Fluid Flow and Heat Transfer in Microchannel Heat Sinks: Modelling review and recent progress

Jie Gao, Zhuohuan Hu, Qiguo Yang, Xing Liang, Hongwei Wu

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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.
Original languageEnglish
Article number101203
Number of pages17
JournalThermal Science and Engineering Progress
Early online date13 Jan 2022
Publication statusPublished - 1 Mar 2022


  • Boiling
  • Computational fluid dynamics
  • Genetic algorithm
  • Heat transfer
  • Helical coils
  • Molecular dynamics simulation
  • Neural network
  • Taguchi algorithm
  • Terrestrial gravity
  • lattice Boltzmann methods


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