Optimization of creep constitutive modeling of Lead-Free Solder using gene expression programming methods

In this paper, the GEP method is utilized to derive an ontological model for creep data, focusing on the mechanical properties and structural deformation mechanisms of solder at different scales. By analyzing the effect of micro and meso-structural morphology on the material, experimental validation is provided for the construction of an ontological model that depicts the viscoplasticity of Pb-Free solder in detail. Iterative optimization of a larger population of experimental samples will drive the development of a fine-grained intrinsic model that will be supported by solid theoretical and empirical evidence, advancing the field towards deeper understanding and innovation. In this study, the GEP algorithm is used to fit the intrinsic model of solder creep and is shown to have good fitting results. The advantages of GEP in equation model fitting are the simplicity of its heuristic algorithm, the ease of its implementation and its good optimization results. In addition, GEP is highly flexible, adaptable and robust to noisy data. After comparing the experimental data simulations, it is found that GEP is able to accurately analyze and predict in the establishment and optimization of creep model, which brings an important contribution to the field of solder research.