Melting dynamics of a phase change material (PCM) with dispersed metallic nanoparticles using transport coefficients from empirical and mean field models

Madruga Sanchez, Santiago and Mischlich, Gonzalo S. (2017). Melting dynamics of a phase change material (PCM) with dispersed metallic nanoparticles using transport coefficients from empirical and mean field models. "Applied Thermal Engineering", v. 124 ; pp. 1123-1133. ISSN 1359-4311. https://doi.org/10.1016/j.applthermaleng.2017.06.097.

Description

Title: Melting dynamics of a phase change material (PCM) with dispersed metallic nanoparticles using transport coefficients from empirical and mean field models
Author/s:
  • Madruga Sanchez, Santiago
  • Mischlich, Gonzalo S.
Item Type: Article
Título de Revista/Publicación: Applied Thermal Engineering
Date: July 2017
Volume: 124
Subjects:
Freetext Keywords: Nanofluid; PCM; Convection; Nanoparticles
Faculty: E.T.S. de Ingeniería Aeronáutica y del Espacio (UPM)
Department: Matemática Aplicada a la Ingeniería Aeroespacial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

We study the melting process of n-octadecane with dispersed Al2O3 nanoparticles in a semicircle. The effective transport coefficients of the resulting nanofluid are modeled with (i) mean field models due to Maxwell-Garnett for the conductivity and Brinkmann for viscosity, and (ii) an empirical model based on a least square fit to experimental data due to Corcione (2011). In both cases, we consider a uniform nanoparticle distribution in the liquid and solid phases and incorporate as well the change of conductivity in the latter phase. We carry out simulations with the transport coefficients predicted by both models and find that Maxwell & Brinkmann overestimates heat transfer rates compared to the empirical fit for most of the ranges of nanoparticle concentration, size, and temperature. However, the proper selection of nanoparticles attending to their size and temperature can lead to enhanced heat transfer, even beyond of mean field model predictions. We show how the effective Prandtl number is the single most important parameter that determines the dynamics and duration of the melting process, and how predictions of our simulations agree with recent experiments (Ho and Gao, 2009).

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTRA2016-75075UnspecifiedUnspecifiedUnspecified
Government of SpainESP2013-45432-PUnspecifiedUnspecifiedUnspecified
Government of SpainESP2015-70458-PUnspecifiedUnspecifiedUnspecified

More information

Item ID: 50189
DC Identifier: http://oa.upm.es/50189/
OAI Identifier: oai:oa.upm.es:50189
DOI: 10.1016/j.applthermaleng.2017.06.097
Official URL: https://www.sciencedirect.com/science/article/pii/S1359431116320026?via%3Dihub
Deposited by: Memoria Investigacion
Deposited on: 02 Aug 2018 10:44
Last Modified: 01 Oct 2018 22:30
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