Numerical approach to enhance solidification by incorporating hybrid nanoparticles and employing porous foam

Cold energy storage units using PCM (phase change material) are crucial in applications such as cryogenic cooling, refrigeration, and energy-efficient building design. However, the slow solidification rate of conventional PCMs limits their performance. This study presents a numerical investigation aimed at accelerating the freezing process of water by simultaneously employing porous foam, radial fins, and hybrid nanoparticles, along with the effect of radiative heat transfer. A hybrid nanofluid composed of water and mixed nano-powders is introduced to improve thermal conductivity, while the inclusion of porous media enhances heat extraction. The governing equations are solved applying the Galerkin finite element approach, with adaptive meshing to accurately capture the transient freezing front. Radiation effects are modeled using the Rosseland approximation to reflect realistic thermal behavior. Validation is performed by comparing the numerical model against established experimental benchmarks. Outputs indicated that the use of hybrid nano-powders alone reduces freezing time by 6.62%, while radiation cooling (without porous foam) further reduces it by 13.83%. The most substantial enhancement occurs with the inclusion of porous foam, leading to an 80.6% reduction in freezing time. These findings confirm the synergistic effect of porous structures, nanoparticle enhancement, and radiative cooling, offering a novel cold energy storage systems.

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Publication Details

Journal
Case Studies in Thermal Engineering
Published
2025-06-09
DOI
https://doi.org/10.1016/j.csite.2025.106489
Citations
4
Primary Topic
Pickering emulsions and particle stabilization
Type
article
Field-Weighted Citation Impact
2.07

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article

Numerical approach to enhance solidification by incorporating hybrid nanoparticles and employing porous foam

Walid Aich, Hussein A.Z. AL-bonsrulah, Abd Elmotaleb A.M.A. Elamin, Moaz Al‐lehaibi et al.
4 citations
Case Studies in Thermal Engineering
Pickering emulsions and particle stabilization
2.07
article

Numerical approach to enhance solidification by incorporating hybrid nanoparticles and employing porous foam

Walid Aich, Hussein A.Z. AL-bonsrulah, Abd Elmotaleb A.M.A. Elamin, Moaz Al‐lehaibi, Ali Basem, Lotfi Ben Said, Mohammed A. Tashkandi, Lioua Kolsi
article en
4 citations

Abstract

Cold energy storage units using PCM (phase change material) are crucial in applications such as cryogenic cooling, refrigeration, and energy-efficient building design. However, the slow solidification rate of conventional PCMs limits their performance. This study presents a numerical investigation aimed at accelerating the freezing process of water by simultaneously employing porous foam, radial fins, and hybrid nanoparticles, along with the effect of radiative heat transfer. A hybrid nanofluid composed of water and mixed nano-powders is introduced to improve thermal conductivity, while the inclusion of porous media enhances heat extraction. The governing equations are solved applying the Galerkin finite element approach, with adaptive meshing to accurately capture the transient freezing front. Radiation effects are modeled using the Rosseland approximation to reflect realistic thermal behavior. Validation is performed by comparing the numerical model against established experimental benchmarks. Outputs indicated that the use of hybrid nano-powders alone reduces freezing time by 6.62%, while radiation cooling (without porous foam) further reduces it by 13.83%. The most substantial enhancement occurs with the inclusion of porous foam, leading to an 80.6% reduction in freezing time. These findings confirm the synergistic effect of porous structures, nanoparticle enhancement, and radiative cooling, offering a novel cold energy storage systems.

Case Studies in Thermal EngineeringVol. 73
Northern Border University (SA), Prince Sattam Bin Abdulaziz University (SA), Umm al-Qura University (SA), University of Ha'il (SA), University of Kerbala (IQ), University of Warith Al-Anbiyaa
Northern Border University
Openalex Percentile: Top 13%
Pickering emulsions and particle stabilization
2.07
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