Screening and metamodeling of computer experiments with functional outputs. Application to thermal-hydraulic computations

Benjamin Auder (1) , Agnes de Crecy (1) , Bertrand Iooss (2, 3, 4) , Michel Marques (1)

1 CEA-DES (ex-DEN) - CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire)
2 GdR MASCOT-NUM - Méthodes d'Analyse Stochastique des Codes et Traitements Numériques
3 EDF R&D MRI - Management des Risques Industriels
4 IMT - Institut de Mathématiques de Toulouse UMR5219

To perform uncertainty, sensitivity or optimization analysis on scalar variables calculated by a cpu time expensive computer code, a widely accepted methodology consists in first identifying the most influential uncertain inputs (by screening techniques), and then in replacing the cpu time expensive model by a cpu inexpensive mathematical function, called a metamodel. This paper extends this methodology to the functional output case, for instance when the model output variables are curves. The screening approach is based on the analysis of variance and principal component analysis of output curves. The functional metamodeling consists in a curve classification step, a dimension reduction step, then a classical metamodeling step. An industrial nuclear reactor application (dealing with uncertainties in the pressurized thermal shock analysis) illustrates all these steps.

Mots clés: Functional output; Pressurized thermal shock transient; Principal component analysis; Uncertainty and sensitivity analysis

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

Benjamin Auder, Agnes de Crecy, Bertrand Iooss, Michel Marques. Screening and metamodeling of computer experiments with functional outputs. Application to thermal-hydraulic computations. Reliability Engineering and System Safety, 2012, 107, pp.122-131. ⟨hal-00525491v2⟩