Data Analytics and Machine Learning for Exascale Computational Fluid Dynamics

PI Ken Jansen, University of Colorado Boulder
Jansen Aurora ESP

Flow over a vertical tail/rudder assembly (grey surface) with 24 active synthetic jets which introduce vortical structures (visualized by isosurfaces of vorticity colored by local flow speed) that alter the flow, reducing separation, improving rudder performance, and thereby allowing future aircraft designs to lower drag and fuel consumption. Image: Jun Fang, Argonne National Laboratory

Project Description

This project will develop data analytics and machine learning techniques to greatly enhance the value of flow simulations with the extraction of meaningful dynamics information. A hierarchy of turbulence models will be applied to a series of increasingly complex flows before culminating in the first flight-scale design optimization of active flow control on an aircraft’s vertical tail.

Project Type
Allocations