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

Madruga Sánchez, Santiago ORCID: https://orcid.org/0000-0002-9996-1287 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.

Descripción

Título: Melting dynamics of a phase change material (PCM) with dispersed metallic nanoparticles using transport coefficients from empirical and mean field models
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: Applied Thermal Engineering
Fecha: Julio 2017
ISSN: 1359-4311
Volumen: 124
Materias:
ODS:
Palabras Clave Informales: Nanofluid; PCM; Convection; Nanoparticles
Escuela: E.T.S. de Ingeniería Aeronáutica y del Espacio (UPM)
Departamento: Matemática Aplicada a la Ingeniería Aeroespacial
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

Texto completo

[thumbnail of INVEMEM_2017_271043.pdf]
Vista Previa
PDF (Portable Document Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (3MB) | Vista Previa

Resumen

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).

Proyectos asociados

Tipo
Código
Acrónimo
Responsable
Título
Gobierno de España
TRA2016-75075
Sin especificar
Sin especificar
Sin especificar
Gobierno de España
ESP2013-45432-P
Sin especificar
Sin especificar
Sin especificar
Gobierno de España
ESP2015-70458-P
Sin especificar
Sin especificar
Sin especificar

Más información

ID de Registro: 50189
Identificador DC: https://oa.upm.es/50189/
Identificador OAI: oai:oa.upm.es:50189
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/5495717
Identificador DOI: 10.1016/j.applthermaleng.2017.06.097
URL Oficial: https://www.sciencedirect.com/science/article/pii/...
Depositado por: Memoria Investigacion
Depositado el: 02 Ago 2018 10:44
Ultima Modificación: 12 Nov 2025 00:00