An Optimizer Using the PSO Algorithm to Determine Thermal Parameters of PCM: A case study of grey water heat harnessing

Abdur Rehman Mazhar; Shuli Liu; Ashish Shukla

doi:10.1016/j.ijheatmasstransfer.2019.118574

An Optimizer Using the PSO Algorithm to Determine Thermal Parameters of PCM: A case study of grey water heat harnessing

Abdur Rehman Mazhar, Shuli Liu, Ashish Shukla

Research output: Contribution to journal › Article › peer-review

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Abstract

The melting and freezing of Phase Change Materials (PCMs) is categorized as a moving boundary problem. For this reason the mathematical solution to study the behaviour of practical applications is only possible via complex numerical approximations. However for a preliminary design the main concern is to select the optimum thermal characteristics of the PCM storage unit, for both melting and freezing. This is to be done before the detailed design by integrating an optimization algorithm with a numerical simulation. The application of using PCMs to harness the waste heat from non-industrial grey water is investigated as a case of study. For this purpose, the 2-phase analytical solution to the Stefan problem is coupled with the particle swarm optimizer (PSO) to find the best combination of thermal characteristics within the prescribed boundary conditions of this case study. Results show that the optimum phase change temperature lies between 20 and 22 °C, depending on various sets of input parameters. At the same time the ratio of latent to sensible heat transferred by the PCM highly influences this optimum temperature for the combination of both melting and freezing. Similarly results show melting being faster and more intensive in term of latent heat charging compared to a higher sensible heat discharging while freezing.

Original language	English
Article number	118574
Journal	International Journal of Heat and Mass Transfer
Volume	144
Early online date	3 Sept 2019
DOIs	https://doi.org/10.1016/j.ijheatmasstransfer.2019.118574
Publication status	Published - Dec 2019

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in International Journal of Heat and Mass Transfer. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Heat and Mass Transfer [144, (2019)] DOI: 10.1016/j.ijheatmasstransfer.2019.118574

© 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/10.1016/j.ijheatmasstransfer.2019.118574

Keywords

Neumann solution
Particle swarm optimization
Phase change materials
Stefan problem
Thermal characteristics

ASJC Scopus subject areas

Condensed Matter Physics
Mechanical Engineering
Fluid Flow and Transfer Processes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.ijheatmasstransfer.2019.118574

Post-PrintAccepted author manuscript, 1.72 MBLicence: CC BY-NC-ND

Cite this

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abstract = "The melting and freezing of Phase Change Materials (PCMs) is categorized as a moving boundary problem. For this reason the mathematical solution to study the behaviour of practical applications is only possible via complex numerical approximations. However for a preliminary design the main concern is to select the optimum thermal characteristics of the PCM storage unit, for both melting and freezing. This is to be done before the detailed design by integrating an optimization algorithm with a numerical simulation. The application of using PCMs to harness the waste heat from non-industrial grey water is investigated as a case of study. For this purpose, the 2-phase analytical solution to the Stefan problem is coupled with the particle swarm optimizer (PSO) to find the best combination of thermal characteristics within the prescribed boundary conditions of this case study. Results show that the optimum phase change temperature lies between 20 and 22 °C, depending on various sets of input parameters. At the same time the ratio of latent to sensible heat transferred by the PCM highly influences this optimum temperature for the combination of both melting and freezing. Similarly results show melting being faster and more intensive in term of latent heat charging compared to a higher sensible heat discharging while freezing.",

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An Optimizer Using the PSO Algorithm to Determine Thermal Parameters of PCM: A case study of grey water heat harnessing

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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