Fluid flow and heat transfer in microchannel heat sinks: Modelling review and recent progress

• Published in: Thermal science and engineering progress Vol. 29; p. 101203
• Main Authors: Gao, Jie, Hu, Zhuohuan, Yang, Qiguo, Liang, Xing, Wu, Hongwei
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2022
• Subjects: Boiling; Computational fluid dynamics; Genetic algorithm; Heat transfer; Helical coils; lattice Boltzmann methods; Molecular dynamics simulation; Neural network; Taguchi algorithm; Terrestrial gravity; Taguchi algorithm; Computational fluid dynamics; Genetic algorithm; lattice Boltzmann methods; Neural network; Molecular dynamics simulation; Boiling; Heat transfer; Terrestrial gravity; Helical coils
• ISSN: 2451-9049; 2451-9049
• DOI: 10.1016/j.tsep.2022.101203

•The conventional CFD method in microchannel is critically reviewed.•The advantages and disadvantages of CFD in microchannel are analyzed.•The application of LBM, MDS and DSMC are discussedin detail.•Three optimisationand prediction methodsin microchannels are compared.•The optimization principles of TM, GA and ANN are analyzedand discussed. Nowadays, microchannels have been widely utilized in various multidisciplinary fields, and as a consequence, some new and different requirements for microchannels in the process of practical application are required, such as structure, working fluid, and operating conditions, etc. This article reviews the current research achievement of microchannels, as well as the thermodynamic research on microchannels with different structures in the past five years, but mainly focuses on the numerical methods. The purpose of this review article aims to summarize a comprehensive overview of the latest developments of numerical methods in microchannel heat sinks, as well as to provide a useful benchmark for future research. The present article reviews straightforward on the most commonly used numerical methods for solving governing equations and optimizing data, including conventional computational fluid dynamics (CFD) simulation methods, molecular dynamics simulation (MDS), Lattice Boltzmann methods (LBM), direct simulation Monte Carlo (DSMC), and other techniques such as machine learning (ML) approach, artificial neural network (ANN) method, genetic algorithm (GA), Taguchi algorithm (TA), as well as optimisation methods. This review will not only help to understand the physical mechanism of microchannels in different application fields but also help to fill in the gaps in related research and provide research methods for future numerical studies.