B. Echard

TL;DR: An iterative approach based on Monte Carlo Simulation and Kriging metamodel to assess the reliability of structures in a more efficient way and is shown to be very efficient as the probability of failure obtained with AK-MCS is very accurate and this, for only a small number of calls to the performance function.

TL;DR: An original and easily implementable method called AK-IS for active learning and Kriging-based Importance Sampling, based on the AK-MCS algorithm, that enables the correction or validation of the FORM approximation with only a very few mechanical model computations.

TL;DR: In this article, the authors proposed a more general and robust approach that is able to accurately assess the failure probability and determine importance factors of each random variable for potential time-demanding mechanical models, such as those encountered in industry.

TL;DR: In this paper, a Kriging-based procedure is proposed to identify the minimum of measured points to check the conformity with a given confidence level, which is validated on a simple example of orientation tolerance and then performed to inspect the form defect on three aircraft workpieces.

TL;DR: In this article, a finite element model was developed to simulate the impact tests and this was used to calculate the dynamic strain energy release rate, which was compared with that determined using a simple analytical method.