Matteo Broggi

发表

General purpose software for efficient uncertainty management of large finite element models

Edoardo Patelli, H. Murat Panayirci, Matteo Broggi, 2012, Finite elements in analysis and design : the international journal of applied finite elements and computer aided engineering.

A Bayesian Framework for Crack Detection in Structural Components Under Dynamic Excitation

Edoardo Patelli, Matteo Broggi, P. Beaurepaire, 2013 .

Failure Analysis of Soil Slopes with Advanced Bayesian Networks

Michael Beer, Matteo Broggi, Long Xue He, 2019, Periodica Polytechnica Civil Engineering.

Use of massively parallel computing to improve modelling accuracy within the nuclear sector

Lee Margetts, José David Arregui-Mena, Paul Mummery, 2016 .

RELIABILITY ASSESSMENT OF AXIALLY COMPRESSED COMPOSITE CYLINDRICAL SHELLS WITH RANDOM IMPERFECTIONS

Matteo Broggi, Gerhart I. Schuëller, A. Calvi, 2011 .

COSSAN-X: A General Purpose Code for Computational Stochastic Structural Analysis

Edoardo Patelli, Gerhart I. Schuëller, Matteo Broggi, 2010 .

Computation of the Sobol' indices using importance sampling

Edoardo Patelli, Matteo Broggi, Pierre Beaurepaire, 2014 .

An integrated and efficient numerical framework for uncertainty quantification: application to the NASA Langley multidisciplinary uncertainty quantification challenge

Marco de Angelis, Edoardo Patelli, Matteo Broggi, 2014 .

Survival signature approach for the reliability analysis of an axial compressor

Joerg R. Seume, Matteo Broggi, Michael Beer, 2017 .

Locally Recurrent Neural Networks for Nuclear Dynamics Modeling

Enrico Zio, Matteo Broggi, Nicola Pedroni, 2008 .

Meta-models for fatigue damage estimation of offshore wind turbines jacket substructures

Raimund Rolfes, Matteo Broggi, Cristian Guillermo Gebhardt, 2017 .

Failure and Reliability Predictions by Infinite Impulse Response Locally Recurrent Neural Networks

Enrico Zio, Matteo Broggi, Nicola Pedroni, 2012 .

Estimation of failure probability in braced excavation using Bayesian networks with integrated model updating

Michael Beer, Yong Liu, Matteo Broggi, 2020 .

Model updating strategy of the DLR-AIRMOD test structure

Edoardo Patelli, John E. Mottershead, Matteo Broggi, 2017 .

The role of the Bhattacharyya distance in stochastic model updating

Michael Beer, Matteo Broggi, Sifeng Bi, 2019, Mechanical Systems and Signal Processing.

On the Robust Estimation of Small Failure Probabilities for Strong Nonlinear Models

Jonathan Sadeghi, Marco de Angelis, Edoardo Patelli, 2019, ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg.

Predicting Reliability by Recurrent Neural Networks

Enrico Zio, Matteo Broggi, Nicola Pedroni, 2008 .

A BAYESIAN MODEL UPDATING PROCEDURE FOR DYNAMIC HEALTH MONITORING

Edoardo Patelli, Matteo Broggi, P. Beaurepaire, 2014 .

Model Updating by Uncertain Parameter Inference

Edoardo Patelli, John E. Mottershead, Matteo Broggi, 2014 .

Efficient Model Updating of the GOCE Satellite Based on Experimental Modal Data

Gerhart I. Schuëller, Matteo Broggi, B. Goller, 2013 .

Efficient modeling of imperfections for buckling analysis of composite cylindrical shells

Matteo Broggi, Gerhart I. Schuëller, M. Broggi, 2011 .

Common Cause Failure Importance Analysis for Aerospace Systems

Jinhua Mi, Matteo Broggi, Yuhua Cheng, 2019 .

A multivariate interval approach for inverse uncertainty quantification with limited experimental data

Edoardo Patelli, Michael Beer, John E. Mottershead, 2019, Mechanical Systems and Signal Processing.

Efficient Approximation of the Survival Signature for Large Networks

Matteo Broggi, Michael Beer, Sebastian Brandt, 2018 .

On-line Bayesian model updating for structural health monitoring

Edoardo Patelli, Matteo Broggi, Roberto Rocchetta, 2018 .

Efficient Reliability and Risk Analysis of Complex Interconnected Systems

Michael Beer, Matteo Broggi, Jasper Behrensdorf, 2018 .

Uncertainty Management in Multidisciplinary Design of Critical Safety Systems

Marco de Angelis, Edoardo Patelli, Matteo Broggi, 2015, J. Aerosp. Inf. Syst..

Do we have enough data? Robust reliability via uncertainty quantification

Edoardo Patelli, Matteo Broggi, Roberto Rocchetta, 2018 .

BAYESIAN MODEL UPDATING FOR EXISTING SEISMIC-ISOLATED BRIDGES USING OBSERVED ACCELERATION RESPONSE DATA

Michael Beer, Matteo Broggi, Masaru Kitahara, 2020 .

Non-intrusive stochastic analysis with parameterized imprecise probability models: II. Reliability and rare events analysis

Michael Beer, Zhenzhou Lu, Pengfei Wei, 2019, Mechanical Systems and Signal Processing.

Reliability-Based Methodology for the Optimal Design of Viscous Dampers

Edoardo Patelli, Enrico Tubaldi, Matteo Broggi, 2017 .

MODELLING THE DYNAMICS OF THE LEAD BISMUTH EUTECTIC EXPERIMENTAL ACCELERATOR DRIVEN SYSTEM BY AN INFINITE IMPULSE RESPONSE LOCALLY RECURRENT NEURAL NETWORK

Enrico Zio, Matteo Broggi, Nicola Pedroni, 2009 .

Failure and Reliability Predictions by Locally Recurrent Neural Networks

Enrico Zio, Matteo Broggi, Nicola Pedroni, 2012 .

A stochastic model updating technique for complex aerospace structures

Gerhart I. Schuëller, Matteo Broggi, B. Goller, 2011 .

Decision-Making for Resilience-Enhancing Endowments in Complex Systems using Principles of Risk Measures

Sebastian Kruse, Matteo Broggi, Stefan Weber, 2018 .

Sensitivity Analysis of Material and Load Parameters to Fatigue Stresses of an Offshore Wind Turbine Monopile Substructure

Peter Schaumann, Michael Beer, Matteo Broggi, 2017 .

Reliability-based design of fluid viscous damper for seismic protection of building frames

Edoardo Patelli, Andrea Dall'Asta, Enrico Tubaldi, 2014 .

Generalization of non-intrusive imprecise stochastic simulation for mixed uncertain variables

Michael Beer, Pengfei Wei, Matteo Broggi, 2019, Mechanical Systems and Signal Processing.

Non-intrusive stochastic analysis with parameterized imprecise probability models: I. Performance estimation

Michael Beer, Zhenzhou Lu, Pengfei Wei, 2019, Mechanical Systems and Signal Processing.

OpenCossan: an efficient open tool for dealing with epistemic and aleatory uncertainties

Marco de Angelis, Edoardo Patelli, Matteo Broggi, 2014 .

Risk Assessment for Slope Stability with enhanced Bayesian Networks Methods

Matteo Broggi, Michael Beer, António Topa Gomes, 2018 .

Bayesian Model Updating in Time Domain with Metamodel-Based Reliability Method

Matteo Broggi, Michael Beer, Sifeng Bi, 2021 .

Contaminant source identification in water distribution networks: A Bayesian framework

Matteo Broggi, Michael Beer, Hector A. Jensen, 2021 .

Sensitivity Analysis of an Aircraft Engine Model Under Consideration of Dependent Variables

Matteo Broggi, Jens Friedrichs, Michael Beer, 2021, Volume 1: Aircraft Engine; Fans and Blowers; Marine; Wind Energy; Scholar Lecture.

Numerically efficient computation of the survival signature for the reliability analysis of large networks

Matteo Broggi, Michael Beer, Tobias-Emanuel Regenhardt, 2021, Reliab. Eng. Syst. Saf..

Efficient reliability analysis of complex systems in consideration of imprecision

Pengfei Wei, Matteo Broggi, Michael Beer, 2021, Reliab. Eng. Syst. Saf..

Failure probability estimation of a class of series systems by multidomain Line Sampling

Pengfei Wei, Matteo Broggi, Michael Beer, 2021, Reliab. Eng. Syst. Saf..

Sensitivity or Bayesian model updating: a comparison of techniques using the DLR AIRMOD test data

Edoardo Patelli, John E. Mottershead, Michael Link, 2017 .

Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure

Edoardo Patelli, David Moens, Matteo Broggi, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

A probability‐box approach on uncertain correlation lengths by stochastic finite element method

Matteo Broggi, Michael Beer, Udo Nackenhorst, 2018, PAMM.