Predictive Large‐Eddy Simulation of Jet Fuel Atomization, High‐Lift Airframes, and Reacting Supersonic Turbulent Flows on Unstructured Grids

PI Name: 
Parviz Moin
PI Email: 
moin@stanford.edu
Institution: 
Stanford University
Allocation Program: 
ALCC
Allocation Hours at ALCF: 
120 Million
Year: 
2014
Research Domain: 
Engineering

Accurate predictive modeling is crucial in the design of energy‐efficient and environmentally friendly engineering systems, including aircraft propulsion and land-based power generation. High‐fidelity, unstructured large eddy simulation (LES) is emerging as an accurate yet cost-effective computational tool for prediction of several key aircraft components. Combining recent advances in LES modeling with our highly scalable, unstructured code CharLES, predictive LES of real aircraft geometries at flight Reynolds number is possible using today’s leadership-class computers. Three high‐risk, high‐payoff simulations are examined that leverage the CharLES codebase to significantly advance the state‐of‐the‐art in LES technology for (1) liquid jet atomization, (2) wall modeling and control of turbulent boundary layers, and (3) supersonic turbulent combustion flamelet modeling for hypersonic flight. This project aims to demonstrate that LES of complex geometries at flight Reynolds numbers is possible with today’s large‐scale computers, which is a crucial step towards extended use of LES in transportation and power industries.