Xiaohan Jing , Lin Qiu , Hong Zhao , Zeqian Zhang , Yaoming Zhang , Yan Gu
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引用次数: 0
Abstract
In this study, an accurate and stable space-time radial basis function (STRBF) collocation method is developed to solve two- and three-dimensional dynamic coupled thermo-mechanical problems. The proposed method enhances numerical precision by strategically positioning source points beyond the computational domain through space-time scaling factors. To address the challenge of selecting the optimal shape parameter, a new coupled STRBF is formulated by combining the Multiquadric function with the conical spline. Furthermore, a multiscale computational strategy is implemented to mitigate numerical instability in the resulting linear system. The effectiveness of the developed approach is demonstrated through four numerical examples involving complex geometries and different initial and boundary conditions. Numerical results show that, compared to the traditional RBF collocation method, the developed scheme not only enhances computational accuracy but also significantly reduces the dependence on the choice of shape parameter, making it a promising method for dealing with transient coupled thermo-mechanical problems.
期刊介绍:
Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory.
The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation.
This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods.
Computational science typically unifies three distinct elements:
• Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous);
• Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems;
• Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).