2024
Sunny, J., de Angelis, M., & Edwards, B. (n.d.). Regionally adjusted stochastic earthquake ground motion models, associated variabilities and epistemic uncertainties. Journal of Seismology. doi:10.1007/s10950-024-10195-7DOI: 10.1007/s10950-024-10195-7
2023
Gray, N., de Angelis, M., & Ferson, S. (2023). Towards an automatic uncertainty compiler. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 160. doi:10.1016/j.ijar.2023.108951DOI: 10.1016/j.ijar.2023.108951
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
de Angelis, M., Gray, A., Ferson, S., & Patelli, E. (2023). Robust online updating of a digital twin with imprecise probability. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 186. doi:10.1016/j.ymssp.2022.109877DOI: 10.1016/j.ymssp.2022.109877
Bonney, M. S., de Angelis, M., Dal Borgo, M., & Wagg, D. J. (2023). Contextualisation of information in digital twin processes. Mechanical Systems and Signal Processing, 184, 109657. doi:10.1016/j.ymssp.2022.109657DOI: 10.1016/j.ymssp.2022.109657
Lye, A., Gray, A., de Angelis, M., & Ferson, S. (2023). ROBUST PROBABILITY BOUNDS ANALYSIS FOR FAILURE ANALYSIS UNDER LACK OF DATA AND MODEL UNCERTAINTY. 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:10.7712/120223.10345.19797DOI: 10.7712/120223.10345.19797
2022
Gray, A., de Angelis, M., Patelli, E., & Ferson, S. (2023). Bivariate dependency tracking in interval arithmetic. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 186. doi:10.1016/j.ymssp.2022.109771DOI: 10.1016/j.ymssp.2022.109771
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
Gray, N., Ferson, S., De Angelis, M., Gray, A., & de Oliveira, F. B. (2022). Probability bounds analysis for Python. Software Impacts, 100246. doi:10.1016/j.simpa.2022.100246DOI: 10.1016/j.simpa.2022.100246
Code for stochastic area metric (Software / Code)
De Angelis, M., & Sunny, J. (2022). Code for stochastic area metric (Version 0.3) [Computer Software]. doi:10.5281/ZENODO.6366288DOI: 10.5281/ZENODO.6366288
Sunny, J., De Angelis, M., & Edwards, B. (2022). Ranking and Selection of Earthquake Ground-Motion Models Using the Stochastic Area Metric. SEISMOLOGICAL RESEARCH LETTERS, 93(2A), 787-797. doi:10.1785/0220210216DOI: 10.1785/0220210216
intervals (Software / Code)
De Angelis, M. (2022). intervals (Version 0.1) [Computer Software]. doi:10.5281/zenodo.6205624DOI: 10.5281/zenodo.6205624
Gray, A., Wimbush, A., de Angelis, M., Hristov, P. O., Calleja, D., Miralles-Dolz, E., & Rocchetta, R. (2022). From inference to design: A comprehensive framework for uncertainty quantification in engineering with limited information. Mechanical Systems and Signal Processing, 165, 108210. doi:10.1016/j.ymssp.2021.108210DOI: 10.1016/j.ymssp.2021.108210
Bonney, M. S., de Angelis, M., Dal Borgo, M., Andrade, L., Beregi, S., Jamia, N., & Wagg, D. J. (2022). Development of a digital twin operational platform using Python Flask. DATA-CENTRIC ENGINEERING, 3. doi:10.1017/dce.2022.1DOI: 10.1017/dce.2022.1
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
Bounding Failure Probability with the SIVIA Algorithm (Conference Paper)
Angelis, M. D., & Gray, A. (2022). Bounding Failure Probability with the SIVIA 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_s14-07-334-cdDOI: 10.3850/978-981-18-5183-4_s14-07-334-cd
Development of a digital twin operational platform using Python Flask—ADDENDUM (Journal article)
Bonney, M. S., de Angelis, M., Dal Borgo, M., Andrade, L., Beregi, S., Jamia, N., & Wagg, D. J. (2022). Development of a digital twin operational platform using Python Flask—ADDENDUM. Data-Centric Engineering, 3. doi:10.1017/dce.2022.13DOI: 10.1017/dce.2022.13
Interval-Based Global Sensitivity Analysis for Epistemic Uncertainty (Conference Paper)
Miralles-Dolz, E., Gray, E., Angelis, M. D., & Patelli, E. (2022). Interval-Based Global Sensitivity Analysis for Epistemic Uncertainty. In Book of Extended Abstracts for the 32nd European Safety and Reliability Conference. Research Publishing Services. doi:10.3850/978-981-18-5183-4_s14-04-180-cdDOI: 10.3850/978-981-18-5183-4_s14-04-180-cd
2021
Ferson, S., & De Angelis, M. (2021). Computing with confidence. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 137, 67-68. doi:10.1016/j.ijar.2021.07.001DOI: 10.1016/j.ijar.2021.07.001
Line Sampling Simulation (Chapter)
Valdebenito, M. A., de Angelis, M., & Patelli, E. (2021). Line Sampling Simulation. In Reliability-Based Analysis and Design of Structures and Infrastructure (pp. 215-226). CRC Press. doi:10.1201/9781003194613-15DOI: 10.1201/9781003194613-15
Reliability-Based Analysis and Design of Structures and Infrastructure (Book)
Farsangi, E. N., Noori, M., Gardoni, P., Takewaki, I., Varum, H., & Bogdanovic, A. (n.d.). Reliability-Based Analysis and Design of Structures and Infrastructure. CRC Press. doi:10.1201/9781003194613DOI: 10.1201/9781003194613
De Angelis, M., Rocchetta, R., Gray, A., & Ferson, S. (2021). Constructing consonant beliefs from multivariate data with scenario theory. Poster session presented at the meeting of The International Symposium on Imprecise Probabilities: Theories and Applications.
De Angelis, M., Rocchetta, R., Gray, A., & Ferson, S. (2021). Constructing consonant beliefs from multivariate data with scenario theory. Virtually from Liverpool.
De Angelis, M., Rocchetta, R., Gray, A., & Ferson, S. (2021). Constructing Consonant Predictive Beliefs from Data with Scenario Theory. In Proceedings of Machine Learning Research Vol. 147 (pp. 362). Granada, Spain.
De Angelis, M., Behrendt, M., Comerford, L., Zhang, Y., & Michael, B. (2021, May 17). Forward interval propagation through the discrete Fourier transform. In 9th International workshop on reliable engineering computing (pp. 39-52). Taormina, Italy. Retrieved from http://ww2new.unime.it/REC2021/proceedings/REC2021_Proceedings.pdf
De Angelis, M. (2021). The interval (discrete) Fourier transform. Virtual Taormina, Italy..
Gray, A., De Angelis, M., Ferson, S., & Patelli, E. (2021, May 17). What’s Z−X, when Z = X+Y? Dependency tracking in interval arithmetic with bivariate sets. In 9th International Workshop on Reliable Engineering Computing (REC2021). Virtual (Taormina, Italy).
Gray, N., Calleja, D., Wimbush, A., Miralles-Dolz, E., Gray, A., De Angelis, M., . . . Ferson, S. (2021). Is no test better than a bad test: Impact of diagnostic uncertainty on the spread of COVID-19 (vol 15, e0240775, 2020). PLOS ONE, 16(2). doi:10.1371/journal.pone.0247129DOI: 10.1371/journal.pone.0247129
Gray, A., Hose, D., De Angelis, M., Hanss, M., & Ferson, S. (2021). Dependent Possibilistic Arithmetic Using Copulas. In PROCEEDINGS OF THE TWELVETH INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITY: THEORIES AND APPLICATIONS Vol. 147 (pp. 169-179). Retrieved from https://www.webofscience.com/
Digital Twin Operational Platform for Connectivity and Accessibility using Flask Python (Conference Paper)
Bonney, M. S., de Angelis, M., Wagg, D., & Dal Borgo, M. (2021). Digital Twin Operational Platform for Connectivity and Accessibility using Flask Python. In 24TH ACM/IEEE INTERNATIONAL CONFERENCE ON MODEL-DRIVEN ENGINEERING LANGUAGES AND SYSTEMS COMPANION (MODELS-C 2021) (pp. 239-243). doi:10.1109/MODELS-C53483.2021.00042DOI: 10.1109/MODELS-C53483.2021.00042
2020
Comment on: British Society for Rheumatology guideline on diagnosis and treatment of giant cell arteritis (Journal article)
Oparaji, B. U., Clearkin, L., Ferson, S., De Angelis, M., Ferrer-Fernandez, M., Calleja, D., . . . Derrer-Merk, E. (2020). Comment on: British Society for Rheumatology guideline on diagnosis and treatment of giant cell arteritis. RHEUMATOLOGY, 59(12), E159. doi:10.1093/rheumatology/keaa265DOI: 10.1093/rheumatology/keaa265
Lye, A., De Angelis, M., & Patelli, E. (2020). Bayesian Regression over Sparse Fatigue Crack Growth Data for Nuclear Piping. Poster session presented at the meeting of Modelling in Nuclear Science and Engineering Seminar 2020. Bangor University. Retrieved from http://dx.doi.org/10.13140/RG.2.2.12347.95528
Is "No test is better than a bad test"? Impact of diagnostic uncertainty in mass testing on the spread of Covid-19 (Journal article)
Gray, N., Calleja, D., Wimbush, A., Miralles-Dolz, E., Gray, A., De Angelis, M., . . . Ferson, S. (2020). Is "No test is better than a bad test"? Impact of diagnostic uncertainty in mass testing on the spread of Covid-19. PLoS One. doi:10.1371/journal.pone.0240775DOI: 10.1371/journal.pone.0240775
Gray, N., Calleja, D., Wimbush, A., Miralles-Dolz, E., Gray, A., De-Angelis, M., . . . Ferson, S. (2020). Is “no test is better than a bad test”? Impact of diagnostic uncertainty in mass testing on the spread of COVID-19. doi:10.1101/2020.04.16.20067884DOI: 10.1101/2020.04.16.20067884
Sadeghi, J., de Angelis, M., & Patelli, E. (2020). Analytic Probabilistic Safety Analysis under Severe Uncertainty. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 6(1). doi:10.1061/AJRUA6.0001028DOI: 10.1061/AJRUA6.0001028
A Problem in the Bayesian Analysis of Data without Gold Standards (Conference Paper)
Gray, N., Angelis, M. D., Calleja, D., & Ferson, S. (2019). A Problem in the Bayesian Analysis of Data without Gold Standards. In Proceedings of the 29th European Safety and Reliability Conference (ESREL). Research Publishing Services. doi:10.3850/978-981-11-2724-3_0458-cdDOI: 10.3850/978-981-11-2724-3_0458-cd
Gray, A., Wimbush, A., De Angelis, M., Hristov, P. O., Miralles-Dolz, E., Calleja, D., & Rocchetta, R. (2020). Bayesian Calibration and Probability Bounds Analysis Solution to the Nasa 2020 UQ Challenge on Optimization under 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_5520-cdDOI: 10.3850/978-981-14-8593-0_5520-cd
Resilience Assessment of Safety-Critical Systems with Credal Networks (Conference Paper)
Estrada-Lugo, H. D., Santhosh, T. V., Angelis, M. D., & Patelli, E. (2020). Resilience Assessment of Safety-Critical Systems with Credal Networks. 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_4192-cdDOI: 10.3850/978-981-14-8593-0_4192-cd
Robust propagation of probability boxes by interval predictor models (Conference Paper)
Sadeghi, J., de Angelis, M., & Patelli, E. (2020). Robust propagation of probability boxes by interval predictor models. In STRUCTURAL SAFETY Vol. 82. doi:10.1016/j.strusafe.2019.101889DOI: 10.1016/j.strusafe.2019.101889
2019
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
Estrada-Lugo, H. D., Tolo, S., de Angelis, M., & Patelli, E. (2019). Pseudo Credal Networks for Inference With Probability Intervals. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 5(4). doi:10.1115/1.4044239DOI: 10.1115/1.4044239
Sadeghi, J., de Angelis, M., & Patelli, E. (2019). Efficient training of interval Neural Networks for imprecise training data. NEURAL NETWORKS, 118, 338-351. doi:10.1016/j.neunet.2019.07.005DOI: 10.1016/j.neunet.2019.07.005
De Angelis, M., Estrada Lugo, H. D., Patelli, E., & Ferson, S. (2019). On the dimensionality of inference in credal nets with interval probabilities. Poster session presented at the meeting of ISIPTA 2019. Ghent.
Estrada-Lugo, H. D., De Angelis, M., & Patelli, E. (2019). Probabilistic risk assessment of fire occurrence in residential buildings: Application to the Grenfell tower. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
De Angelis, M., Ferson, S., Patelli, E., & Kreinovich, V. (2019). BLACK-BOX PROPAGATION OF FAILURE PROBABILITIES UNDER EPISTEMIC UNCERTAINTY. In Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120219.6373.18699DOI: 10.7712/120219.6373.18699
Gray, N., De Angelis, M., & Ferson, S. (2019). COMPUTING WITH UNCERTAINTY: INTRODUCING PUFFIN THE AUTOMATIC UNCERTAINTY COMPILER. In Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120219.6354.18702DOI: 10.7712/120219.6354.18702
Probabilistic risk assessment of fire occurrence in residential buildings: Application to the Grenfell tower (Conference Paper)
Estrada-Lugo, H. D., De Angelis, M., & Patelli, E. (2019). Probabilistic risk assessment of fire occurrence in residential buildings: Application to the Grenfell tower. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
2018
de-Angelis, M., Ricciardi, V., & Dalmau, E. (2018). Uncertainty estimation of road-dust emissions via interval statistics. In Journal of Physics: Conference Series Vol. 1065 (pp. 212023). IOP Publishing. doi:10.1088/1742-6596/1065/21/212023DOI: 10.1088/1742-6596/1065/21/212023
Sadeghi, J., de Angelis, M., & Patelli, E. (2018). Frequentist history matching with Interval Predictor Models. APPLIED MATHEMATICAL MODELLING, 61, 29-48. doi:10.1016/j.apm.2018.04.003DOI: 10.1016/j.apm.2018.04.003
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
Sadeghi, J., De Angelis, M., & Patelli, E. (2018, July 16). Efficient training of neural networks with interval uncertainty. In M. De Angelis (Ed.), http://rec2018.uk/papers/proceedings/proceedings.pdf (pp. 137-146). Liverpool.
An efficient computational strategy for robust maintenance scheduling: Application to corroded pipelines (Conference Paper)
Patelli, E., & de Angelis, M. (2018). An efficient computational strategy for robust maintenance scheduling: Application to corroded pipelines. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 2201-2209). Retrieved from https://www.webofscience.com/
Bayesian networks with imprecise datasets: Application to oscillating water column (Conference Paper)
Estrada-Lugo, H. D., Patelli, E., de Angelis, M., & Raj, D. D. (2018). Bayesian networks with imprecise datasets: Application to oscillating water column. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 2611-2618). Retrieved from https://www.webofscience.com/
Sadeghi, J. C., Patelli, E., De Angelis, M., & Prinja, N. K. (2018). EFFICIENT COMPUTATIONAL STRUCTURAL RELIABILITY ANALYSIS OF CONCRETE CONTAINMENTS. In 2nd International Conference on Nuclear Power Plants: Structures, Risk & Decommissioning. Croydon, UK.
Sadeghi, J. C., Patelli, E., & De Angelis, M. (2018). ANALYTIC IMPRECISE-PROBABILISTIC STRUCTURAL RELIABILITY ANALYSIS. In http://www.nineeng.com/bepu/images/Program%20Book%20and%20cover.pdf. Lucca, Italy. Retrieved from https://www.researchgate.net/
Altieri, D., Tubaldi, E., De Angelis, M., Patelli, E., & Dall'Asta, A. (2018). Reliability-based optimal design of nonlinear viscous dampers for the seismic protection of structural systems. BULLETIN OF EARTHQUAKE ENGINEERING, 16(2), 963-982. doi:10.1007/s10518-017-0233-4DOI: 10.1007/s10518-017-0233-4
Sadeghi, J., Fetz, T., Oberguggenberger, M., Patelli, E., & De Angelis, M. (2018). Probability Box Propagation: Benchmarking Challenge Problems. In 19th working conference of the IFIP Working Group 7.5 on Reliability and Optimization of Structural Systems. doi:10.3929/ethz-b-000335938DOI: 10.3929/ethz-b-000335938
2017
Ferrero, R., Wu, C., De Angelis, M., George-Williams, H., Patelli, E., Carboni, A., . . . IEEE. (2017). Low-Cost Battery Monitoring by Converter-Based Electrochemical Impedance Spectroscopy. In 2017 IEEE INTERNATIONAL WORKSHOP ON APPLIED MEASUREMENTS FOR POWER SYSTEMS (AMPS) (pp. 78-83). Retrieved from http://gateway.webofknowledge.com/
Hernandez, J. E., Kacprzyk, J., Panetto, H., Fernandez, A., Liu, S., Ortiz, A., & De-Angelis, M. (2017). Challenges and solutions for enhancing agriculture value chain decision-making. A short review. In IFIP Advances in Information and Communication Technology Vol. 506 (pp. 761-774). Springer. doi:10.1007/978-3-319-65151-4_68DOI: 10.1007/978-3-319-65151-4_68
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
2015
Line sampling approach for extreme case analysis in presence of aleatory and epistemic uncertainties (Conference Paper)
Patelli, E., & de Angelis, M. (2015). Line sampling approach for extreme case analysis in presence of aleatory and epistemic uncertainties. In Unknown Conference (pp. 2585-2593). CRC Press. doi:10.1201/b19094-339DOI: 10.1201/b19094-339
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
De Angelis, M. (2015, July 15). Efficient random set uncertainty quantification by means of advanced sampling techniques. (PhD Thesis, University of Liverpool).
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
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 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
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
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
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
Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures (Book)
Deodatis, G., Ellingwood, B. R., & Frangopol, D. M. (Eds.) (n.d.). Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures. CRC Press. doi:10.1201/b16387DOI: 10.1201/b16387
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
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.
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).
Interval solution and robust validation of uncertain elastic beams (Conference Paper)
Gabriele, S., Valente, C., & De Angelis, M. (2013). Interval solution and robust validation of uncertain elastic beams. 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. 445-452).
On Robust Maintenance Scheduling of Fatigue-prone Structural Systems Considering Imprecise Probability (Conference Paper)
Patelli, E., Valdebenito, M. A., & De Angelis, M. (2013). On Robust Maintenance Scheduling of Fatigue-prone Structural Systems Considering Imprecise Probability. In 2013 PROGNOSTICS AND HEALTH MANAGEMENT CONFERENCE (PHM) Vol. 33 (pp. 1081-1086). doi:10.3303/CET1333181DOI: 10.3303/CET1333181
2012
An open computational framework for reliability based optimization (Conference Paper)
Patelli, E., & De Angelis, M. (2012). An open computational framework for reliability based optimization. In Civil-Comp Proceedings Vol. 99.
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. -).
