NEUP CINR-20-19066: Engineering-Informed, Data-Driven Degradation Modeling, Prognostics and Control for Radiation-induced Void Swelling in Reactor Steels

The goal of this research is to advance the capability to model, predict and control void swelling in irradiated structural components through developing engineering-informed, advanced data-driven statistical and machine learning techniques. Excess swelling not only leads to dimensional instability, but also can cause severe embrittlement of internal materials. The proposed efforts will ensure more effective safety regulation, aging management and license renewal.

Additional Info

Field	Value
Awarded Institution	University of Wisconsin-Madison
PI	Kaibo Liu