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A meta-model (or a surrogate model) is the modern name for what wastraditionally called a response surface. It is intended to mimic the behaviourof a computational model M (e.g. a finite element model in mechanics) whilebeing inexpensive to evaluate, in contrast to the original model which may takehours or even days of computer processing time. In this paper various types ofmeta-models that have been used in the last decade in the context of structuralreliability are reviewed. More specifically classical polynomial responsesurfaces, polynomial chaos expansions and kriging are addressed. It is shownhow the need for error estimates and adaptivity in their construction hasbrought this type of approaches to a high level of efficiency. A new techniquethat solves the problem of the potential biasedness in the estimation of aprobability of failure through the use of meta-models is finally presented.

Meta-models for structural reliability and uncertainty quantification