Reliability Analysis of Concrete Gravity Dams Based on Least Squares Support Vector Machines with an Improved Particle Swarm Optimization Algorithm

Abstract

A reliability analysis method based on least squares support vector machines with an improved particle swarm optimization algorithm (IPSO-LSSVM) is proposed to calculate the reliability of concrete gravity dams when explicit nonlinear limit-state functions are difficult to obtain accurately. First, the main failure modes of concrete gravity dams and their influencing factors are determined. Second, Latin hypercube sampling is used to create samples. A finite element calculation batch program of concrete gravity dams is written to calculate the safety indexes of each sample. Third, based on the samples, the IPSO-LSSVM model is established to replace the finite element calculation. Finally, the failure probability of concrete gravity dams is obtained by using the Monte Carlo (MC) method. The case study for a typical concrete gravity dam in the Yunnan Province of China shows that the dam is reliable because the failure probability is 8.87 × 10−5. The proposed reliability analysis method is efficient and feasible for calculating the reliability of concrete gravity dams.