Detection of multiple complicated flaw clusters by dynamic variable-node XFEM with a three-step detection algorithm

Abstract

We present an efficient computational approach composed of forward and inverse analyses that can neatly capture multiple flaw clusters with high accuracy yet low computational effort. The inverse analysis consists of three continuous steps with distinct targets. Firstly, a combination of improved discrete artificial bee colony (IDABC) algorithm and hierarchical clustering analysis (HCA) is applied to seize sub-domains that contain flaw clusters with a conservative number of sensors. Secondly, additional sensors are introduced into the captured sub-domains so that flaw numbers and their rough geometries can be achieved by the IDABC-HCA optimizer. Eventually, the initial guesses of approximate geometries are turned towards the true geometries by using Broyden-Fletcher-Goldfarb-Shanno approach. In addition, a “Queue and Kill” method is used to determine and eliminate incorrect candidate flaws and/or clusters of flaws in the first two steps. The forward analysis is solved through a combination of dynamic extended finite element method (XFEM) enhanced by local mesh refinement, which highly matches the three-step strategy. The local mesh refinement not only improves the computational accuracy of concerning areas, i.e., sub-domains, but also controls the computation amount. Numerical examples demonstrate the effectiveness and robustness of the developed method in detecting multiple flaw clusters.