comerford, L., Beer, M., & Kougioumtroglou, L. (2015). Compressive Sensing for power spectrum estimation of multi-dimensional processes under missing data. In 2015 INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP 2015) (pp. 162-165). Retrieved from https://www.webofscience.com/
Enhanced Bayesian Network approach to sea wave overtopping hazard quantification (Conference Paper)
Tolo, S., Patelli, E., & Beer, M. (2015). Enhanced Bayesian Network approach to sea wave overtopping hazard quantification. In Unknown Conference (pp. 1983-1990). CRC Press. doi:10.1201/b19094-258DOI: 10.1201/b19094-258
Human factors and quality control procedures: An example from the offshore oil & gas industry (Conference Paper)
Morais, C., Moura, R., Beer, M., & Lewi, J. (2015). Human factors and quality control procedures: An example from the offshore oil & gas industry. In Unknown Conference (pp. 3835-3841). CRC Press. doi:10.1201/b19094-502DOI: 10.1201/b19094-502
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2015). Learning from accidents: Analysis of multi-attribute events and implications to improve design and reduce human errors. In Unknown Conference (pp. 3049-3056). CRC Press. doi:10.1201/b19094-402DOI: 10.1201/b19094-402
Optimal risk regulatory policy in the development of a geological disposal facility (Conference Paper)
Nieto-Cerezo, O., Patelli, E., & Beer, M. (2015). Optimal risk regulatory policy in the development of a geological disposal facility. In Unknown Conference (pp. 2781-2788). CRC Press. doi:10.1201/b19094-364DOI: 10.1201/b19094-364
Reliability assessments and remaining life of pipelines subject to combined loadings using imprecise probabilities (Conference Paper)
Opeyemi, D., Patelli, E., Beer, M., & Timashev, S. (2015). Reliability assessments and remaining life of pipelines subject to combined loadings using imprecise probabilities. In Unknown Conference (pp. 2789-2796). CRC Press. doi:10.1201/b19094-365DOI: 10.1201/b19094-365
Robust design of inspection schedules by means of probability boxes for structural systems prone to damage accumulation (Conference Paper)
de Angelis, M., Patelli, E., & Beer, M. (2015). Robust design of inspection schedules by means of probability boxes for structural systems prone to damage accumulation. In Unknown Conference (pp. 2733-2741). CRC Press. doi:10.1201/b19094-358DOI: 10.1201/b19094-358
Survival signature-based sensitivity analysis of systems with epistemic uncertainties (Conference Paper)
Feng, G., Patelli, E., & Beer, M. (2015). Survival signature-based sensitivity analysis of systems with epistemic uncertainties. In Unknown Conference (pp. 1547-1552). CRC Press. doi:10.1201/b19094-202DOI: 10.1201/b19094-202
A nonlinear model of failure function for reliability analysis of RC frame columns with tension failure (Journal article)
Jiang, Y., Sun, G., He, Y., Beer, M., & Zhang, J. (2015). A nonlinear model of failure function for reliability analysis of RC frame columns with tension failure. ENGINEERING STRUCTURES, 98, 74-80. doi:10.1016/j.engstruct.2015.04.030DOI: 10.1016/j.engstruct.2015.04.030
Special Issue: Computational Stochastic Dynamics Prologue (Journal article)
Beer, M., Kougioumtzoglou, I. A., & Naess, A. (2014). Special Issue: Computational Stochastic Dynamics Prologue. PROBABILISTIC ENGINEERING MECHANICS, 38, 102. doi:10.1016/j.probengmech.2014.11.004DOI: 10.1016/j.probengmech.2014.11.004
Analysis of a major-accident dataset by Association Rule Mining to minimise unsafe interfaces (Conference Paper)
Doell, C., Held, P., Moura, R., Kruse, R., & Beer, M. (n.d.). Analysis of a major-accident dataset by Association Rule Mining to minimise unsafe interfaces. In The 13th International Probabilistic Workshop (IPW2015). Liverpool, UK.
Long-term performance assessment and design of offshore structures (Journal article)
Zhang, Y., Beer, M., & Quek, S. T. (2015). Long-term performance assessment and design of offshore structures. COMPUTERS & STRUCTURES, 154, 101-115. doi:10.1016/j.compstruc.2015.02.029DOI: 10.1016/j.compstruc.2015.02.029
A COMPUTATIONAL TOOL FOR BAYESIAN NETWORKS ENHANCED WITH RELIABILITY METHODS (Conference Paper)
Tolo, S., Patelli, E., Beer, M., & Kang, Z. (2015). A COMPUTATIONAL TOOL FOR BAYESIAN NETWORKS ENHANCED WITH RELIABILITY METHODS. In Proceedings of the 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2015). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120215.4316.546DOI: 10.7712/120215.4316.546
Moura, R., Beer, M., Doell, C., & Kruse, R. (2015). A Clustering Approach to a Major-Accident Data Set: Analysis of Key Interactions to Minimise Human Errors. In 2015 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI) (pp. 1838-1843). doi:10.1109/SSCI.2015.256DOI: 10.1109/SSCI.2015.256
de Angelis, M., Patelli, E., & Beer, M. (2015). Advanced Line Sampling for efficient robust reliability analysis. STRUCTURAL SAFETY, 52, 170-182. doi:10.1016/j.strusafe.2014.10.002DOI: 10.1016/j.strusafe.2014.10.002
An artificial neural network approach for stochastic process power spectrum estimation subject to missing data (Journal article)
Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2015). An artificial neural network approach for stochastic process power spectrum estimation subject to missing data. STRUCTURAL SAFETY, 52, 150-160. doi:10.1016/j.strusafe.2014.10.001DOI: 10.1016/j.strusafe.2014.10.001
Swan, L., Waring, S., Alison, L., & Beer, M. (2015). Communicating risk in major incidents: The public's perception. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Comparative studies on assessment of corrosion rates in pipelines as semi-probabilistic and fully stochastic values (Conference Paper)
Opeyemi, D. A., Patelli, E., Beer, M., & Timashev, S. A. (2015). Comparative studies on assessment of corrosion rates in pipelines as semi-probabilistic and fully stochastic values. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Editorial: Engineering analysis with vague and imprecise information (Journal article)
Beer, M., & Patelli, E. (2015). Editorial: Engineering analysis with vague and imprecise information. STRUCTURAL SAFETY, 52, 143. doi:10.1016/j.strusafe.2014.11.001DOI: 10.1016/j.strusafe.2014.11.001
Enhanced Bayesian Networks approach to risk assessment of spent fuel ponds (Conference Paper)
Tolo, S., Patelli, E., Beer, M., & Broggi, M. (2015). Enhanced Bayesian Networks approach to risk assessment of spent fuel ponds. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Moura, R., Beer, M., Lewis, J., & Patelli, E. (2015). Learning from accidents: Analysis and representation of human errors in multi-attribute events. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Limit State Imprecise Interval Analysis in Geotechnical Engineering (Conference Paper)
Marques, S. H., Beer, M., Gomes, A. T., & Henriques, A. A. (2015). Limit State Imprecise Interval Analysis in Geotechnical Engineering. In GEOTECHNICAL SAFETY AND RISK V (pp. 383-388). doi:10.3233/978-1-61499-580-7-383DOI: 10.3233/978-1-61499-580-7-383
Limit State Imprecise Probabilistic Analysis in Geotechnical Engineering (Conference Paper)
Marques, S. H., Beer, M., Gomes, A. T., & Henriques, A. A. (2015). Limit State Imprecise Probabilistic Analysis in Geotechnical Engineering. In GEOTECHNICAL SAFETY AND RISK V (pp. 269-274). doi:10.3233/978-1-61499-580-7-269DOI: 10.3233/978-1-61499-580-7-269
Nonlinear stochastic dynamic analysis for performance based multi-objective optimum design considering life cycle seismic loss estimation (Conference Paper)
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2015). Nonlinear stochastic dynamic analysis for performance based multi-objective optimum design considering life cycle seismic loss estimation. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Reliability analysis of systems based on survival signature (Conference Paper)
Feng, G., Patelli, E., & Beer, M. (2015). Reliability analysis of systems based on survival signature. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Structural system response and reliability analysis under incomplete earthquake records (Conference Paper)
Comerford, L., Jensen, H., Beer, M., Mayorga, C., Kougioumtzoglou, I., & Kusanovic, D. (2015). Structural system response and reliability analysis under incomplete earthquake records. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Uncertainty management of safety-critical systems: A solution to the back-propagation problem (Conference Paper)
De Angelis, M., Patelli, E., & Beer, M. (2015). Uncertainty management of safety-critical systems: A solution to the back-propagation problem. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
2014
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2015). Human error analysis: Review of past accidents and implications for improving robustness of system design. In SAFETY AND RELIABILITY: METHODOLOGY AND APPLICATIONS (pp. 1037-1046). Retrieved from https://www.webofscience.com/
Human error analysis: Review of past accidents and implications for improving robustness of system design (Chapter)
Human error analysis: Review of past accidents and implications for improving robustness of system design (2014). In Safety and Reliability: Methodology and Applications (pp. 1073-1082). CRC Press. doi:10.1201/b17399-150DOI: 10.1201/b17399-150
Mechanism design for risk allocation and benefit sharing in the development of a Geological Disposal Facility for nuclear radioactive waste (Conference Paper)
Nieto-Cerezo, O., Patelli, E., Wenzelburger, J., & Beer, M. (2015). Mechanism design for risk allocation and benefit sharing in the development of a Geological Disposal Facility for nuclear radioactive waste. In SAFETY AND RELIABILITY: METHODOLOGY AND APPLICATIONS (pp. 481-486). Retrieved from https://www.webofscience.com/
Mechanism design for risk allocation and benefit sharing in the development of a Geological Disposal Facility for nuclear radioactive waste (Chapter)
Mechanism design for risk allocation and benefit sharing in the development of a Geological Disposal Facility for nuclear radioactive waste (2014). In Safety and Reliability: Methodology and Applications (pp. 517-522). CRC Press. doi:10.1201/b17399-73DOI: 10.1201/b17399-73
Approximation Concepts for Fuzzy Structural Analysis (Conference Paper)
Valdebenito, M. A., Jensen, H. A., Beer, M., & Pérez, C. A. (2014). Approximation Concepts for Fuzzy Structural Analysis. In Vulnerability, Uncertainty, and Risk. American Society of Civil Engineers. doi:10.1061/9780784413609.014DOI: 10.1061/9780784413609.014
Bayesian Network Approach for Risk Assessment of a Spent Nuclear Fuel Pond (Chapter)
Tolo, S., Patelli, E., & Beer, M. (2014). Bayesian Network Approach for Risk Assessment of a Spent Nuclear Fuel Pond. American Society of Civil Engineers. doi:10.1061/9780784413609.061DOI: 10.1061/9780784413609.061
Line Sampling for Assessing Structural Reliability with Imprecise Failure Probabilities (Chapter)
de Angelis, M., Patelli, E., & Beer, M. (2014). Line Sampling for Assessing Structural Reliability with Imprecise Failure Probabilities. American Society of Civil Engineers. doi:10.1061/9780784413609.093DOI: 10.1061/9780784413609.093
OpenCossan: An Efficient Open Tool for Dealing with Epistemic and Aleatory Uncertainties (Chapter)
Patelli, E., Broggi, M., Angelis, M. D., & Beer, M. (2014). OpenCossan: An Efficient Open Tool for Dealing with Epistemic and Aleatory Uncertainties. American Society of Civil Engineers. doi:10.1061/9780784413609.258DOI: 10.1061/9780784413609.258
Robust Design Optimization of Structural Systems Under Evolutionary Stochastic Seismic Excitation (Chapter)
Mitseas, I. P., Kougioumtzoglou, I. A., Beer, M., Patelli, E., & Mottershead, J. E. (2014). Robust Design Optimization of Structural Systems Under Evolutionary Stochastic Seismic Excitation. American Society of Civil Engineers. doi:10.1061/9780784413609.022DOI: 10.1061/9780784413609.022
Towards Efficient Ways of Estimating Failure Probability of Mechanical Structures Under Interval Uncertainty (Conference Paper)
Beer, M., de Angelis, M., & Kreinovich, V. (2014). Towards Efficient Ways of Estimating Failure Probability of Mechanical Structures Under Interval Uncertainty. In Vulnerability, Uncertainty, and Risk. American Society of Civil Engineers. doi:10.1061/9780784413609.033DOI: 10.1061/9780784413609.033
Uncertainty Quantification in Power Spectrum Estimation of Stochastic Processes Subject to Missing Data (Conference Paper)
Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2014). Uncertainty Quantification in Power Spectrum Estimation of Stochastic Processes Subject to Missing Data. In Vulnerability, Uncertainty, and Risk. American Society of Civil Engineers. doi:10.1061/9780784413609.038DOI: 10.1061/9780784413609.038
Vulnerability, Uncertainty, and Risk (Conference Paper)
Vulnerability, Uncertainty, and Risk (2014). In Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM) and the Sixth International Symposium on Uncertainty, Modeling, and Analysis (ISUMA). American Society of Civil Engineers. doi:10.1061/9780784413609DOI: 10.1061/9780784413609
Compressive sensing based power spectrum estimation from incomplete records by utilizing an adaptive basis (Conference Paper)
Comerford, L. A., Beer, M., & Kougioumtzoglou, I. A. (2014). Compressive sensing based power spectrum estimation from incomplete records by utilizing an adaptive basis. In 2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR ENGINEERING SOLUTIONS (CIES) (pp. 117-124). Retrieved from https://www.webofscience.com/
An artificial neural network based approach for power spectrum estimation subject to limited and/or missing data (Conference Paper)
Comerford, L., Kougioumtzoglou, I., & Beer, M. (2014). An artificial neural network based approach for power spectrum estimation subject to limited and/or missing data. In Unknown Conference (pp. 1083-1090). CRC Press. doi:10.1201/b16387-159DOI: 10.1201/b16387-159
Long-term reliability assessment of offshore structures in complex environment (Conference Paper)
Zhang, Y., Quek, S., & Beer, M. (2014). Long-term reliability assessment of offshore structures in complex environment. In Unknown Conference (pp. 2209-2216). CRC Press. doi:10.1201/b16387-321DOI: 10.1201/b16387-321
A compressive sensing based approach for estimating stochastic process power spectra subject to missing data (Conference Paper)
Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2014). A compressive sensing based approach for estimating stochastic process power spectra subject to missing data. In EURODYN 2014: IX INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (pp. 2995-2999). Retrieved from https://www.webofscience.com/
A pilot-study investigating the assessment and allocation of risks in public-private partnership transportation projects in Vietnam (Conference Paper)
Nhat, M. N., Lewis, J., Beer, M., & Boussabaine, A. (2014). A pilot-study investigating the assessment and allocation of risks in public-private partnership transportation projects in Vietnam. In Proceedings 30th Annual Association of Researchers in Construction Management Conference, ARCOM 2014 (pp. 1419-1428).
An open approach to educational resource development, with a specific example from structural engineering (Conference Paper)
Comerford, L., DeAngelis, M., Mannis, A., Beer, M., & Kougioumtzoglou, I. (2014). An open approach to educational resource development, with a specific example from structural engineering. In SEFI Annual Conference 2014.
Modified linear estimation method for generating multi-dimensional multi-variate Gaussian field in modelling material properties (Journal article)
Liu, Y., Lee, F. -H., Quek, S. -T., & Beer, M. (2014). Modified linear estimation method for generating multi-dimensional multi-variate Gaussian field in modelling material properties. PROBABILISTIC ENGINEERING MECHANICS, 38, 42-53. doi:10.1016/j.probengmech.2014.09.001DOI: 10.1016/j.probengmech.2014.09.001
Optimal design of nonlinear structures under evolutionary stochastic earthquake excitations (Conference Paper)
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2014). Optimal design of nonlinear structures under evolutionary stochastic earthquake excitations. In OPT-i 2014 - 1st International Conference on Engineering and Applied Sciences Optimization, Proceedings (pp. 2213-2233).
2013
An efficient strategy for computing interval expectations of risk (Conference Paper)
De Angelis, M., Patelli, E., & Beer, M. (2013). An efficient strategy for computing interval expectations of risk. In Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures - Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 (pp. 2225-2232).
Comparing intervals and moments for the quantification of coarse information (Conference Paper)
Beer, M., & Kreinovich, V. (2013). Comparing intervals and moments for the quantification of coarse information. In Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures - Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 (pp. 375-381).
An artificial neural network based approach for power spectrum estimation and simulation of stochastic processes subject to missing data (Conference Paper)
Comerford, L. A., Kougioumtzoglou, I. A., & Beer, M. (2013). An artificial neural network based approach for power spectrum estimation and simulation of stochastic processes subject to missing data. In PROCEEDINGS OF THE 2013 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR ENGINEERING SOLUTIONS (CIES) (pp. 118-124). Retrieved from https://www.webofscience.com/
Bayesian approach for inconsistent information (Journal article)
Stein, M., Beer, M., & Kreinovich, V. (2013). Bayesian approach for inconsistent information. INFORMATION SCIENCES, 245, 96-111. doi:10.1016/j.ins.2013.02.024DOI: 10.1016/j.ins.2013.02.024
Interval or moments: which carry more information? (Journal article)
Beer, M., & Kreinovich, V. (2013). Interval or moments: which carry more information?. SOFT COMPUTING, 17(8), 1319-1327. doi:10.1007/s00500-013-1002-1DOI: 10.1007/s00500-013-1002-1
Verified stochastic methods Markov set-chains and dependency modeling of mean and standard deviation (Journal article)
Rebner, G., Beer, M., Auer, E., & Stein, M. (2013). Verified stochastic methods Markov set-chains and dependency modeling of mean and standard deviation. SOFT COMPUTING, 17(8), 1415-1423. doi:10.1007/s00500-013-1009-7DOI: 10.1007/s00500-013-1009-7
Imprecise probabilities in engineering analyses (Journal article)
Beer, M., Ferson, S., & Kreinovich, V. (2013). Imprecise probabilities in engineering analyses. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 37(1-2), 4-29. doi:10.1016/j.ymssp.2013.01.024DOI: 10.1016/j.ymssp.2013.01.024
Special issue of Mechanical Systems and Signal Processing "Imprecise probabilities-What can they add to engineering analyses?" Foreword (Journal article)
Beer, M., & Ferson, S. (2013). Special issue of Mechanical Systems and Signal Processing "Imprecise probabilities-What can they add to engineering analyses?" Foreword. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 37(1-2), 1-3. doi:10.1016/j.ymssp.2013.03.018DOI: 10.1016/j.ymssp.2013.03.018
Structural reliability analysis on the basis of small samples: An interval quasi-Monte Carlo method (Journal article)
Zhang, H., Dai, H., Beer, M., & Wang, W. (2013). Structural reliability analysis on the basis of small samples: An interval quasi-Monte Carlo method. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 37(1-2), 137-151. doi:10.1016/j.ymssp.2012.03.001DOI: 10.1016/j.ymssp.2012.03.001
Reliability analysis with scarce information: Comparing alternative approaches in a geotechnical engineering context (Journal article)
Beer, M., Zhang, Y., Quek, S. T., & Phoon, K. K. (2013). Reliability analysis with scarce information: Comparing alternative approaches in a geotechnical engineering context. STRUCTURAL SAFETY, 41, 1-10. doi:10.1016/j.strusafe.2012.10.003DOI: 10.1016/j.strusafe.2012.10.003
Computational Intelligence in Structural Analysis and Design (Conference Paper)
Beer, M. (2013). Computational Intelligence in Structural Analysis and Design. In PROCEEDINGS OF THE 2013 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR ENGINEERING SOLUTIONS (CIES) (pp. IV-V). Retrieved from https://www.webofscience.com/
Special issue "Uncertainty quantification in structural analysis and design: To commemorate Professor Gerhart I. Schueller for his life-time contribution in the area of computational stochastic mechanics" (Journal article)
Jensen, H. A., & Beer, M. (2013). Special issue "Uncertainty quantification in structural analysis and design: To commemorate Professor Gerhart I. Schueller for his life-time contribution in the area of computational stochastic mechanics". COMPUTERS & STRUCTURES, 126, 1-2. doi:10.1016/j.compstruc.2013.04.002DOI: 10.1016/j.compstruc.2013.04.002
2012
Interval Analysis for System Identification of Linear MDOF Structures in the Presence of Modeling Errors (Journal article)
Zhang, M. Q., Beer, M., & Koh, C. G. (2012). Interval Analysis for System Identification of Linear MDOF Structures in the Presence of Modeling Errors. JOURNAL OF ENGINEERING MECHANICS, 138(11), 1326-1338. doi:10.1061/(ASCE)EM.1943-7889.0000433DOI: 10.1061/(ASCE)EM.1943-7889.0000433
Fuzzy Probability Theory (Chapter)
Beer, M. (2012). Fuzzy Probability Theory. In Computational Complexity (pp. 1240-1252). Springer New York. doi:10.1007/978-1-4614-1800-9_76DOI: 10.1007/978-1-4614-1800-9_76
CUDA Accelerated Fault Tree Analysis with C-XSC (Conference Paper)
Rebner, G., & Beer, M. (2012). CUDA Accelerated Fault Tree Analysis with C-XSC. In Unknown Conference (pp. 539-549). Springer Berlin Heidelberg. doi:10.1007/978-3-642-33362-0_41DOI: 10.1007/978-3-642-33362-0_41
Life-cycle financial modelling of long term infrastructure projects "PPP-BOT projects" under uncertainty and risk (Conference Paper)
Attarzadeh, M., Chua, D. K. H., Zhu, L., & Beer, M. (2012). Life-cycle financial modelling of long term infrastructure projects "PPP-BOT projects" under uncertainty and risk. In Life-Cycle and Sustainability of Civil Infrastructure Systems - Proceedings of the 3rd International Symposium on Life-Cycle Civil Engineering, IALCCE 2012 (pp. 991-996).
Dealing with scarce information on engineering systems (Conference Paper)
de Angelis, M., Patelli, E., & Beer, M. (2012). Dealing with scarce information on engineering systems. In 6th EUROPEAN CONGRESS ON COMPUTATIONAL METHODS IN APPLIED SCIENCES AND ENGINEERING (ECCOMAS 2012) (pp. -).
Dealing with scarce information on engineering systems (Journal article)
Patelli, E. (2012). Dealing with scarce information on engineering systems. N/A, N/A, N/A.
Proceedings of the 5th Asian-Pacific Symposium on Structural Reliability and its Applications (APSSRA2012): Sustainable Civil Infrastructures - Hazards, Risk, Uncertainty (Conference Paper)
Phoon, K. K., Beer, M., Quek, S. T., & Pang, S. D. (Eds.) (2012). Proceedings of the 5th Asian-Pacific Symposium on Structural Reliability and its Applications (APSSRA2012): Sustainable Civil Infrastructures - Hazards, Risk, Uncertainty. In 5th Asian-Pacific Symposium on Structural Reliability and its Applications (APSSRA2012) (pp. 1-780). Singapore: Research Publishing Singapore.
Safety and robustness assessment of structures with generalized data uncertainty (Journal article)
Beer, M., Graf, W., & Kaliske, M. (2012). Safety and robustness assessment of structures with generalized data uncertainty. GACM Report, 7, 23-28.
Safety and robustness assessment of structures with generalized data uncertainty (Journal article)
Beer, M., Graf, W., & Kaliske, M. (2012). Safety and robustness assessment of structures with generalized data uncertainty. GACM Report, 7, 23-28.
2011
Bayesian quantification of inconsistent information (Conference Paper)
Stein, M., & Beer, M. (2011). Bayesian quantification of inconsistent information. In Applications of Statistics and Probability in Civil Engineering -Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering (pp. 463-470).
Structural Reliability Assessment with Fuzzy Probabilities (Conference Paper)
Beer, M., Zhang, M., Tong, Q. S., & Ferson, S. (2011). Structural Reliability Assessment with Fuzzy Probabilities. In ISIPTA '11 - PROCEEDINGS OF THE SEVENTH INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITY: THEORIES AND APPLICATIONS (pp. 61-70). Retrieved from https://www.webofscience.com/
Uncertainty analysis in geotechnical engineering-a comparative study of selected approaches (Conference Paper)
Beer, M., Zhang, Y., Quek, S. T., & Phoon, K. K. (2011). Uncertainty analysis in geotechnical engineering-a comparative study of selected approaches. In APPLICATIONS OF STATISTICS AND PROBABILITY IN CIVIL ENGINEERING (pp. 2768-2775). Retrieved from https://www.webofscience.com/
Introduction (Journal article)
Kruse, R., Beer, M., & Zadeh, L. A. (2011). Introduction. INTEGRATED COMPUTER-AIDED ENGINEERING, 18(3), 201-202. doi:10.3233/ICA-2011-0377DOI: 10.3233/ICA-2011-0377
Fuzzy Probability in Engineering Analyses (Conference Paper)
Beer, M., & Ferson, S. (2011). Fuzzy Probability in Engineering Analyses. In Vulnerability, Uncertainty, and Risk. American Society of Civil Engineers. doi:10.1061/41170(400)7DOI: 10.1061/41170(400)7
Risk Management of Asalouye Desalination Project (Conference Paper)
Attarzadeh, M., Chua, D. K. H., & Beer, M. (2011). Risk Management of Asalouye Desalination Project. In Vulnerability, Uncertainty, and Risk. American Society of Civil Engineers. doi:10.1061/41170(400)98DOI: 10.1061/41170(400)98
Risk Management of Long Term Infrastructure Projects "PPP-BOT Projects" by Using Uncertainty, Probabilistic and Stochastic Methods, and Models (Conference Paper)
Attarzadeh, M., Chua, D. K. H., & Beer, M. (2011). Risk Management of Long Term Infrastructure Projects "PPP-BOT Projects" by Using Uncertainty, Probabilistic and Stochastic Methods, and Models. In Vulnerability, Uncertainty, and Risk. American Society of Civil Engineers. doi:10.1061/41170(400)44DOI: 10.1061/41170(400)44
A new approach for robustness assessment of fixed offshore structures under imprecise marine corrosion (Conference Paper)
Zhang, M. Q., Beer, M., Koh, C. G., Hirokane, M., & IEEE. (2014). A new approach for robustness assessment of fixed offshore structures under imprecise marine corrosion. In 2014 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2014) (pp. 2919-2926). Retrieved from http://gateway.webofknowledge.com/
BAYESIAN UPDATE WITH FUZZY INFORMATION (Conference Paper)
Beer, M., & Stein, M. (2012). BAYESIAN UPDATE WITH FUZZY INFORMATION. In PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2011, VOL 9 (pp. 821-829). Retrieved from https://www.webofscience.com/
Identification of Representative Paths in Noisy Processes (Conference Paper)
Liebscher, M., Reuter, U., Beer, M., Mehmood, Z., & IEEE. (2014). Identification of Representative Paths in Noisy Processes. In 2014 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2014) (pp. 2907-2912). Retrieved from http://gateway.webofknowledge.com/
Identification of Representative Paths in Noisy Processes (Conference Paper)
Liebscher, M., Reuter, U., Beer, M., & Mehmood, Z. (2011). Identification of Representative Paths in Noisy Processes. In PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS, EURODYN 2011 (pp. 2907-2912). Retrieved from https://www.webofscience.com/
Statics (Book)
Ang, K. K., Beer, M., & Wang, C. M. (2011). Statics. Singapore: McGraw-Hill.
2010
A Summary on Fuzzy Probability Theory (Conference Paper)
Beer, M. (2010). A Summary on Fuzzy Probability Theory. In 2010 IEEE International Conference on Granular Computing. IEEE. doi:10.1109/grc.2010.78DOI: 10.1109/grc.2010.78
Comparison of uncertainty models in reliability analysis of offshore structures under marine corrosion (Journal article)
Zhang, M. Q., Beer, M., Quek, S. T., & Choo, Y. S. (2010). Comparison of uncertainty models in reliability analysis of offshore structures under marine corrosion. STRUCTURAL SAFETY, 32(6), 425-432. doi:10.1016/j.strusafe.2010.04.003DOI: 10.1016/j.strusafe.2010.04.003
Special Issue "Modeling and Analysis of Rare and Imprecise Information" Foreword (Journal article)
Beer, M., Kwang, P. K., & Tong, Q. S. (2010). Special Issue "Modeling and Analysis of Rare and Imprecise Information" Foreword. STRUCTURAL SAFETY, 32(6), 357. doi:10.1016/j.strusafe.2010.09.004DOI: 10.1016/j.strusafe.2010.09.004
Discrete-continuous variable structural optimization of systems under stochastic loading (Journal article)
Jensen, H. A., & Beer, M. (2010). Discrete-continuous variable structural optimization of systems under stochastic loading. STRUCTURAL SAFETY, 32(5), 293-304. doi:10.1016/j.strusafe.2010.03.007DOI: 10.1016/j.strusafe.2010.03.007
Detection of branching points in noisy processes (Journal article)
Beer, M., & Liebscher, M. (2010). Detection of branching points in noisy processes. COMPUTATIONAL MECHANICS, 45(4), 363-374. doi:10.1007/s00466-009-0458-4DOI: 10.1007/s00466-009-0458-4
4th International Workshop on Reliable Engineering Computing (REC2010), Robust Design - Coping with Hazards, Risk and Uncertainty (Conference Paper)
Beer, M., Muhanna, R. L., & Mullen, R. L. (Eds.) (2010). 4th International Workshop on Reliable Engineering Computing (REC2010), Robust Design - Coping with Hazards, Risk and Uncertainty. In International Workshop on Reliable Engineering Computing (REC2010) (pp. 808). Singapore: Research Publishing.
Detection of branching points in noisy processes (Journal article)
Beer, M., & Liebscher, M. (2010). Detection of branching points in noisy processes. Computational Mechanics, 45(4), 363-374. doi:10.1007/s00466-009-0458-4DOI: 10.1007/s00466-009-0458-4
2009
Uncertainty and robustness in structural design (Conference Paper)
Beer, M., & Liebscher, M. (2009). Uncertainty and robustness in structural design. In Proceedings of the 12th International Conference on Civil, Structural and Environmental Engineering Computing.
Lifetime prediction using accelerated test data and neural networks (Journal article)
Freitag, S., Beer, M., Graf, W., & Kaliske, M. (2009). Lifetime prediction using accelerated test data and neural networks. COMPUTERS & STRUCTURES, 87(19-20), 1187-1194. doi:10.1016/j.compstruc.2008.12.007DOI: 10.1016/j.compstruc.2008.12.007
A neural network approach for simulating stationary stochastic processes (Journal article)
Beer, M., & Spanos, P. D. (2009). A neural network approach for simulating stationary stochastic processes. STRUCTURAL ENGINEERING AND MECHANICS, 32(1), 71-94. doi:10.12989/sem.2009.32.1.071DOI: 10.12989/sem.2009.32.1.071
Engineering quantification of inconsistent information (Journal article)
Beer, M. (2009). Engineering quantification of inconsistent information. International Journal of Reliability and Safety, 3(1/2/3), 174. doi:10.1504/ijrs.2009.026840DOI: 10.1504/ijrs.2009.026840
Fuzzy Probability Theory (Chapter)
Beer, M. (2009). Fuzzy Probability Theory. In R. Meyers (Ed.), Encyclopedia of Complexity and Systems Science (Vol. 6, pp. 4047-4059). New York: Springer.
Non-traditional Prospects in the Simultaneous Treatment of Uncertainty and Imprecision (Chapter)
Beer, M. (2009). Non-traditional Prospects in the Simultaneous Treatment of Uncertainty and Imprecision. In B. H. V. Topping, & Y. Tsompanakis (Eds.), Soft Computing in Civil and Structural Engineering (Vol. 23, pp. 247-266). Stirlingshire: Saxe-Coburg Publications.
2008
Designing robust structures - A nonlinear simulation based approach (Journal article)
Beer, M., & Liebscher, M. (2008). Designing robust structures - A nonlinear simulation based approach. COMPUTERS & STRUCTURES, 86(10), 1102-1122. doi:10.1016/j.compstruc.2007.05.037DOI: 10.1016/j.compstruc.2007.05.037
Engineering computation under uncertainty -: Capabilities of non-traditional models (Journal article)
Moeller, B., & Beer, M. (2008). Engineering computation under uncertainty -: Capabilities of non-traditional models. COMPUTERS & STRUCTURES, 86(10), 1024-1041. doi:10.1016/j.compstruc.2007.05.041DOI: 10.1016/j.compstruc.2007.05.041
Special issue -: Uncertainty in structural analysis -: Their effect on robustness, sensitivity and design (Journal article)
Moeler, B., & Beer, M. (2008). Special issue -: Uncertainty in structural analysis -: Their effect on robustness, sensitivity and design. COMPUTERS & STRUCTURES, 86(10), 1023. doi:10.1016/j.compstruc.2007.10.001DOI: 10.1016/j.compstruc.2007.10.001
2007
Fuzzy structural analysis in view of numerical efficiency (Conference Paper)
Liebscher, M., Beer, M., Moeller, B., & Graf, W. (2007). Fuzzy structural analysis in view of numerical efficiency. In APPLICATIONS OF STATISICS AND PROBABILITY IN CIVIL ENGINEERING (pp. 249-250). Retrieved from https://www.webofscience.com/
Karhunen-loeve expansion of stochastic processes with a modified exponential covariance kernel (Journal article)
Spanos, P. D., Beer, M., & Red-Horse, J. (2007). Karhunen-loeve expansion of stochastic processes with a modified exponential covariance kernel. JOURNAL OF ENGINEERING MECHANICS, 133(7), 773-779. doi:10.1061/(ASCE)0733-9399(2007)133:7(773)DOI: 10.1061/(ASCE)0733-9399(2007)133:7(773)
Lifetime prediction with neural networks (Conference Paper)
Freitag, S., Beer, M., Graf, W., & Kaliske, M. (2007). Lifetime prediction with neural networks. In Civil-Comp Proceedings Vol. 87.
Model-free sampling (Journal article)
Beer, M. (2007). Model-free sampling. STRUCTURAL SAFETY, 29(1), 49-65. doi:10.1016/j.strusafe.2006.01.001DOI: 10.1016/j.strusafe.2006.01.001
2006
Time-dependent reliability of textile-strengthened RC structures under consideration of fuzzy randomness (Journal article)
Möller, B., Beer, M., Graf, W., & Sickert, J. U. (2006). Time-dependent reliability of textile-strengthened RC structures under consideration of fuzzy randomness. COMPUTERS & STRUCTURES, 84(8-9), 585-603. doi:10.1016/j.compstruc.2005.10.006DOI: 10.1016/j.compstruc.2005.10.006
Zum Einfluß der Datenbasis auf Tragwerkssicherheit und Versagensrisiko (Journal article)
Graf, W., Möller, B., & Beer, M. (2006). Zum Einfluß der Datenbasis auf Tragwerkssicherheit und Versagensrisiko. Wissenschaftliche Zeitschrift der Technischen Universität Dresden, 55(3-4), 49-53.
2004
Uncertain structural design based on nonlinear fuzzy analysis (Journal article)
Beer, M. (2004). Uncertain structural design based on nonlinear fuzzy analysis. ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK, 84(10-11), 740-753. doi:10.1002/zamm.200410154DOI: 10.1002/zamm.200410154
Discussion on "Structural reliability analysis through fuzzy number approach, with application to stability" (Journal article)
Möller, B., Graf, W., & Beer, M. (2004). Discussion on "Structural reliability analysis through fuzzy number approach, with application to stability". COMPUTERS & STRUCTURES, 82(2-3), 325-327. doi:10.1016/S0045-7949(03)00336-5DOI: 10.1016/S0045-7949(03)00336-5
Fuzzy Randomness (Book)
Möller, B., & Beer, M. (2004). Fuzzy Randomness. Springer Berlin Heidelberg. doi:10.1007/978-3-662-07358-2DOI: 10.1007/978-3-662-07358-2
2003
Safety assessment of structures in view of fuzzy randomness (Journal article)
Möller, B., Graf, W., & Beer, M. (2003). Safety assessment of structures in view of fuzzy randomness. COMPUTERS & STRUCTURES, 81(15), 1567-1582. doi:10.1016/S0045-7949(03)00147-0DOI: 10.1016/S0045-7949(03)00147-0
Fuzzy stochastic finite element method (Chapter)
Möller, B., Graf, W., Beer, M., & Sickert, J. U. (2003). Fuzzy stochastic finite element method. In Unknown Book (pp. 2074-2077). Retrieved from https://www.webofscience.com/
Fuzzy probabilistic structural analysis considering fuzzy random functions (Conference Paper)
Sickert, J. U., Beer, M., Graf, W., & Möller, B. (2003). Fuzzy probabilistic structural analysis considering fuzzy random functions. In APPLICATIONS OF STATISTICS AND PROBABILITY IN CIVIL ENGINEERING, VOLS 1 AND 2 (pp. 379-386). Retrieved from https://www.webofscience.com/
Processing uncertainty in structural analysis, design and safety assessment (Conference Paper)
Beer, M., Moller, B., & Liebscher, M. (2003). Processing uncertainty in structural analysis, design and safety assessment. In ISUMA 2003: FOURTH INTERNATIONAL SYMPOSIUM ON UNCERTAINTY MODELING AND ANALYSIS (pp. 34-39). doi:10.1109/ISUMA.2003.1236137DOI: 10.1109/ISUMA.2003.1236137
2001
Fuzzy finite element method and its application (Conference Paper)
Möller, B., Beer, M., Graf, W., & Sickert, J. U. (2001). Fuzzy finite element method and its application. In TRENDS IN COMPUTATIONAL STRUCTURAL MECHANICS (pp. 529-538). Retrieved from https://www.webofscience.com/
2000
Fuzzy structural analysis using α-level optimization (Journal article)
Möller, B., Graf, W., & Beer, M. (2000). Fuzzy structural analysis using α-level optimization. COMPUTATIONAL MECHANICS, 26(6), 547-565. doi:10.1007/s004660000204DOI: 10.1007/s004660000204
RC-folded plate structures with textile reinforcement (Conference Paper)
Möller, B., Beer, M., Graf, W., & Hoffmann, A. (2000). RC-folded plate structures with textile reinforcement. In European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2000.
Fuzzy-Tragwerksanalyse - Tragwerksanalyse mit unscharfen Parametern (Journal article)
Möller, B., Graf, W., & Beer, M. (2000). Fuzzy-Tragwerksanalyse - Tragwerksanalyse mit unscharfen Parametern. Bauingenieur, 75(11), 697-708.
Modellierung von Unschärfe im Ingenieurbau (Journal article)
Möller, B., Beer, M., Graf, W., Hoffmann, A., & Sickert, J. U. (2000). Modellierung von Unschärfe im Ingenieurbau. Bauinformatik Journal, 3, 21-25.
1999
Possibility Theory Based Safety Assessment (Journal article)
Moller, B., Beer, M., Graf, W., & Hoffmann, A. (1999). Possibility Theory Based Safety Assessment. Computer-Aided Civil and Infrastructure Engineering, 14(2), 81-91. doi:10.1111/0885-9507.00132DOI: 10.1111/0885-9507.00132
Ultimate limit loads of RC-folded plate structures with textile reinforcement (Conference Paper)
Möller, B., Graf, W., Hoffmann, A., & Beer, M. (1999). Ultimate limit loads of RC-folded plate structures with textile reinforcement. In COMPUTATIONAL METHODS AND EXPERIMENTAL MEASUREMENTS IX (pp. 453-462). Retrieved from https://www.webofscience.com/
1998
Safety assessment using fuzzy theory (Conference Paper)
Möller, B., & Beer, M. (1998). Safety assessment using fuzzy theory. In COMPUTING IN CIVIL ENGINEERING (pp. 756-759). Retrieved from https://www.webofscience.com/
1997
Uncertainty analysis in civil engineering using fuzzy modeling (Conference Paper)
Moeller, B., & Beer, M. (1997). Uncertainty analysis in civil engineering using fuzzy modeling. In PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON COMPUTING IN CIVIL AND BUILDING ENGINEERING, VOLS 1-4 (pp. 1425-1430). Retrieved from https://www.webofscience.com/
1995
New varioram intake system of the Porsche 911 engine (Journal article)
Beer, M., Kling, J., Pelters, S., Rutschmann, E., & Scheiba, J. (1995). New varioram intake system of the Porsche 911 engine. MTZ Motortechnische Zeitschrift, 56(9).
