Solar energy paper index

Parallel simulation of rarefied gas flows on unstructured meshes using the DIG-augmented DSMC method

2026-07-09 · arXiv: 2607.08195

One-line summary

A solar energy research paper on Parallel simulation of rarefied gas flows on unstructured meshes using the DIG-augmented DSMC method.

Engineering notes

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Chinese explanation / 中文解读

中文解读待补充:本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。

Original abstract

While the direct simulation Monte Carlo (DSMC) is a mainstream stochastic particle method for simulating rarefied gas flows, it incurs excessively high computational costs in the near continuum regime. As a hybrid acceleration approach coupling DSMC with macroscopic synthetic equations, the direct intermittent general synthetic iterative scheme (DIG) delivers fast convergence and asymptotic-preserving characteristics, which effectively alleviate the kinetic scale limitations inherent to standard DSMC. In this study, we develop a parallel DIG augmented DSMC solver for three dimensional rarefied gas flow simulations on unstructured meshes. On top of the standard DSMC algorithms for particle transport and collisions, a reliable intermittent coupling framework is constructed to exchange macroscopic flow data between the stochastic DSMC module and deterministic macroscopic synthetic equations. For parallel execution on unstructured grids, we employ a hybrid MPI architecture equipped with ghost cells to enable local particle tracking and batch inter-rank particle migration. A graph partitioning based dynamic load balancing strategy is also integrated to mitigate uneven particle distribution over computational domains. Numerical results demonstrate that the proposed solver achieves satisfactory agreement with the SPARTA DSMC. Leveraging the fast convergence and asymptotic-preserving properties of the DIG method, the required number of spatial cells and statistical sampling steps are drastically decreased, leading to substantial reductions in computational memory and runtime. This work presents an efficient high-performance numerical tool for high-fidelity simulations of rarefied flows over complex geometries. The code is available in the developer repository at the github link.

5.0Engineering value
7.0Research novelty
4.0Business relevance

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