Publications of Dr. techn. Matteo Broggi

Salomon, J., Broggi, M., & Beer, M. (2024): Resilience-based decision criteria for optimal regeneration.,  J. R. Seume, B. Denkena, & P. Gilge, Regeneration of Complex Capital Goods. Springer International Publishing.
ISBN: 978-3-031-51394-7

Behrensdorf, J.; Broggi, M.; Beer, M. (2018): Efficient Reliability and Risk Analysis of Complex Interconnected Systems,  In: Beer, M.; Huang, H.W.; Ayyub, B.M.; Zhang, D.M.; Phillips, B.M. (eds.), Resilience Engineering for Urban Tunnels, American Society of Civil Engineers, Infrastructure Resilience Publications (IRP) IRP 2, 43–54.
DOI: 10.1061/9780784415139.ch04

Feng, C.X.; Broggi, M.; Hu, Y.; Faes, M.G.R.; Beer, M. (2025): Interval Fields for Geotechnical Engineering Uncertainty Analysis under Limited Data,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, in press

Behrensdorf, J.; Broggi, M.; Beer, M. (2024): Interval Predictor Model for the Survival Signature using Monotone Radial Basis Functions,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, in press.

Bittner, M.; Broggi, M.; Beer, M (2024): Efficient reliability analysis of stochastic dynamic first-passage problems by probability density evolution analysis with subset supported point selection,  Engineering Structures, 312, Article 118210

Bittner, M.; Fritsch, L.; Hirzinger, B.; Broggi, M.; Beer, M. (2024): Efficient time-dependent reliability analysis for a railway bridge model,  XII. International Conference on Structural Dynamics, Journal of Physics: Conference Series 2647, Article 062002
DOI: 10.1088/1742-6596/2647/6/062002

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), Article 04024017
DOI: 10.1061/AJRUA6/RUENG-1169

Ding, C.; Wei, P.F.; Shi, Y.; Liu, J.X.; Broggi, M.; Beer, M. (2024): Sampling and active learning methods for network reliability estimation using K-terminal spanning tree,  Reliability Engineering & System Safety, 250, Article 110309
DOI: 10.1016/j.ress.2024.110309

Grashorn, J.; Broggi, M.; Ludovic, C.; Beer, M. (2024): Efficiency comparison of MCMC and Transport Map Bayesian posterior estimation for structural health monitoring,  Mechanical Systems and Signal Processing, 216, Article 111440
DOI: 10.1016/j.ymssp.2024.111440

Shi, Y.; Behrensdorf, J.; Zhou, J.Y.; Hu, Y.; Broggi, M.; Beer, M. (2024): Network Reliability Analysis through Survival Signature and Machine Learning Techniques,  Reliability Engineering and System Safety, 242, Article 109806
DOI: 10.1016/j.ress.2023.109806

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, Article 109775.
DOI: 10.1016/j.ymssp.2022.109775

Feng, C.X.; Faes, M.; Broggi, M.; Dang, C.; Yang, J.S.; Zheng, Z.B.; Beer, M. (2023): Application of interval field method to the stability analysis of slopes in presence of uncertainties,  Computers and Geotechnics, 153, Article 105060.
DOI: 10.1016/j.compgeo.2022.105060

Grashorn, J.; Urrea-Quintero, J.-H.; Broggi, M.; Chamoin, L.; Beer, M. (2023): Transport map Bayesian parameter estimation for dynamical systems,  Proceedings in Applied Mathematics and Mechanics, 23(1), Article e202200136
DOI: 10.1002/pamm.202200136

Persoons, A.; Wei, P.F.; 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, Article 144.
DOI: 10.1007/s00158-023-03598-6

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 the Context of Resilience Optimization,  Disaster Prevention and Resilience, 2(2):4.
DOI: 10.20517/dpr.2023.03

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, Article 103287.
DOI: 10.1016/j.probengmech.2022.103287

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, Article 103269.
DOI: 10.1016/j.probengmech.2022.103269

Kitahara, M.; Bi, S.F.; Broggi, M.; Beer, M. (2022): Nonparametric Bayesian stochastic model updating with hybrid uncertainties,  Mechanical Systems and Signal Processing, 163, Article 108195.

Kitahara, M.; Song, J.W.; Wei, P.F.; Broggi, M.; Beer, M. (2022): A distributionally robust approach for mixed aleatory and epistemic uncertainties propagation,  AIAA Journal, in press.

Kitahara, M.;Bi, S.F.; Broggi, M.; Beer, M. (2022): Distribution-free stochastic model updating of dynamic systems with parameter dependencies,  Structural Safety, 97, Article 102227

Lye, A.; Kitahara, M.; Broggi, M.; Patelli, E. (2022): Robust optimization of a dynamic Black-box system under severe uncertainty: A distribution-free framework,  Mechanical Systems and Signal Processing, 167, Article 108522.

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, 61–78.
DOI: 10.1016/j.rcns.2022.10.005

Bai, Y.T.; Li, Y.S.; Tang, Z.Y.; 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/s10518-021-01076-2

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 and System Safety, 216, Article 107935.
DOI: 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, Article 107834.
DOI: https://doi.org/10.1016/j.ymssp.2021.107834

Kitahara, M.; Bi, S.F.; 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), Article 04021030.

Kitahara, M.; Broggi, B.; Beer, M (2021): Residual seismic performance estimation of seismic-isolated bridges based on model updating using approximate Bayesian computation,  Journal of Japan Society of Civil Engineers, part A1 (Structural Engineering & Earthquake Engineering), 77, I_61–I_70.

Salomon, J.; Winnewisser, N.; Wei, P.F.; Broggi, M.; Beer, M. (2021): Efficient Reliability Analysis of Complex Systems in Consideration of Imprecision,  Reliability Engineering and System Safety, 216, Article 107972.
DOI: 10.1016/j.ress.2021.107972

Valdebenito, M.A.; Wei, P.F.; Song, J.W.; Beer, M.; Broggi, M. (2021): Failure Probability Estimation of a Class of Series Systems by Multidomain Line Sampling,  Reliability Engineering and System Safety, 213, Article 107673.

Yang, L.C.; Bi, S.F.; Faes, M.G.R.; Broggi, M.; Beer, M. (2021): Bayesian inversion for imprecise probabilistic models using a novel entropy-based uncertainty quantification metric,  Mechanical Systems and Signal Processing, 162, Article 107954.

Kitahara, M.; Broggi, M.; Beer, M. (2020): Efficient seismic performance estimation method by surrogate modeling based on adaptive Kriging and Markov chain Monte Carlo,  Journal of Japan Society of Civil Engineers, part A2 (Applied Mechanics), 76, 75–86.

Mi, J.H, Beer, M.; Li, Y.F.; Broggi, M.; Cheng, Y.H. (2020): Reliability and Importance Analysis of Uncertain System with Common Cause Failures Based on Survival Signature,  Reliability Engineering and System Safety, 201, Article 106988.
DOI: https://doi.org/10.1016/j.ress.2020.106988

Mi, J.H; Li, Y.F.; Beer, M.; Broggi, M.; Cheng, Y.H. (2020): Importance measure of probabilistic common cause failures under system hybrid uncertainty based on bayesian network,  Maintenance and reliability, 22 (1), 112–120.
DOI: https://doi.org/10.17531/ein.2020.1.13

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), Article 041006.
DOI: 10.1115/1.4044043

Bi, S.F.; Broggi, M.; Wei, P.F.; Beer, M. (2019): The Bhattacharyya distance: enriching the P-box in stochastic sensitivity analysis,  Mechanical Systems and Signal Processing, 129, pp. 265-281.
DOI: 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.2018.08.050

Faes, M.; Sadeghi, J.; Broggi, M.; De Angelis, M.; Patelli, E.; Beer, M.; Moens, D. (2019): On the robust estimation of small failure probabilities for strong non-linear models,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 5, Article 041007.
DOI: 10.1115/1.4044044

He, L.X.; Gomes, A.T.; Broggi, M.; Beer, M. (2019): Failure Analysis of Soil Slopes with Advanced Bayesian Networks,  Periodica Polytechnica Civil Engineering.
DOI: 10.3311/PPci.14092

He, L.X.; Wang, L.; Beer, M.; Liu, Y.; Broggi, M.; Bi, S.F. (2019): Estimation of failure probability in a braced excavation by Bayesian networks integrating with model updating approaches,  Underground Space, 5(4), 315–323.

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), art. no. 031003.
DOI: 10.1115/1.4043150

Salomon, J.; Broggi, M.; Kruse, S.; Weber, S.; Beer, M. (2019): Resilience Decision-Making Method For Complex Systems,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 6(2), Article 020901. | File |
DOI: 10.1115/1.4044907

Song, J.W.; Wei, P.F.; Valdebenito, M.; Bi, S.F.; Broggi, M.; Beer, M.; Lei, Z.X. (2019): Generalization of non-intrusive imprecise stochastic simulation for mixed uncertain variables,  Mechanical Systems and Signal Processing, 134, 106316, 17 pages.

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.2019.02.015

Wei, P.F.; Song, J.W.; Bi, S.F.; Broggi, M.; Beer, M.; Lu, Z.Z.; Yue, Z.F. (2019): Non-intrusive stochastic analysis with parameterized imprecise probability models: I. Performance estimation,  Mechanical Systems and Signal Processing, 124, 349-368.
DOI: 10.1016/j.ymssp.2019.01.058

Bi, S.F.; Broggi, M.; Beer, M. (2018): The role of the Bhattacharyya distance in stochastic model updating,  Mechanical Systems and Signal Processing, 117: 437-452.
DOI: 10.1016/j.ymssp.2018.08.017

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.2017.10.015

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.2017.10.020

Jiang, Y.B.; Luo, J.; Beer, M.; Patelli, E.; Broggi, M.; He, Y.H.; Zhang, J.R. (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.2016.10.002

Patelli, E.; Govers, Y.; Broggi, M.; Martins Gomes, H.; Link, M.; Mottershead, J. (2017): Sensitivity or Bayesian model updating: a comparison of techniques using the DLR AIRMOD test data,  Archive of Applied Mechanics, Volume 87, Issue 5, pp 905–925.
DOI: 10.1007/s00419-017-1233-1

Evans, Ll.M.; Arregui-Mena, J.D.; Mummery, P.M.; Akers, R.; Surrey, E.; Shterenlikht, A.; Broggi, M.; Margetts, L. (2016): Use of massively parallel computing to improve modelling accuracy within the nuclear sector,  The International Journal of Multiphysics, 10, 2.
DOI: 10.21152/1750-9548.10.2.215

Rocchetta, R.; Patelli, E.; Broggi, M.; Schewe, S. (2016): Robust probabilistic risk/safety analysis of complex systems and critical infrastructures,  Reliability Engineering and System Safety, 136, 47-61.

Venturini, Tiziano; Trefolini, Emanuele; Patelli, Edoardo; Broggi, Matteo; Tuliani, Giacomo; Disperati, Leonardo (2016): Mapping slope deposits depth by means of cluster analysis: a comparative assessment,  Rendiconti online della societa geologica italiana, Vol. 39/2016: 47-50.
DOI: 10.3301/ROL.2016.44

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.

Patelli, E.; Murat Panayirci, H.; Broggi, M.; Goller, B.; Beaurepaire, P.; Pradlwarter, H. J.; Schuëller, G. I. (2012): General purpose software for efficient uncertainty management of large finite element models,  Finite Elements in Analysis and Design; 51(1): 31—48.

Zio, E.; Broggi, M.; Golea, L. R.; Pedroni, N. (2012): Failure and reliability predictions by infinite impulse response locally recurrent neural networks,  Chemical Engineering Transactions; 26: 117—122.

Broggi, M.; Calvi, A.; Schuëller, G. (2011): Reliability assessment of axially compressed composite cylindrical shells with random imperfections,  International Journal of Structural Stability and Dynamics; 11(2): 215—236.
DOI: 10.1142/S0219455411004063

Broggi, M.; Schuëller, G. (2011): Efficient modeling of imperfections for buckling analysis of composite cylindrical shells,  Engineering Structures; 33(5): 1796—1806.

Goller, B.; Broggi, M.; Calvi, A.; Schuëller, G. (2011): A stochastic model updating technique for complex aerospace structures,  Finite Elements in Analysis and Design; 47(7): 739—752.

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.

Zio, E.; Pedroni, N.; Broggi, M.; Golea, L. R. (2009): Modelling the dynamics of the lead bismuth eutectic experimental accelerator driven system byan infinite impulse response locally recurrent neural network,  Nuclear Engineering and Technology; 41(10): 1293—1306.