Machine Learning and Artificial Intelligence for T/H: I

Machine-Learning-Aided Approach for Predicting the Thermal Expansion Behaviors in Advanced Test Reactor Capsules

9:00–9:20AM EDT

Takanori Kajihara (INL), Han Bao (INL), Nicolas E. Woolstenhulme (INL), Colby B. Jensen (INL), Daniel B. Chapman (INL), Sunming Qin (INL), Austin D. Fleming (INL)

Investigation of Machine Learning Regression Techniques to Predict Critical Heat Flux over a Large Parameter Space

9:20–9:40AM EDT

Emil Helmryd Grosfilley (Uppsala Univ.), Gustav Robertson (Uppsala Univ.), Jerol Soibam (Mälardalen Univ.), Jean-Marie Le Corre (Westinghouse Electric Sweden)

Using Machine Learning to Assess Spill Fire Data for use in Fire PRA

9:40–10:00AM EDT

Elvan Sahin (Virginia Tech), Mehran Islam (Virginia Tech), Brian Y. Lattimer (Virginia Tech), Juliana P. Duarte (Univ. Wisconsin, Madison)

Machine Learning from LES Data to Improve Coarse Grid RANS Simulations

10:00–10:20AM EDT

Arsen S. Iskhakov (NCSU), Taylor Grubbs (NCSU), Nam T. Dinh (NCSU), Victor Coppo Leite (Penn State), Elia Merzari (Penn State)