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Data-driven methods for heat transfer and fluid flow

Guest editorial: Data-driven methods for heat transfer and fluid flow

R.S. Ransing
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Two-phase flow regime identification using multi-method feature extraction and explainable kernel Fisher discriminant analysis

Umair Khan; William Pao; Karl Ezra Salgado Pilario; Nabihah Sallih; Muhammad Rehan Khan
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Prediction of multi-physics field distribution on gas turbine endwall using an optimized surrogate model with various deep learning frames

Weixin Zhang; Zhao Liu; Yu Song; Yixuan Lu; Zhenping Feng
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Swirl-induced motion prediction with physics-guided machine learning utilizing spatiotemporal flow field structure

Ziming Zhou; Fengnian Zhao; David Hung
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Deep learning algorithms for temperature prediction in two-phase immersion-cooled data centres

Pratheek Suresh; Balaji Chakravarthy
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Permeability estimation for deformable porous media with convolutional neural network

Kunpeng Shi; Guodong Jin; Weichao Yan; Huilin Xing
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Investigating embedded data distribution strategy on reconstruction accuracy of flow field around the crosswind-affected train based on physics-informed neural networks

Guang-Zhi Zeng; Zheng-Wei Chen; Yi-Qing Ni; En-Ze Rui
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Turbo-RANS: straightforward and efficient Bayesian optimization of turbulence model coefficients

Ryley McConkey; Nikhila Kalia; Eugene Yee; Fue-Sang Lien
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A neural based modeling approach for predicting effective thermal conductivity of brewer’s spent grain

Amanda de Oliveira e Silva; Alice Leonel; Maisa Tonon Bitti Perazzini; Hugo Perazzini
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Artificial intelligence-based droplet size prediction for microfluidic system

Sameer Dubey; Pradeep Vishwakarma; TVS Ramarao; Satish Kumar Dubey; Sanket Goel; Arshad Javed
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Prediction of the minimum fluidization velocity of different biomass types by artificial neural networks and empirical correlations

Thenysson Matos; Maisa Tonon Bitti Perazzini; Hugo Perazzini
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An artificial intelligence approach for the estimation of conduction heat transfer using deep neural networks

Mohammad Edalatifar; Jana Shafi; Majdi Khalid; Manuel Baro; Mikhail A. Sheremet; Mohammad Ghalambaz
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Physics-informed neural networks (P INNs): application categories, trends and impact

Mohammad Ghalambaz; Mikhail A. Sheremet; Mohammed Arshad Khan; Zehba Raizah; Jana Shafi
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Data-driven wall modeling for LES involving non-equilibrium boundary layer effects

Sarath Radhakrishnan; Joan Calafell; Arnau Miró; Bernat Font; Oriol Lehmkuhl
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Physically consistent temperature fields for geophysical inversion based on the parametrized location of an isotherm

Mariano Tomás Fernandez; Sergio Zlotnik; Pedro Diez
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Reinforcement learning for cooling rate control during quenching

Elie Hachem; Abhijeet Vishwasrao; Maxime Renault; Jonathan Viquerat; P. Meliga
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Flow control by a hybrid use of machine learning and control theory

Takeru Ishize; Hiroshi Omichi; Koji Fukagata
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