Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm

Abstract

The physical and mechanical parameters of hydraulic structures in complicated operating conditions often change over time. Updating these parameters in a timely manner is important to comprehend the operating behaviors and monitor the safety of hydraulic structures. Conventional inverse analysis methods can only generate inversions on the comprehensive deformation modulus of concrete dam structures, which contradict practical conditions. Based on the researches on conventional reversion methods of the deformation modulus of the dam body, foundation, and reservoir basin, the objective fitness function is established in this paper according to engineering-measured data and finite element simulation results. The quantum genetic algorithm has high global search efficiency and population diversity. A mechanical parameter inversion of high-arch dams is built from the intelligent optimization of an established algorithm by applying the quantum genetic algorithm. The proposed algorithm is tested to be feasible and valid for practical engineering projects and therefore shows scientific and practical application values.