Credibility Optimization of Space Structure Models with Uncertain Joint Parameters

Large space truss structures with a large number of flexible joints are widely used in aerospace engineering. However, in most studies, the uncertainty analysis of the joint parameters is not taken into consideration. In order to improve the credibility and prediction accuracy of simulation models, an optimization process based on radial basis functions and approximate Bayesian computation is proposed. The radial basis function model acts as a surrogate model for avoiding enormous computational cost. The proposed method is applied into a Pratt-type spatial truss with flexible joints. The flexible joint is modeled as a combination of six linear spring-damper elements. The lower and upper bounds of the stiffness and damping coefficients of the joints are updated. The results show that the optimized model has a higher level of credibility, which also verifies the effectiveness of the proposed method.