In-core Temperature Forecasting by Random Forest Modeling in Extreme Harsh Environment

Abstract

This paper proposed accurate in-core distributed temperature predictions by random forest modeling based on optical measurements. The prediction error is within 3.6% of the temperature swing in the extremely harsh environment.