Development of a Sustainable Universal Python Code for Accurate 2D Heat Transfer Conduction Simulations in Educational Environment

Simulation software like ANSYS, COMSOL, and SimScale excel at modeling heat transfer phenomena, but their extensive functionalities necessitate a deep understanding, making them less suitable and too expensive for use in educational settings below the post-secondary level in Singapore, where the current curriculum does not demand such advanced capabilities. To provide a more accessible and cost-effective solution, this work introduces a novel universal Python code designed to simplify the understanding of 2D steady-state heat transfer on irregular shapes, utilizing only Microsoft Excel and Python. The developed code employs the Gauss–Seidel iteration method within a full multigrid framework, applying the relevant nodal finite-difference equations based on the node type within a 2D irregular shape delineated by a 65 × 65 mesh in Excel. The generated contour plots from these simulations are meticulously compared with those produced by ANSYS to validate accuracy. The comparison reveals that the results from the Python code closely align with those from ANSYS, showing only minor differences. Consequently, the Python code emerges as a viable and simplified alternative for conducting 2D steady-state heat transfer simulations, making it a valuable tool for educational purposes, bridging the gap between complex simulation software and the educational needs of students in Singapore.

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Publication Details

Journal
Applied Sciences
Published
2024-08-15
DOI
https://doi.org/10.3390/app14167159
Citations
3
Primary Topic
Heat Transfer and Optimization
Type
article
Field-Weighted Citation Impact
0.64
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article

Development of a Sustainable Universal Python Code for Accurate 2D Heat Transfer Conduction Simulations in Educational Environment

Chiang Liang Kok, Yit Yan Koh, Tee Hui Teo, Chee Kit Ho et al.
3 citations
Applied Sciences
Heat Transfer and Optimization
0.64
article

Development of a Sustainable Universal Python Code for Accurate 2D Heat Transfer Conduction Simulations in Educational Environment

Chiang Liang Kok, Yit Yan Koh, Tee Hui Teo, Chee Kit Ho, Abbas Syihan Bin Muhammad Taufik
article en
3 citations

Abstract

Simulation software like ANSYS, COMSOL, and SimScale excel at modeling heat transfer phenomena, but their extensive functionalities necessitate a deep understanding, making them less suitable and too expensive for use in educational settings below the post-secondary level in Singapore, where the current curriculum does not demand such advanced capabilities. To provide a more accessible and cost-effective solution, this work introduces a novel universal Python code designed to simplify the understanding of 2D steady-state heat transfer on irregular shapes, utilizing only Microsoft Excel and Python. The developed code employs the Gauss–Seidel iteration method within a full multigrid framework, applying the relevant nodal finite-difference equations based on the node type within a 2D irregular shape delineated by a 65 × 65 mesh in Excel. The generated contour plots from these simulations are meticulously compared with those produced by ANSYS to validate accuracy. The comparison reveals that the results from the Python code closely align with those from ANSYS, showing only minor differences. Consequently, the Python code emerges as a viable and simplified alternative for conducting 2D steady-state heat transfer simulations, making it a valuable tool for educational purposes, bridging the gap between complex simulation software and the educational needs of students in Singapore.

Applied SciencesVol. 14(16)
Singapore University of Technology and Design (SG), Singapore Institute of Technology (SG), University of Newcastle Australia (AU)
Quality Education
Openalex Percentile: Top 36%
Heat Transfer and Optimization
0.64
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Development of a Sustainable Universal Python Code for Accurate 2D Heat Transfer Conduction Simulations in Educational Environment — Chiang Liang Kok, Yit Yan Koh, et al. · Applied Sciences (2024) | TGRS Research Map | TGRS