具有空间相关系数的对流扩散方程的双松弛时间正则化晶格玻尔兹曼模型

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Yuan Yu , Zuojian Qin , Haizhuan Yuan , Shi Shu
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引用次数: 0

摘要

本文为具有空间依赖系数的对流扩散方程(CDE)提出了一种新的双松弛-时间正则化(TRT-R)晶格玻尔兹曼(LB)模型。在此框架内,我们首先通过对非平衡态部分进行高阶赫米特展开,构建一个新的正则化程序,从而推导出 TRT-R 碰撞算子(CO)。然后,引入离散源项的一阶离散速度形式,以提高源项的精度。最后,我们提出了一个新的一阶空间衍生辅助项来恢复正确的 CDE。为了评估这一模型,我们模拟了扩散强度可调的二维和三维非均质对流扩散问题。研究结果表明,在不同的时间步长、网格分辨率、扩散比例系数和魔法参数条件下,新引入的源项明显提高了模型的精度和稳定性。与传统的 BGK CO 相比,在大多数情况下,采用 TRT-R CO 可显著减少误差。此外,还研究了魔法参数对 TRT-R CO 性能的影响。除此以外,研究还证实了 TRT-R CO 在使用半程反弹方案强制执行 Dirichlet 边界条件时消除数值滑移的功效,从而进一步证明了该算法的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two-relaxation-time regularized lattice Boltzmann model for convection-diffusion equation with spatially dependent coefficients
In this paper, a new two-relaxation-time regularized (TRT-R) lattice Boltzmann (LB) model for the convection-diffusion equation (CDE) with spatially dependent coefficients is proposed. Within this framework, we first derive a TRT-R collision operator (CO) by constructing a new regularized procedure through the high-order Hermite expansion of non-equilibrium part. Then, a first-order discrete-velocity form of discrete source term is introduced to improve the accuracy of the source term. Finally, a new first-order space-derivative auxiliary term is proposed to recover the correct CDE. To assess this model, we simulated non-homogeneous convection-diffusion problems with adjustable diffusion intensity in both two and three dimensions. The findings indicate that the newly introduced source terms markedly enhance the model's precision and stability under varying time steps, grid resolutions, diffusion scaling coefficients, and magic parameters. The adoption of the TRT-R CO leads to a significant error reduction compared to the classic BGK CO in most scenarios. Furthermore, the influence of the magic parameter on the performance of the TRT-R CO was investigated. Beyond this, the study also confirms the efficacy of the TRT-R CO in eliminating numerical slip when enforcing Dirichlet boundary conditions with a halfway bounce-back scheme, thereby providing further evidence of the algorithm's advantages.
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CiteScore
7.20
自引率
4.30%
发文量
567
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