NEUP CINR-23-29708: Optimizing Application-Dependent Energy Group Structures for Multigroup Neutron Transport Models using Machine Learning

We will develop Machine Learning methods that will dramatically reduce both the computational run-time and manual effort needed to find multigroup energy structures that accurately capture the underlying physics of neutron reactions while allowing multigroup simulations to run quickly without overwhelming available memory.

Additional Info

Field	Value
Awarded Institution	Colorado School of Mines
PI	Andrew Osborne