Multi-Level Damage Detection Using Octree Partitioning Algorithm

This research proposes a damage detection methodology that takes advantages of full-field sensing of structural elements via 3D digital image correlation (3D-DIC) within a new optimization algorithm. To get a unique solution for a finite element model updating problem in detecting internal properties of a structure by topology optimization method, a novel strategy is proposed termed as octree partitioning algorithm (OPA). Damage detection is attained using minimizing a defined objective function of residuals between the observed and corresponding mimicked responses, resulting in the identification of the underlying material distribution. This brief paper explores this concept through a case study on a series of small structural test specimens with fabricated damage on the specimens. The results show that the proposed OPA has capability of tuning the initial model to find the ideal partition configuration for the proposed model updating process.