Romero, German et Lombana, Mauricio.
2025.
« Development of a Python-based BEM software for multi-physical analysis and development of energy ».
In Proceedings of the CSME-CFDSC-CSR 2025 International Congress (Montreal, QC, Canada, May 25-28, 2025)
Coll. « Progress in Canadian Mechanical Engineering », vol. 8.
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Résumé
This work introduces the development of Python-based software leveraging the Boundary Element Method (BEM) to predict advanced materials' thermal and multi-physical properties, including Phase Change Materials (PCM), aerogels, sands, and other prospective candidates for energy applications. The primary goal is to conduct virtual experiments that enable efficient material characterization and optimize performance in solar energy harvesting, industrial waste heat recovery, and hydrogen generation systems. By significantly reducing development costs and accelerating the timeline for new products, this research provides strategic advantages for industrial adoption, contributing to energy efficiency improvements and carbon footprint reduction in the oil & gas sector while supporting global energy transition initiatives. The proposed software integrates BEM to solve complex, multi-physical problems, such as transient heat transfer, phase transitions, thermal energy storage, and coupled thermal behaviour under realistic boundary conditions. Virtual experiments are conducted to simulate temperature distributions, thermal conductivity, phase change dynamics, and energy storage performance in materials under conditions relevant to solar energy systems, waste heat recovery, and hydrogen production processes. The model’s accuracy is rigorously validated through benchmark problems, comparisons with Finite Element Method (FEM) simulations, and available experimental data, ensuring reliability and precision. Preliminary results demonstrate the software's ability to accurately predict the multi-physical and thermal behaviour of materials such as PCM, aerogels, and sand under dynamic and operationally relevant conditions. Virtual experiments reveal significant potential for optimizing thermal energy storage systems, enhancing waste heat utilization, and improving material performance in hydrogen generation processes. Importantly, the virtual experimentation approach enables substantial cost reductions and accelerates the design and development of innovative materials, providing industries with a competitive edge. The BEM-based methodology minimizes computational costs while maintaining high accuracy, making it suitable for large-scale simulations of energy systems. The developed Python-based software provides a robust and efficient tool for the characterization, optimization, and accelerated development of advanced energy materials, including PCM, aerogels, and other candidates. Its capability to perform virtual experiments reduces the costs and time associated with traditional material testing and enables the rapid deployment of cutting-edge technologies for solar energy systems, waste heat recovery, and hydrogen production. By enhancing energy efficiency and reducing carbon emissions, this work supports the oil & gas sector in its transition toward cleaner energy solutions and contributes to global decarbonization efforts.
| Type de document: | Compte rendu de conférence |
|---|---|
| Éditeurs: | Éditeurs ORCID Hof, Lucas A. NON SPÉCIFIÉ Di Labbio, Giuseppe NON SPÉCIFIÉ Tahan, Antoine NON SPÉCIFIÉ Sanjosé, Marlène NON SPÉCIFIÉ Lalonde, Sébastien NON SPÉCIFIÉ Demarquette, Nicole R. NON SPÉCIFIÉ |
| Date de dépôt: | 18 déc. 2025 15:32 |
| Dernière modification: | 18 déc. 2025 15:32 |
| URI: | https://espace2.etsmtl.ca/id/eprint/32490 |
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