Efficient two-scale analysis with thermal residual stresses and strains based on self-consistent clustering analysis

Abstract

The thermal residual stresses and strains are crucial in the industrial manufacturing process of the metal alloys and other composites. In representative volume element (RVE) of these complex composite structures, how to accurately and efficiently simulate the responses considering thermal residual stresses and strains is also vital, which could be served as a foundation to multiscale analysis. Recently an effective reduced-order method named self-consistent clustering analysis (SCA) has been proposed to solve microscopic responses in RVE. This paper modifies the original SCA method for thermoelastic and thermal elastoplastic problems, and the microscopic responses of the RVE are compared with the results of analytical and Fast Fourier Transform (FFT) methods to validate its accuracy and feasibility. Then, this study demonstrates the influences of different clustering strategies in offline stage, develops the clustering number optimization and discusses the two-scale analysis using the modified SCA method with/without thermal residual stresses and strains in microscale. In two-scale analysis, the macroscopic and microscopic responses are studied to explore the effects of thermal residual stresses and strains. The two-scale analysis framework with modified SCA method proposed in this work is proved to be efficient in simulating composites considering thermal residual strains and stresses.