Stochastic Metamodel for Probability of Detection Estimation of Eddy-Current Testing Problem in Random Geometric - Archive ouverte HAL
Article Dans Une Revue IEEE Transactions on Magnetics Année : 2019

Stochastic Metamodel for Probability of Detection Estimation of Eddy-Current Testing Problem in Random Geometric

Résumé

The calculation of the Probability Of Detection (POD) in Non Destructive Eddy Current Testing requires the solution of a stochastic model requiring numerous calls of a numerical model leading to a huge computation time. To reduce this computation time, we propose in this paper to combine either the use of a stochastic metamodel and a mapping which avoids the remeshing step. The stochastic metamodel is constructed using the Least Angle Regression Method. This approach is tested on a axisymmetric problem with 6 random input paramters which shows its efficiency and its accuracy.
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Dates et versions

hal-02282008 , version 1 (15-01-2020)

Identifiants

Citer

Djamel Eddin Abdelli, Thanh Hung Nguyen, Stéphane Clenet, Ahmed Cheriet. Stochastic Metamodel for Probability of Detection Estimation of Eddy-Current Testing Problem in Random Geometric. IEEE Transactions on Magnetics, 2019, 55 (6), pp.1-4. ⟨10.1109/TMAG.2019.2893421⟩. ⟨hal-02282008⟩
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