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This study presents a detailed numerical analysis of lid-driven cavity flow using two advanced computational approaches: the Highly Stable Lattice Boltzmann Method (HSLBM) and the Multiple-Relaxation-Time Lattice Boltzmann Method (MRT-LBM). The investigation examines the influence of critical parameters, including Reynolds numbers (Re) ranging from 100 to 10,000 and grid resolutions varying from 21 × 21 to 261 × 261 nodes. Through comprehensive simulations, we analyze key flow characteristics including velocity profiles, streamline patterns, and vortex formation dynamics within the cavity. The results demonstrate that both methods successfully capture primary and secondary vortices, showing excellent agreement with benchmark data at moderate Reynolds numbers. Notably, HSLBM exhibits superior numerical stability at elevated Reynolds numbers and requires less memory than MRT-LBM. Our comparative analysis reveals that HSLBM achieves accuracy comparable to MRT-LBM while providing enhanced stability and computational efficiency. These findings offer valuable insights into the relative performance and practical applicability of these methods for internal flow simulations.

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Analysis of the Effects of Physical Parameters in Internal Flow Using the Highly Stable Lattice Boltzmann Method and MRT Lattice Boltzmann Method

  • 会议论文

  • 发表日期：

    2025年

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  • Abdelhak Bahlouli,
  • Adel Lalaoua,
  • Idir Lasloudji

摘要

This study presents a detailed numerical analysis of lid-driven cavity flow using two advanced computational approaches: the Highly Stable Lattice Boltzmann Method (HSLBM) and the Multiple-Relaxation-Time Lattice Boltzmann Method (MRT-LBM). The investigation examines the influence of critical parameters, including Reynolds numbers (Re) ranging from 100 to 10,000 and grid resolutions varying from 21 × 21 to 261 × 261 nodes. Through comprehensive simulations, we analyze key flow characteristics including velocity profiles, streamline patterns, and vortex formation dynamics within the cavity. The results demonstrate that both methods successfully capture primary and secondary vortices, showing excellent agreement with benchmark data at moderate Reynolds numbers. Notably, HSLBM exhibits superior numerical stability at elevated Reynolds numbers and requires less memory than MRT-LBM. Our comparative analysis reveals that HSLBM achieves accuracy comparable to MRT-LBM while providing enhanced stability and computational efficiency. These findings offer valuable insights into the relative performance and practical applicability of these methods for internal flow simulations.