Mengbo Zhu , Jianfeng Chen , Xiaoqiang Li , Congshan Zhuo , Sha Liu , Chengwen Zhong
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引用次数: 0
Abstract
A solver for the Shakhov model equation, founded on dugksFOAM, has been successfully developed. This was achieved through the application of a conservation-type gas kinetic scheme with a simplified interface flux. The process begins with the updating of macroscopic quantities. Subsequently, the distribution function is computed using these newly updated values. This innovative approach effectively mitigates errors that might occur during the integration of the distribution function, especially when an unstructured velocity space is employed. The solver offers two distinct methods for velocity space integration. The first is a traditional structured space, which can be conveniently adjusted and configured via input files. The second is an unstructured space, which utilizes fewer discrete velocity points. These points are determined based on the mesh files provided by the user. In this unstructured approach, the velocity points are strategically positioned to strike an optimal balance between computing efficiency and precision, thereby enhancing the overall performance and accuracy of the solver.
The solver's hybrid parallelization technique, specifically the X-space parallelization approach that encompasses both physical and velocity spaces, empowers the efficient execution of large-scale three-dimensional simulations. By subjecting the solver to benchmark cases such as shock tube problems, lid-driven cavity flow, Poiseuille flow, and flows past cylinders, sphere and X-38 vehicle, the accuracy and dependability of this solver have been thoroughly validated and verified. This comprehensive verification process not only benchmark cases the solver's robustness in handling diverse fluid dynamics scenarios but also highlights its potential for broader applications in the field of computational fluid dynamics.
期刊介绍:
The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper.
Computer Programs in Physics (CPiP)
These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged.
Computational Physics Papers (CP)
These are research papers in, but are not limited to, the following themes across computational physics and related disciplines.
mathematical and numerical methods and algorithms;
computational models including those associated with the design, control and analysis of experiments; and
algebraic computation.
Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.