A stochastic multiscale method for thermo-mechanical analysis arising from random porous materials with interior surface radiation. (February 2017)

• Record Type: Journal Article
• Authors: Yang, Zhiqiang; Cui, Junzhi; Sun, Yi; Liu, Yizhi; Xiao, Youcai
• Is Part Of: Advances in engineering software. Volume 104(2017)
• Page Start: 12
• Page End: 27
• Publication Date: 2017-02
• Subjects: Stochastic multiscale method -- Interior surface radiation -- Random porous materials -- Thermo-mechanical analysis; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2016.11.006
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: A stochastic multiscale analysis method is proposed. Thermo-mechanical coupling problem of random porous materials with radiation boundary condition is considered. Thermo-mechanical properties for the porous materials with varying probability distribution models are shown. Some numerical results are given in detail to validate the stochastic multiscale method developed. Abstract: A stochastic multiscale computational method for predicting the thermo-mechanical coupling properties of random porous materials is proposed. Here, the thermal radiation effect at microscale of the material consisting of randomly distributed pores is considered, which has an important impact on the macroscopic temperature and stress fields. A novel unified homogenization procedure, based on two-scale asymptotic expressions, has been established. The higher-order multiscale formulations for solving the dynamic thermo-mechanical coupling problem with the inertia term, coupling term and radiation term are given successively. Then, the statistical prediction algorithm based on the multiscale method is described in detail. Finally, numerical examples for porous materials with varying probability distribution models are calculated by the proposed algorithm, and compared with the data by finite element method with very fine meshes. The comparison shows that the stochastic multiscale computational method developed in this paper is useful for determination of the thermo-mechanical properties of porous materials and demonstrates its potential applications in engineering and technology.