A hybrid meshing framework adapted to the topography to simulate Atmospheric Boundary Layer flows

TL;DR

This paper introduces a fully automatic, topography-adapted meshing framework for simulating Atmospheric Boundary Layer flows on complex terrains, improving accuracy and efficiency through adaptive meshing and hybrid quality optimization.

Contribution

It presents a novel adaptive meshing process tailored for complex terrains, including a hybrid quality optimization approach and convergence analysis for ABL flow simulations.

Findings

Quadratic convergence to geometry with adaptive meshing.

Reduced error by 50% compared to non-adaptive methods.

Achieved 20% error reduction with 30% fewer degrees of freedom.

Abstract

A new topography adapted mesh generation process tailored to simulate Atmospheric Boundary Layer (ABL) flows on complex terrains is presented. The mesher is fully automatic given: the maximum and minimum surface mesh size, the size of the first element of the boundary layer, the maximum size in the boundary layer and the size at the top of the domain. The following contributions to the meshing workflow for ABL flow simulation are performed. First, we present a smooth topography modeling to query first and second order geometry derivatives. Second, we propose a new adaptive meshing procedure to discretize the topography based on two different metrics. Third, the ABL mesher is presented, featuring both prisms and tetrahedra. We extrude the triangles of the adapted surface mesh, generating prisms that reproduce the Surface Boundary Layer. Then, the rest of the domain is meshed with an unstructured tetrahedral mesh. In addition, for both the surface and volume meshers we detail a hybrid quality optimization approach, analyzing its impact on the solver for high-complexity terrains. We analyze the convergence of the triangle adaptive approach, obtaining quadratic convergence to the geometry and reducing to one half the error for the same amount of degrees of freedom than without adaptivity and optimization. We also study the mesh convergence of our RANS solver, obtaining quadratic mesh convergence to the solution, and using a 30% of the degrees of freedom while reducing a 20% of the error of standard semi-structured approaches. Finally, we present the generated meshes and the simulation results for a complete complex topographic scenario.