7 citations · 14 across the 9 of their papers we have counts for
9 papers
A generalized framework for performance-based earthquake engineering: integrated assessment of structural reliability and resilience
C. NArdin, S. Marelli, B. Sudret +1
Assessing structural performance under seismic hazard requires accounting for both damage accumulation and post-event recovery. In current performance-based earthquake engineering…
Time-variant reliability using time-dependent surrogate models
Stefano Marelli, Styfen Schär, Bruno Sudret
Time-variant reliability analysis is a critical task for ensuring the safety of engineering dynamical systems subjected to stochastic excitations. However, assessing failure probab…
MF-GLaM: A multifidelity stochastic emulator using generalized lambda models
K. Giannoukou, X. Zhu, S. Marelli +1
Stochastic simulators exhibit intrinsic stochasticity due to unobservable, uncontrollable, or unmodeled input variables, resulting in random outputs even at fixed input conditions.…
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…
Surrogate modeling with functional nonlinear autoregressive models (F-NARX)
Styfen Schär, Stefano Marelli, Bruno Sudret
We propose a novel functional approach to surrogate modeling of dynamical systems with exogenous inputs. This approach, named Functional Nonlinear AutoRegressive with eXogenous inp…
UQ state-dependent framework for seismic fragility assessment of industrial components
C. Nardin, S. Marelli, O. S. Bursi +2
In this study, we propose a novel surrogate modelling approach to efficiently and accurately approximate the response of complex dynamical systems driven by time-varying Recently,…
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…
Uncertainty-aware multi-fidelity surrogate modeling with noisy data
Katerina Giannoukou, Stefano Marelli, Bruno Sudret
Emulating high-accuracy computationally expensive models is crucial for tasks requiring numerous model evaluations, such as uncertainty quantification and optimization. When lower-…