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Heat transfer modelling in Discrete Element Method (DEM)-based simulations of thermal processes: Theory and model development

Journal

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pecs.2020.100847

Keywords

Thermal DEM; Heat transfer modelling; CFD; Particulate flow; Thermal processes; Thermal models

Funding

  1. Australian Coal Industry's Research Program (ACARP) [C26004]

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Over the past decade, DEM-based simulation has become a promising alternative to physical measurements of thermal particulate systems. Despite their rapid advancement and successful applications to a wide range of industrial processes, a comprehensive review of the theory that underpins the thermal DEM-based simulations is yet to be conducted. This work presents a critical and in-depth review of all major thermal models and heat transfer mechanisms pertinent to DEM-based simulations. Other critical aspects such as boundary conditions and particle body temperature distribution that were often overlooked are also summarised and discussed, aiming to provide a clear path for the development of robust thermal DEM-based models. The quasi-analytical solution based on the Hertzian contact theory proves classic and remains the main method to solving the conduction of static contacts. Recent attempts have been mainly directed towards improving the calculation of conduction through collisional contacts and the thin wedge of interstitial fluid between particles. Empirical correlations that were developed before 1981 remain predominant in calculating the fluid-particle convection coefficient. Though more accurate, the discrete models of radiation that rely on the solution of view factors amongst individual particles have been applied much less than the continuum models due to the significant computational overhead. Generally, previous efforts have led to the construction of a solid framework of thermal DEM-based models. Significant work is required to improve existing or develop new heat transfer sub-models, particularly those for accurate and efficient modelling of conduction and radiation in particle-laden systems. (C) 2020 Elsevier Ltd. All rights reserved.

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