A semi-implicit stochastic multiscale method for radiative heat transfer problem

TL;DR

This paper introduces a semi-implicit stochastic multiscale method for radiative heat transfer in composite materials, effectively handling nonlinearity, multiscale spatial features, and high-dimensional randomness with proven convergence and numerical validation.

Contribution

The paper develops a novel semi-implicit stochastic multiscale approach that separates and efficiently addresses spatial multiscale properties, high-dimensional randomness, and nonlinearity in radiative heat transfer problems.

Findings

The method achieves optimal convergence rates.

Numerical experiments demonstrate efficiency and accuracy.

The approach effectively handles complex microstructures.

Abstract

In this paper, we propose and analyze a new semi-implicit stochastic multiscale method for the radiative heat transfer problem with additive noise fluctuation in composite materials. In the proposed method, the strong nonlinearity term induced by heat radiation is first approximated, by a semi-implicit predictor-corrected numerical scheme, for each fixed time step, resulting in a spatially random multiscale heat transfer equation. Then, the infinite-dimensional stochastic processes are modeled and truncated using a complete orthogonal system, facilitating the reduction of the model's dimensionality in the random space. The resulting low-rank random multiscale heat transfer equation is approximated and computed by using efficient spatial basis functions based multiscale method. The main advantage of the proposed method is that it separates the computational difficulty caused by the spatial multiscale properties, the high-dimensional randomness and the strong nonlinearity of the solution, so they can be overcome separately using different strategies. The convergence analysis is carried out, and the optimal rate of convergence is also obtained for the proposed semi-implicit stochastic multiscale method. Numerical experiments on several test problems for composite materials with various microstructures are also presented to gauge the efficiency and accuracy of the proposed semi-implicit stochastic multiscale method.