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<p>This study introduces a new type of fins’ heat sinks, namely the skeleton-based heat exchanger; it combines multi-objective optimization along with the parametric identification of the new design to improve the heat exchange performances. Then, the materials and geometry features were selected according to multi-objective genetic algorithm optimization based on thermal/CFD simulations. By taking advantages of ANSYS Fluent platform, including design of experiments and MOGA, the optimal feasible space of the skeletal geometry features was detected; optimal materials’ performance was obtained near AlSi10Mg aluminum alloy. The second step focused on the system identification of the optimal design; it was mainly based on thermal solicitations namely the Dirac impulse along with the corresponding temperature output; the optimal design was detected to be a 1st-order system, while the validation involved both step and ramp input signals. In sum, results indicate a strong potential to improve heat exchangers using MOGA of the skeletal geometry with the AlSi10Mg; this includes the system effectiveness, the fins’ efficiency, and the overall efficiency that ranged above 90% according to the simulations. In addition, the study was corroborated by a benchmark that allowed positioning the present findings within existing literature; the authors especially pointed out the existing contribution and those of the current work. However, this opens new prospects to further research and practical applications in electronics cooling where future studies are currently under development, focusing on experimenting the proposed design integrating along with the phase change materials integration to enhance this new system.</p>

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Simulation-based optimization and parametric identification of a new skeletal shape-based fins’ heat exchanger

  • 期刊论文

  • 发表日期：

    2025年6月19日

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  • Fabrice Nimbona,
  • Mostapha El Jai,
  • Iatimad Akhrif,
  • Nadir Rihani,
  • Benaissa El Fahime,
  • Mohammed Radouani

摘要

This study introduces a new type of fins’ heat sinks, namely the skeleton-based heat exchanger; it combines multi-objective optimization along with the parametric identification of the new design to improve the heat exchange performances. Then, the materials and geometry features were selected according to multi-objective genetic algorithm optimization based on thermal/CFD simulations. By taking advantages of ANSYS Fluent platform, including design of experiments and MOGA, the optimal feasible space of the skeletal geometry features was detected; optimal materials’ performance was obtained near AlSi10Mg aluminum alloy. The second step focused on the system identification of the optimal design; it was mainly based on thermal solicitations namely the Dirac impulse along with the corresponding temperature output; the optimal design was detected to be a 1st-order system, while the validation involved both step and ramp input signals. In sum, results indicate a strong potential to improve heat exchangers using MOGA of the skeletal geometry with the AlSi10Mg; this includes the system effectiveness, the fins’ efficiency, and the overall efficiency that ranged above 90% according to the simulations. In addition, the study was corroborated by a benchmark that allowed positioning the present findings within existing literature; the authors especially pointed out the existing contribution and those of the current work. However, this opens new prospects to further research and practical applications in electronics cooling where future studies are currently under development, focusing on experimenting the proposed design integrating along with the phase change materials integration to enhance this new system.