Machine learning driven metaheuristics to optimize the design-operational parameters for enhanced pool boiling CHF subject to a range of surface-liquid combinations

• Published in: International journal of heat and mass transfer Vol. 252; p. 127510
• Main Authors: Sajjad, Uzair, Mehdi, Sadaf, Zaidi, Syed Shoaib Hassan, Ali, Hafiz Muhammad
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2025
• Subjects: Boiling crisis; Genetic algorithm; Machine learning; Pool boiling heat transfer; Roughened surfaces; CHF; ANN; XAI; Roughened surfaces; DNN; MAE; R; Boiling crisis; Genetic algorithm; HTC; Machine learning; GA; PINN; Pool boiling heat transfer; ML

•CHF is accurately predicted using DNN.•An inverse approach is adopted from CHF to identifying optimal design parameters.•New Genetic Algorithm-based model is developed.•Genetic Algorithm-based model reveals CHF trend for different fluids. Critical heat flux (CHF) is crucial for heat-flux controlled...