Resilient Machine Learning: Advancement, Barriers, and Opportunities in the Nuclear Industry
The widespread adoption and success of Machine Learning (ML) technologies depend on
thorough testing of the resilience and robustness to adversarial attacks. The testing should …
thorough testing of the resilience and robustness to adversarial attacks. The testing should …
Enhancing accuracy of prediction of critical heat flux in Circular channels by ensemble of deep sparse autoencoders and deep neural Networks
Abstract Accurate prediction of Critical Heat Flux (CHF) is essential for ensuring safety and
economic efficiency of water-cooled reactors and two-phase flow boiling heat transfer …
economic efficiency of water-cooled reactors and two-phase flow boiling heat transfer …
Analyzing the effects of various isotropic and anisotropic kernels on critical heat flux prediction using Gaussian process regression
The critical heat flux (CHF) is an important parameter determining the heat transfer capability
of nuclear reactors. Therefore, prediction of CHF with accuracy and correct understanding is …
of nuclear reactors. Therefore, prediction of CHF with accuracy and correct understanding is …
Comparison of standalone and hybrid machine learning models for prediction of critical heat flux in vertical tubes
Critical heat flux (CHF) is an essential parameter that plays a significant role in ensuring the
safety and economic efficiency of nuclear power facilities. It imposes design and operational …
safety and economic efficiency of nuclear power facilities. It imposes design and operational …
Dependence of critical heat flux in vertical flow systems on dimensional and dimensionless parameters using machine learning
The critical heat flux (CHF) associated with the departure from nucleate boiling (DNB)
determines the design and safety aspects of two-phase flow boiling systems. Despite the …
determines the design and safety aspects of two-phase flow boiling systems. Despite the …
[HTML][HTML] Re-examining the input-parameters and AI strategies for Critical Heat Flux prediction
K Wang, D Wang, X Liu, S Cheng, S Wang, W Zhou… - Energy, 2025 - Elsevier
This study employed three deep-learning models to predict CHF, with Transformers
outperforming the other methods, thereby solidifying its leading position. The research re …
outperforming the other methods, thereby solidifying its leading position. The research re …
Hybrid Deep Convolutional Neural Networks Combined with Autoencoders and Augmented Data to Predict the Look-Up Table 2006
Lookup tables derived from empirical research contain limited data for critical heat flux
(CHF). Machine learning techniques can be employed to create CHF prediction models by …
(CHF). Machine learning techniques can be employed to create CHF prediction models by …
Prediction of Condensation Heat Transfer of Passive Cooling Systems in Nuclear Power Plants through Machine Learning
The accurate prediction of steam-air mixture condensation plays crucial role in managing
severe accidents such as main steam line break (MSLB) and loss of coolant accident …
severe accidents such as main steam line break (MSLB) and loss of coolant accident …
An Optimized Stacking Ensemble Learning Model Using 3-Pyramids Technique for the 2006 CHF Groeneveld Look Table Prediction
Typically, critical heat flux (CHF) look-up tables constructed based on physical experiments
have limited data. Using available experimental-based CHF look-up tables as training data …
have limited data. Using available experimental-based CHF look-up tables as training data …
[PDF][PDF] Comparative Analysis of Machine Learning Approaches for Boiling ONB Prediction
A Cabarcos, C Paz, M Concheiro, M Conde-Fontenla… - avestia.com
This study investigates the use of Machine Learning models for predicting both wall
temperature and heat flux at the Onset of Nucleate Boiling (ONB). The dataset used in this …
temperature and heat flux at the Onset of Nucleate Boiling (ONB). The dataset used in this …