Machine Learning Award Powers Engine Design at Argonne

With the help of ALCF supercomputing resources, researchers are refining their computational fluid dynamics (CFD) simulations to better capture the real-world behavior of combustion engines. As part of a partnership between the Argonne National Lab, Convergent Science, and Parallel Works, engine modelers are beginning to use machine learning algorithms and artificial intelligence to optimize their simulations. Now, this alliance recently received a Technology Commercialization Fund award from the DOE to complete this important project.

Publication Name: 
insideHPC
Date Published: 
Friday, January 4, 2019