Global Sensitivity Analysis of Random Buckling Characteristics Based on The Kriging Method

As infrastructure construction gradually extends to regions such as plateaus and deserts, the complex and harsh natural environment will increase the risk of structural instability and collapse. The study of its buckling characteristics is of great significance for dynamic optimization design. Due to the influence of material production, construction processes and harsh outdoor environments, there is uncertainty in material properties (such as elastic modulus), which makes traditional deterministic analysis unable to meet actual needs. This paper takes an I-beam section column as an example, considers the randomness of the structural elastic modulus, and combines Latin hypercubic sampling and the Kriging method to establish a surrogate model between the first three order buckling loads and random parameters. Based on the surrogate model, the probability density distribution of the buckling load of the column structure was obtained, and the Sobol 'index was used to analyze the influence degree of the randomness of each parameter on the buckling characteristics of the support. The research results show that the first-order buckling load of this structure is easily affected by the bottom of the column. As the order increases, the parameters with greater influence gradually move towards the top, and the distribution range gradually expands. After considering the randomness of parameters, the critical buckling load of the structure will decrease, which indicates that the buckling load obtained based on deterministic analysis may lead to an underestimation of the actual failure risk of the structure. Therefore, stochastic analysis is very necessary. The method proposed in this paper has the characteristics of high stability and high efficiency in stochastic analysis.