273 citations · 406 across the 10 of their papers we have counts for
11 papers
High-dimensional reliability-based design optimization using stochastic emulators
M. Moustapha, B. Sudret
Reliability-based design optimization (RBDO) is traditionally formulated as a nested optimization and reliability problem and remains computationally demanding, especially in high…
AL-SPCE - Reliability analysis for nondeterministic models using stochastic polynomial chaos expansions and active learning
A. Pires, M. Moustapha, S. Marelli +1
Reliability analysis traditionally relies on deterministic simulators, where identical inputs yield identical outputs. However, many real-world systems exhibit stochastic behavior,…
Reliability analysis for non-deterministic limit-states using stochastic emulators
Anderson V. Pires, Maliki Moustapha, Stefano Marelli +1
Reliability analysis is a sub-field of uncertainty quantification that assesses the probability of a system performing as intended under various uncertainties. Traditionally, this…
Reliability analysis for data-driven noisy models using active learning
Anderson V. Pires, Maliki Moustapha, Stefano Marelli +1
Reliability analysis aims at estimating the failure probability of an engineering system. It often requires multiple runs of a limit-state function, which usually relies on computa…
Reliability analysis of arbitrary systems based on active learning and global sensitivity analysis
Maliki Moustapha, Pietro Parisi, Stefano Marelli +1
System reliability analysis aims at computing the probability of failure of an engineering system given a set of uncertain inputs and limit state functions. Active-learning solutio…
Learning non-stationary and discontinuous functions using clustering, classification and Gaussian process modelling
M. Moustapha, B. Sudret
Surrogate models have shown to be an extremely efficient aid in solving engineering problems that require repeated evaluations of an expensive computational model. They are built b…
Multi-objective robust optimization using adaptive surrogate models for problems with mixed continuous-categorical parameters
M. Moustapha, A. Galimshina, G. Habert +1
Explicitly accounting for uncertainties is paramount to the safety of engineering structures. Optimization which is often carried out at the early stage of the structural design of…
Active learning for structural reliability: survey, general framework and benchmark
M. Moustapha, S. Marelli, B. Sudret
Active learning methods have recently surged in the literature due to their ability to solve complex structural reliability problems within an affordable computational cost. These…
A two-level Kriging-based approach with active learning for solving time-variant risk optimization problems
H. M. Kroetz, M. Moustapha, A. T. Beck +1
Several methods have been proposed in the literature to solve reliability-based optimization problems, where failure probabilities are design constraints. However, few methods addr…
Surrogate-assisted reliability-based design optimization: a survey and a new general framework
M. Moustapha, B. Sudret
Reliability-based design optimization (RBDO) is an active field of research with an ever increasing number of contributions. Numerous methods have been proposed for the solution of…
Quantile-based optimization under uncertainties using adaptive Kriging surrogate models
M. Moustapha, B. Sudret, J. -M. Bourinet +1
Uncertainties are inherent to real-world systems. Taking them into account is crucial in industrial design problems and this might be achieved through reliability-based design opti…