2022
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
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
2021
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
Behrensdorf, J., Regenhardt, T. -E., Broggi, M., & Beer, M. (2021). Numerically efficient computation of the survival signature for the reliability analysis of large networks. RELIABILITY ENGINEERING & SYSTEM SAFETY, 216. doi:10.1016/j.ress.2021.107935DOI: 10.1016/j.ress.2021.107935
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
Kitahara, M., Bi, S., Broggi, M., & Beer, M. (2021). Bayesian Model Updating in Time Domain with Metamodel-Based Reliability Method. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 7(3). doi:10.1061/AJRUA6.0001149DOI: 10.1061/AJRUA6.0001149
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
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
2020
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
Mi, J., Beer, M., Li, Y. -F., Broggi, M., & Cheng, Y. (2020). Reliability and importance analysis of uncertain system with common cause failures based on survival signature. RELIABILITY ENGINEERING & SYSTEM SAFETY, 201. doi:10.1016/j.ress.2020.106988DOI: 10.1016/j.ress.2020.106988
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
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
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
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 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
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
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
2019
Song, J., Wei, P., Valdebenito, M., Bi, S., Broggi, M., Beer, M., & Lei, Z. (2019). Generalization of non-intrusive imprecise stochastic simulation for mixed uncertain variables. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 134. doi:10.1016/j.ymssp.2019.106316DOI: 10.1016/j.ymssp.2019.106316
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
Behrensdorf, J., Broggi, M., & Beer, M. (2019). Reliability Analysis of Networks Interconnected With Copulas. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 5(4). doi:10.1115/1.4044043DOI: 10.1115/1.4044043
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/
Miro, S., Willeke, T., Broggi, M., Seume, J. R., & Beer, M. (2019). Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 5(3). doi:10.1115/1.4043150DOI: 10.1115/1.4043150
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
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
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
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
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.
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.
2018
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/
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/
On-line Bayesian model updating for structural health monitoring (Journal article)
Rocchetta, R., Broggi, M., Huchet, Q., & Patelli, E. (2018). On-line Bayesian model updating for structural health monitoring. Mechanical Systems and Signal Processing, 103, 174-195. doi:10.1016/j.ymssp.2017.10.015DOI: 10.1016/j.ymssp.2017.10.015
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
Rocchetta, R., Broggi, M., & Patelli, E. (2018). Do we have enough data? Robust reliability via uncertainty quantification. APPLIED MATHEMATICAL MODELLING, 54, 710-721. doi:10.1016/j.apm.2017.10.020DOI: 10.1016/j.apm.2017.10.020
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/
2017
Sensitivity or Bayesian model updating: a comparison of techniques using the DLR AIRMOD test data (Journal article)
Patelli, E., Govers, Y., Broggi, M., Gomes, H. M., Link, M., & Mottershead, J. E. (2017). Sensitivity or Bayesian model updating: a comparison of techniques using the DLR AIRMOD test data. ARCHIVE OF APPLIED MECHANICS, 87(5), 905-925. doi:10.1007/s00419-017-1233-1DOI: 10.1007/s00419-017-1233-1
Patelli, E., Broggi, M., Tolo, S., & Sadeghi, J. (2017). COSSAN SOFTWARE: A MULTIDISCIPLINARY AND COLLABORATIVE SOFTWARE FOR UNCERTAINTY QUANTIFICATION. 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:10.7712/120217.5364.16982DOI: 10.7712/120217.5364.16982
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/
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
Reliability-Based Methodology for the Optimal Design of Viscous Dampers (Conference Paper)
Altieri, D., Tubaldi, E., Broggi, M., & Patelli, E. (2017). Reliability-Based Methodology for the Optimal Design of Viscous Dampers. In Unknown Conference (pp. 427-439). Springer International Publishing. doi:10.1007/978-3-319-47886-9_29DOI: 10.1007/978-3-319-47886-9_29
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
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
Venturini, T., Trefolini, E., Patelli, E., Broggi, M., Tuliani, G., & Disperati, L. (2016). Mapping slope deposits depth by means of cluster analysis: a comparative assessment. RENDICONTI ONLINE SOCIETA GEOLOGICA ITALIANA, 39, 47-50. doi:10.3301/ROL.2016.44DOI: 10.3301/ROL.2016.44
Rocchetta, R., Patelli, E., & Broggi, M. (2016). Bayesian Model Updating for Damage Identification. Poster session presented at the meeting of Unknown Conference.
Use of massively parallel computing to improve modelling accuracy within the nuclear sector (Journal article)
Evans, L. M., Arregui-Mena, J. D., Mummery, P. M., Akers, R. J., Surrey, E., Shterenlikht, A., . . . Margetts, L. (2016). Use of massively parallel computing to improve modelling accuracy within the nuclear sector. International Journal of Multiphysics, 10(2), 215-236.
2015
On Bayesian approaches for real-time crack detection (Conference Paper)
Rocchetta, R., Broggi, M., Patelli, E., & Huchet, Q. (2015). On Bayesian approaches for real-time crack detection. In Unknown Conference (pp. 1929-1936). CRC Press. doi:10.1201/b19094-251DOI: 10.1201/b19094-251
Perspectives on model updating (Presentation material)
Mottershead, J., Broggi, M., Gomes, H. M., Govers, Y., Haddad Khodaparast, H., Link, M., . . . Silva, T. A. N. (2015). Perspectives on model updating. Lagos, Portugal.
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.
Patelli, E., Alvarez, D. A., Broggi, M., & de Angelis, M. (n.d.). Uncertainty management in multidisciplinary design of critical safety systems. Journal of Aerospace Information Systems, 12(1), 140-169. doi:10.2514/1.I010273DOI: 10.2514/1.I010273
Uncertainty on shallow landslide hazard assessment: from field data to hazard mapping (Conference Paper)
Trefolini, E., Tolo, S., Patelli, E., Broggi, M., Disperati, L., & Le Tuan, H. (2015). Uncertainty on shallow landslide hazard assessment: from field data to hazard mapping. In Copernicus Meetings - Geophysical Research Abstracts,Vol. 17, EGU2015-PREVIEW, 2015.
2014
Computation of the Sobol' Indices using Importance Sampling (Chapter)
Beaurepaire, P., Broggi, M., & Patelli, E. (2014). Computation of the Sobol' Indices using Importance Sampling. American Society of Civil Engineers. doi:10.1061/9780784413609.212DOI: 10.1061/9780784413609.212
Model Updating by Uncertain Parameter Inference (Conference Paper)
Gomes, H. M., Broggi, M., Patelli, E., & Mottershead, J. E. (2014). Model Updating by Uncertain Parameter Inference. In Vulnerability, Uncertainty, and Risk. American Society of Civil Engineers. doi:10.1061/9780784413609.153DOI: 10.1061/9780784413609.153
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
Reliability-Based Design of Fluid Viscous Damper for Seismic Protection of Building Frames (Chapter)
Tubaldi, E., Dall'Asta, A., Broggi, M., Patelli, E., & De Angelis, M. (2014). Reliability-Based Design of Fluid Viscous Damper for Seismic Protection of Building Frames. American Society of Civil Engineers. doi:10.1061/9780784413609.177DOI: 10.1061/9780784413609.177
An integrated and efficient numerical framework for uncertainty quantification: application to the NASA Langley multidisciplinary Uncertainty Quantification Challenge (Conference Paper)
Patelli, E., Alvarez, D. A., Broggi, M., & de Angelis, M. (2014). An integrated and efficient numerical framework for uncertainty quantification: application to the NASA Langley multidisciplinary Uncertainty Quantification Challenge. In 16th AIAA Non-Deterministic Approaches Conference. American Institute of Aeronautics and Astronautics. doi:10.2514/6.2014-1501DOI: 10.2514/6.2014-1501
2013
A BAYESIAN MODEL UPDATING PROCEDURE FOR DYNAMIC HEALTH MONITORING (Conference Paper)
Patelli, E., Broggi, M., & Beaurepaire, P. (2014). A BAYESIAN MODEL UPDATING PROCEDURE FOR DYNAMIC HEALTH MONITORING. In Proceedings of the 4th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2013). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120113.4595.c1557DOI: 10.7712/120113.4595.c1557
A BAYESIAN MODEL UPDATING PROCEDURE FOR DYNAMIC HEALTH MONITORING (Conference Paper)
Patelli, E., Broggi, M., & Beaurepaire, P. (2013). A BAYESIAN MODEL UPDATING PROCEDURE FOR DYNAMIC HEALTH MONITORING. In 4th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2013) Kos Island, Greece, June 12 - June 14, 2013. (pp. -).
A Bayesian Framework for Crack Detection in Structural Components Under Dynamic Excitation (Conference Paper)
Broggi, M., Beaurepaire, P., & Patelli, E. (2013). A Bayesian Framework for Crack Detection in Structural Components Under Dynamic Excitation. In 2013 PROGNOSTICS AND HEALTH MANAGEMENT CONFERENCE (PHM) Vol. 33 (pp. 127-132). doi:10.3303/CET1333022DOI: 10.3303/CET1333022
Efficient Model Updating of the GOCE Satellite Based on Experimental Modal Data (Chapter)
Goller, B., Broggi, M., Calvi, A., & Schuëller, G. I. (2013). Efficient Model Updating of the GOCE Satellite Based on Experimental Modal Data. In Computational Methods in Stochastic Dynamics (pp. 215-235). Springer Netherlands. doi:10.1007/978-94-007-5134-7_13DOI: 10.1007/978-94-007-5134-7_13
On general purpose software for the efficient uncertainty management of large Finite Element models (Conference Paper)
Patelli, E., & Broggi, M. (2013). On general purpose software for the efficient uncertainty management of large Finite Element models. In NAFEMS World Congress 2013 9-12 June 2013, Salzburg, Austria. -: NAFEMS.
2012
General purpose software for efficient uncertainty management of large finite element models (Journal article)
Patelli, E., Panayirci, H. M., Broggi, M., Goller, B., Beaurepaire, P., Pradlwarter, H. J., & Schueller, G. I. (2012). General purpose software for efficient uncertainty management of large finite element models. FINITE ELEMENTS IN ANALYSIS AND DESIGN, 51, 31-48. doi:10.1016/j.finel.2011.11.003DOI: 10.1016/j.finel.2011.11.003
Efficient Modelling of thickness imperfections in carbon fiber reinforced plastic (Conference Paper)
Broggi, M., & Schueller, G. I. (2012). Efficient Modelling of thickness imperfections in carbon fiber reinforced plastic. In IASS-IACM 2012 (pp. 323-326). Sarajevo.
Failure and reliability predictions by infinite impulse response locally recurrent neural networks (Conference Paper)
Zio, E., Broggi, M., Golea, L. R., & Pedroni, N. (2012). Failure and reliability predictions by infinite impulse response locally recurrent neural networks. In Chemical Engineering Transactions Vol. 26 (pp. 117-122). doi:10.3303/CET1226020DOI: 10.3303/CET1226020
OpenCossan: General purpose software for uncertainty quantification and management (Software / Code)
Patelli, E., & Broggi, M. (2012). OpenCossan: General purpose software for uncertainty quantification and management [Internet (free access)]. Liverpool.
2011
Efficient model updating of the GOCE satellite based on experimental modal data (Conference Paper)
Goller, B., Broggi, M., Calvi, A., & Schuëller, G. I. (2011). Efficient model updating of the GOCE satellite based on experimental modal data. In ECCOMAS Thematic Conference - COMPDYN 2011: 3rd International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering: An IACM Special Interest Conference, Programme.
A stochastic model updating technique for complex aerospace structures (Journal article)
Goller, B., Broggi, M., Calvi, A., & Schuëller, G. I. (2011). A stochastic model updating technique for complex aerospace structures. Finite Elements in Analysis and Design, 47(7), 739-752. doi:10.1016/j.finel.2011.02.005DOI: 10.1016/j.finel.2011.02.005
Efficient modeling of imperfections for buckling analysis of composite cylindrical shells (Journal article)
Broggi, M., & Schuëller, G. I. (2011). Efficient modeling of imperfections for buckling analysis of composite cylindrical shells. Engineering Structures, 33(5), 1796-1806. doi:10.1016/j.engstruct.2011.02.019DOI: 10.1016/j.engstruct.2011.02.019
RELIABILITY ASSESSMENT OF AXIALLY COMPRESSED COMPOSITE CYLINDRICAL SHELLS WITH RANDOM IMPERFECTIONS (Journal article)
BROGGI, M., CALVI, A., & SCHUËLLER, G. I. (2011). RELIABILITY ASSESSMENT OF AXIALLY COMPRESSED COMPOSITE CYLINDRICAL SHELLS WITH RANDOM IMPERFECTIONS. International Journal of Structural Stability and Dynamics, 11(02), 215-236. doi:10.1142/s0219455411004063DOI: 10.1142/s0219455411004063
Reliability assessment of axially compressed composite cylindrical shells with random imperfections (Conference Paper)
Broggi, M., Calvi, A., & Schuëller, G. I. (2011). Reliability assessment of axially compressed composite cylindrical shells with random imperfections. In International Journal of Structural Stability and Dynamics Vol. 11 (pp. 215-236). doi:10.1142/S0219455411004063DOI: 10.1142/S0219455411004063
2009
MODELLING THE DYNAMICS OF THE LEAD BISMUTH EUTECTIC EXPERIMENTAL ACCELERATOR DRIVEN SYSTEM BY AN INFINITE IMPULSE RESPONSE LOCALLY RECURRENT NEURAL NETWORK (Journal article)
Zio, E., Pedroni, N., Broggi, M., & Golea, L. R. (2009). MODELLING THE DYNAMICS OF THE LEAD BISMUTH EUTECTIC EXPERIMENTAL ACCELERATOR DRIVEN SYSTEM BY AN INFINITE IMPULSE RESPONSE LOCALLY RECURRENT NEURAL NETWORK. Nuclear Engineering and Technology, 41(10), 1293-1306. doi:10.5516/net.2009.41.10.1293DOI: 10.5516/net.2009.41.10.1293
Nuclear reactor dynamics on-line estimation by Locally Recurrent Neural Networks (Journal article)
Zio, E., Broggi, M., & Pedroni, N. (2009). Nuclear reactor dynamics on-line estimation by Locally Recurrent Neural Networks. Progress in Nuclear Energy, 51(3), 573-581. doi:10.1016/j.pnucene.2008.11.006DOI: 10.1016/j.pnucene.2008.11.006
2008
LOCALLY RECURRENT NEURAL NETWORKS FOR NUCLEAR DYNAMICS MODELING (Conference Paper)
ZIO, E., PEDRONI, N., BROGGI, M., & GOLEA, L. (2008). LOCALLY RECURRENT NEURAL NETWORKS FOR NUCLEAR DYNAMICS MODELING. In Computational Intelligence in Decision and Control. WORLD SCIENTIFIC. doi:10.1142/9789812799470_0060DOI: 10.1142/9789812799470_0060
