Publications
2024
Regionally adjusted stochastic earthquake ground motion models, associated variabilities and epistemic uncertainties
Sunny, J., de Angelis, M., & Edwards, B. (2024). Regionally adjusted stochastic earthquake ground motion models, associated variabilities and epistemic uncertainties. Journal of Seismology, 28(2), 303-320. doi:10.1007/s10950-024-10195-7
Analysis of inspection records to evaluate the prevalence of ageing in the UK's industrial asset, base
Brown, C., Ferson, S., & Angelis, M. D. (2022). Analysis of inspection records to evaluate the prevalence of ageing in the UK's industrial asset, base. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 231-237). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-08-073-cd
Sharp Polynomial Upper Bound on the Variance
de Angelis, M. (2024). Sharp Polynomial Upper Bound on the Variance. In Advances in Intelligent Systems and Computing (pp. 76-84). Springer Nature Switzerland. doi:10.1007/978-3-031-65993-5_9
2023
Towards an automatic uncertainty compiler
Gray, N., de Angelis, M., & Ferson, S. (2023). Towards an automatic uncertainty compiler. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 160. doi:10.1016/j.ijar.2023.108951
Uncertainty Propagation of Missing Data Signals with the Interval Discrete Fourier Transform
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-1048
Regionally adjusted stochastic earthquake ground motion models, associated variabilities and epistemic uncertainties
Robust online updating of a digital twin with imprecise probability
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.2022.109877
Contextualisation of information in digital twin processes
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.2022.109657
ROBUST PROBABILITY BOUNDS ANALYSIS FOR FAILURE ANALYSIS UNDER LACK OF DATA AND MODEL UNCERTAINTY
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 Proceedings of the 5th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019) (pp. 391-407). Institute of Structural Analysis and Antiseismic Research National Technical University of Athens. doi:10.7712/120223.10345.19797
2022
Bivariate dependency tracking in interval arithmetic
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.2022.109771
Projecting interval uncertainty through the discrete Fourier transform: An application to time signals with poor precision
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.2022.108920
Probability bounds analysis for Python
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.2022.100246
Code for stochastic area metric
De Angelis, M., & Sunny, J. (2022). Code for stochastic area metric (Version 0.3) [Computer Software]. doi:10.5281/ZENODO.6366288
Ranking and Selection of Earthquake Ground-Motion Models Using the Stochastic Area Metric
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:10.1785/0220210216
intervals
De Angelis, M. (2022). intervals (Version 0.1) [Computer Software]. doi:10.5281/zenodo.6205624
From inference to design: A comprehensive framework for uncertainty quantification in engineering with limited information
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.2021.108210
Development of a digital twin operational platform using Python Flask
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.2022.1
Assessing the Severity of Missing Data Problems with the Interval Discrete Fourier Transform Algorithm
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 (pp. 2553-2560). Research Publishing Services. doi:10.3850/978-981-18-5183-4_s14-05-243-cd
Bounding Failure Probability with the SIVIA Algorithm
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 (pp. 2570-2577). Research Publishing Services. doi:10.3850/978-981-18-5183-4_s14-07-334-cd
Development of a digital twin operational platform using Python Flask—ADDENDUM
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.2022.13
Interval-Based Global Sensitivity Analysis for Epistemic Uncertainty
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 (pp. 2545-2552). Research Publishing Services. doi:10.3850/978-981-18-5183-4_s14-04-180-cd
2021
Computing with confidence
Ferson, S., & De Angelis, M. (2021). Computing with confidence. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 137, 67-68. doi:10.1016/j.ijar.2021.07.001
Line Sampling Simulation
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:10.1201/9781003194613-15
Reliability-Based Analysis and Design of Structures and Infrastructure
Farsangi, E. N., Noori, M., Gardoni, P., Takewaki, I., Varum, H., & Bogdanovic, A. (2021). Reliability-Based Analysis and Design of Structures and Infrastructure. CRC Press. doi:10.1201/9781003194613
Constructing consonant beliefs from multivariate data with scenario theory
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.
Constructing consonant beliefs from multivariate data with scenario theory
De Angelis, M., Rocchetta, R., Gray, A., & Ferson, S. (2021). Constructing consonant beliefs from multivariate data with scenario theory. Virtually from Liverpool.
Constructing Consonant Predictive Beliefs from Data with Scenario Theory
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.
Forward interval propagation through the discrete Fourier transform
De Angelis, M., Behrendt, M., Comerford, L., Zhang, Y., & Michael, B. (2021). 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
The interval (discrete) Fourier transform
De Angelis, M. (2021). The interval (discrete) Fourier transform. Virtual Taormina, Italy..
What’s Z−X, when Z = X+Y? Dependency tracking in interval arithmetic with bivariate sets
Gray, A., De Angelis, M., Ferson, S., & Patelli, E. (2021). 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).
Ranking and calibration of ground-motion models using the stochastic area metric
Sunny, J., De Angelis, M., & Edwards, B. (2021). Ranking and calibration of ground-motion models using the stochastic area metric. EGU General Assembly 2021. doi:10.5194/egusphere-egu21-11143
Is no test better than a bad test: Impact of diagnostic uncertainty on the spread of COVID-19 (vol 15, e0240775, 2020)
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.0247129
Constructing Consonant Predictive Beliefs from Data with Scenario Theory
DeAngelis, M., Rocchetta, R., Gray, A., & Ferson, S. (2021). Constructing Consonant Predictive Beliefs from Data with Scenario Theory. In PROCEEDINGS OF THE TWELVETH INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITY: THEORIES AND APPLICATIONS Vol. 147 (pp. 357-360). Retrieved from https://www.webofscience.com/
Dependent Possibilistic Arithmetic Using Copulas
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
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-C53483.2021.00042
2020
Interval propagation through the discrete Fourier transform
Comment on: British Society for Rheumatology guideline on diagnosis and treatment of giant cell arteritis
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/keaa265
Bayesian Regression over Sparse Fatigue Crack Growth Data for Nuclear Piping
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
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.0240775
Is "No test is better than a bad test"? Impact of diagnostic uncertainty in mass testing on the spread of Covid-19
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:10.1101/2020.04.16.20067884
Analytic Probabilistic Safety Analysis under Severe Uncertainty
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/AJRUA6.0001028
A Problem in the Bayesian Analysis of Data without Gold Standards
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) (pp. 2628-2634). Research Publishing Services. doi:10.3850/978-981-11-2724-3_0458-cd
Bayesian Calibration and Probability Bounds Analysis Solution to the Nasa 2020 UQ Challenge on Optimization under Uncertainty
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 (pp. 1111-1118). Research Publishing Services. doi:10.3850/978-981-14-8593-0_5520-cd
Resilience Assessment of Safety-Critical Systems with Credal Networks
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 (pp. 1199-1206). Research Publishing Services. doi:10.3850/978-981-14-8593-0_4192-cd
Robust propagation of probability boxes by interval predictor models
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.2019.101889
2019
On the Robust Estimation of Small Failure Probabilities for Strong Nonlinear Models
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:10.1115/1.4044044
Pseudo Credal Networks for Inference With Probability Intervals
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:10.1115/1.4044239
Efficient training of interval Neural Networks for imprecise training data
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.2019.07.005
On the dimensionality of inference in credal nets with interval probabilities
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.
Probabilistic risk assessment of fire occurrence in residential buildings: Application to the Grenfell Tower
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.
BLACK-BOX PROPAGATION OF FAILURE PROBABILITIES UNDER EPISTEMIC UNCERTAINTY
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) (pp. 713-723). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120219.6373.18699
COMPUTING WITH UNCERTAINTY: INTRODUCING PUFFIN THE AUTOMATIC UNCERTAINTY COMPILER
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) (pp. 487-497). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120219.6354.18702
Probabilistic risk assessment of fire occurrence in residential buildings: Application to the Grenfell tower
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
Uncertainty estimation of road-dust emissions via interval statistics
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:10.1088/1742-6596/1065/21/212023
Frequentist history matching with Interval Predictor Models
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.2018.04.003
Utilising database-driven interactive software to enhance independent home-study in a flipped classroom setting: going beyond visualising engineering concepts to ensuring formative assessment
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:10.1080/03043797.2017.1293617
Efficient training of neural networks with interval uncertainty
Sadeghi, J., De Angelis, M., & Patelli, E. (2018). 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
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
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/
EFFICIENT COMPUTATIONAL STRUCTURAL RELIABILITY ANALYSIS OF CONCRETE CONTAINMENTS
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.
ANALYTIC IMPRECISE-PROBABILISTIC STRUCTURAL RELIABILITY ANALYSIS
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/
Reliability-based optimal design of nonlinear viscous dampers for the seismic protection of structural systems
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/s10518-017-0233-4
Probability Box Propagation: Benchmarking Challenge Problems
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-000335938
2017
Low-Cost Battery Monitoring by Converter-Based Electrochemical Impedance Spectroscopy
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/
Challenges and solutions for enhancing agriculture value chain decision-making. A short review
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_68
Forced Monte Carlo Simulation Strategy for the Design of Maintenance Plans with Multiple Inspections
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/AJRUA6.0000868
2015
Line sampling approach for extreme case analysis in presence of aleatory and epistemic uncertainties
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/b19094-339
Robust design of inspection schedules by means of probability boxes for structural systems prone to damage accumulation
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/b19094-358
Efficient random set uncertainty quantification by means of advanced sampling techniques
De Angelis, M. (2015, July 15). Efficient random set uncertainty quantification by means of advanced sampling techniques. (PhD Thesis, University of Liverpool).
Advanced Line Sampling for efficient robust reliability analysis
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.2014.10.002
Uncertainty management in multidisciplinary design of critical safety systems
Patelli, E., Alvarez, D. A., Broggi, M., & de Angelis, M. (2015). Uncertainty management in multidisciplinary design of critical safety systems. Journal of Aerospace Information Systems, 12(1), 140-169. doi:10.2514/1.I010273
Uncertainty management of safety-critical systems: A solution to the back-propagation problem
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
de Angelis, M., Patelli, E., & Beer, M. (2014). Line Sampling for Assessing Structural Reliability with Imprecise Failure Probabilities. In Unknown Book (pp. 915-924). American Society of Civil Engineers. doi:10.1061/9780784413609.093
OpenCossan: An Efficient Open Tool for Dealing with Epistemic and Aleatory Uncertainties
Patelli, E., Broggi, M., Angelis, M. D., & Beer, M. (2014). OpenCossan: An Efficient Open Tool for Dealing with Epistemic and Aleatory Uncertainties. In Unknown Book (pp. 2564-2573). American Society of Civil Engineers. doi:10.1061/9780784413609.258
Reliability-Based Design of Fluid Viscous Damper for Seismic Protection of Building Frames
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. In Unknown Book (pp. 1767-1776). American Society of Civil Engineers. doi:10.1061/9780784413609.177
Towards Efficient Ways of Estimating Failure Probability of Mechanical Structures Under Interval Uncertainty
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 (pp. 320-329). American Society of Civil Engineers. doi:10.1061/9780784413609.033
Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures
Deodatis, G., Ellingwood, B. R., & Frangopol, D. M. (2014). Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures. CRC Press. doi:10.1201/b16387
An integrated and efficient numerical framework for uncertainty quantification: application to the NASA Langley multidisciplinary Uncertainty Quantification Challenge
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:10.2514/6.2014-1501
An open approach to educational resource development, with a specific example from structural engineering
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
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
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
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/CET1333181
2012
An open computational framework for reliability based optimization
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
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