Damage detection is a crucial task to ensure the safety and integrity of civil engineering structures. So far, only a limited number of studies have been conducted to detect damage in retaining wall structures, and those that exist rely on simplified analytical models that cannot fully capture the complex interaction between the wall and soil. Accordingly, this study aims to propose a new approach for detecting damage in retaining wall structures through the updating of a high-fidelity ABAQUS based finite element model of the wall-soil system. The presented finite element model updating approach is further formulated as an inverse optimization problem, in which the damage variable is defined as a decrease in the elasticity modulus of the wall material, and the objective function is expressed as the discrepancy between the actual and computed displacement data collected along the wall height. In order to mitigate the computational burden associated with the iterative calculations during the model updating procedure, a surrogate model based on radial basis functions (RBF) is first established to simulate the mapping relationship between the damage variable and the objective function value to be optimized. Subsequently, the differential evolution (DE) algorithm, as a well-known meta-heuristic method, is employed to address the surrogate-based optimization problem. The capability of the proposed method is finally investigated by presenting two numerical examples, including a cantilever retaining wall and a sheet pile wall. The obtained results demonstrate the efficiency and accuracy of the presented approach for detecting damage in retaining wall structures
