Stochastic Metamodel for Probability of Detection Estimation of Eddy-Current Testing Problem in Random Geometric | Abdelli, Djamel Eddin
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Stochastic Metamodel for Probability of Detection Estimation of Eddy-Current Testing Problem in Random Geometric

Archive ouverte : Article de revue

Abdelli, Djamel Eddin | Nguyen, Thanh Hung | Clenet, Stéphane | Cheriet, Ahmed

Edité par HAL CCSD ; Institute of Electrical and Electronics Engineers

International audience. 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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