Robust Cartesian Grid Flow Solver for High-Reynolds-Number Turbulent Flow Simulations

Abstract

A novel, Cartesian-grid-based flow solver is developed for predicting complex high-Reynolds-number turbulent flowfields. The Cartesian grid generator is based on the cut-cell approach using cell merge and Cartesian layer techniques. Cartesian layers imitate the structured grid approach in which the mesh is stretched gradually. Local refinement is added based on local surface curvature. As a turbulence closure model, the two equation k–!-TNT turbulencemodel is successfully implemented using an unconditionally positive-convergent implicit time integration scheme. The overall flow solver’s robustness and accuracy are verified using three challenging test cases. The numerical results convincingly demonstrate the robustness and accuracy of the flow solver, especially in predicting aerodynamic forces.