Simulation and Experimental Study on Thermal Conductivity of Nano-Granule Porous Material Based on Lattice-Boltzmann Method

Nano-porous materials have excellent thermal insulation performance, whose microstructure and physical properties, however, have great influence on the thermal conductivity. To accurately describe the stochastic phase distribution, a random internal morphology and structure generation-growth method,...

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Bibliographic Details
Published in:	Journal of thermal science Vol. 30; no. 1; pp. 248 - 256
Main Authors:	Kan, Ankang, Mao, Shang, Wang, Ning, Shi, Bingling
Format:	Journal Article
Language:	English
Published:	Heidelberg Science Press 2021 Springer Nature B.V
Subjects:	Algorithms Classical and Continuum Physics Density Engineering Fluid Dynamics Engineering Thermodynamics Granular materials Heat and Mass Transfer Heat conductivity Heat transfer Mathematical morphology Microstructure Model accuracy Phase distribution Physical properties Physics Physics and Astronomy Pore size Porosity Porous materials Porous media Pressure effects Stress concentration Thermal conductivity Thermal insulation effective thermal conductivity physics model aerogel Lattice-Boltzmann method mesoscopic scale
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Summary:	Nano-porous materials have excellent thermal insulation performance, whose microstructure and physical properties, however, have great influence on the thermal conductivity. To accurately describe the stochastic phase distribution, a random internal morphology and structure generation-growth method, called the quartet structure generation set (QSGS), has been proposed in the present paper. The model was then imported into lattice Boltzmann algorithm as a fully resolved geometry and used to investigate the effects on heat transfer at the nanoscale. Furthermore, a three-dimensional Lattice Boltzmann method (LBM) D3Q15 was adopted to predict the nano-granule porous material effective thermal conductivity. This ideal method provided a significant advantage over similar porous media methods by directly controlling and adjusting of granule characteristics such as granule size, porosity and pore size distributions and studying their influence directly on thermal conductivity. To verify the accuracy of the proposed model, some experiments based on guarded hot plate meter (GHPM) were conducted. The results indicated that the simulation results agreed well with the experimental data and references values, which illustrated that this method was reliable to generate the microstructure of nano-granule. What’s more, the effects of pressure, core distribution probability, cd and density were investigated. There existed an optimal density (about 120 kg·m -3 ) making the effective thermal conductivity being minimum and an optimal core distribution probability about c d =0.1 making the uniformity being the best. In addition, the present approach is applicable in dealing with other porous materials as well.
ISSN:	1003-2169 1993-033X
DOI:	10.1007/s11630-019-1218-1