NAISS
SUPR
NAISS Projects
SUPR
LESisMORE
Dnr:

NAISS 2025/23-658

Type:

NAISS Small Storage

Principal Investigator:

Mohammed Kassem

Affiliation:

Chalmers tekniska högskola

Start Date:

2025-11-13

End Date:

2026-07-01

Primary Classification:

20306: Fluid Mechanics

Webpage:

Allocation

Abstract

The project will focus on novel and efficient wall modeling approaches for LES. Machine learning methods will be applied in combination with first principal methods with the aim to achieve an accurate, robust and efficient wall modelled (WM) LES capability. the large efficiency potential of accelerating LES-based simulations using graphics processing units (GPU) will be explored top support WMLES on large-scale aeronautical applications. Moreover, efforts on improving spatial and temporal accuracy for fully unstructured grids will be made to support accurately LES resolved turbulence for industrial applications.