394 citations · 2.7k across the 50 of their papers we have counts for
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Surrogate models for oscillatory systems using sparse polynomial chaos expansions and stochastic time warping
Chu V. Mai, Bruno Sudret
Polynomial chaos expansions (PCE) have proven efficiency in a number of fields for propagating parametric uncertainties through computational models of complex systems, namely stru…
Uncertainty propagation of p-boxes using sparse polynomial chaos expansions
Roland Schöbi, Bruno Sudret
In modern engineering, physical processes are modelled and analysed using advanced computer simulations, such as finite element models. Furthermore, concepts of reliability analysi…
Reliability analysis of high-dimensional models using low-rank tensor approximations
K. Konakli, B. Sudret
Engineering and applied sciences use models of increasing complexity to simulate the behaviour of manufactured and physical systems. Propagation of uncertainties from the input to…
Metamodel-based sensitivity analysis: Polynomial chaos expansions and Gaussian processes
L. Le Gratiet, S. Marelli, B. Sudret
Global sensitivity analysis is now established as a powerful approach for determining the key random input parameters that drive the uncertainty of model output predictions. Yet th…
Sparse polynomial chaos expansions of frequency response functions using stochastic frequency transformation
V. Yaghoubi, S. Marelli, B. Sudret +1
Frequency response functions (FRFs) are important for assessing the behavior of stochastic linear dynamic systems. For large systems, their evaluations are time-consuming even for…
Global sensitivity analysis using low-rank tensor approximations
K. Konakli, B. Sudret
In the context of global sensitivity analysis, the Sobol' indices constitute a powerful tool for assessing the relative significance of the uncertain input parameters of a model. W…