In simulation-based realization of complex systems, we are forced to address the issue of
computational complexity. One critical issue that must be addressed is the approximation of …

This paper addresses the issue of designing experiments for a metamodel that needs to be
accurate for a certain level of the response value. Such a situation is common in constrained …

A surrogate modeling strategy, using effective interpolation and sampling methods,
facilitates a reduction in the number of computational fluid dynamics simulations required to …

Computational models with variable fidelity have been widely used in engineering design.
To alleviate the computational burden, surrogate models are used for optimization without …

Robust design is an effective approach to design under uncertainty. Many works exist on
mitigating the influence of parametric uncertainty associated with design or noise variables …

Simulation models with different levels of fidelity have been widely used in engineering
design. Even though the nonhierarchical multimodel fusion approach has been developed …

Metamodels are becoming increasingly popular for representing unknown black box
functions. Several metamodel classes exist, including response surfaces and spline-based …

Among current meta‐modelling approaches, Bayesian‐based interpolative methods have
received significant attention in the literature. These methods are particularly known for their …

Cette thèse est consacrée à la planification et l'exploitation d'expériences numériques à
l'aide de modèles de remplacement (métamodèles), et plus particulièrement à la prise en …

An adaptive sampling method is presented for optimizing the location of data points in
parameter space for multidimensional data interpolation. The method requires a small …