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20242026
most citedPhysics-Based Hybrid Machine Learning for Critical Heat Flux Prediction with Uncertainty Quantification

14 citations · 16 across the 7 of their papers we have counts for

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cs.LG2026

Assessment of Machine Learning-Based Critical Heat Flux Models in the CTF Subchannel Code for Square Rod Bundle Prediction

Aidan Furlong, Vinicius de Melo Monteiro, Robert Salko +2

The prediction of critical heat flux (CHF), a key safety-related quantity in nuclear thermal hydraulics, remains an important challenge due to its direct relationship with fuel per…

cs.LG2026

Prediction of Critical Heat Flux in Rod Bundles Using Tube-Based Hybrid Machine Learning Models in CTF

Aidan Furlong, Robert Salko, Xingang Zhao +1

The prediction of critical heat flux (CHF) using machine learning (ML) approaches has become a highly active research activity in recent years, the goal of which is to build models…