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Article Dans Une Revue International Journal of Heat and Mass Transfer Année : 2024

A genetic algorithm-based topology optimization (GATO) method for convective cooling of a heating surface with multiple heat sources

Résumé

A heat-generating surface with multiple heat sources is frequently encountered in modern power electronic devices. Efficient cooling techniques are especially needed to prevent the overheating of these devices, so as to avoid consequences like performance deterioration, failure rate increase, reduced lifetime and safety threats. The main objective of this study is to design and optimize the structure of heat sinks for single-phase convective cooling of a heat-generating surface under multiple-peak heat flux. In particular, a genetic algorithm-based topology optimization (GATO) method has been developed and tested for this purpose. The middle area of heat sink receiving heat flux is treated as the design domain and represented as a binary matrix (Mrow×column). Each element in the matrix is considered either as fluid or as solid, and their allocation is optimized to minimize the peak temperature (Tpeak) at the heating surface of the heat sink under the constraint of constant void volume for the fully-connected fluid domain. For each optimization step, the fluid flow and temperature characteristics are obtained by CFD simulation using OpenFoam, which are then used for GA operations (selection, crossover, mutation, etc.). The impacts of design and operation parameters on the optimized global flow channel configuration are evaluated, including the heat flux shape, the fluid void fraction, the inlet velocity, and the resolution of the design domain. Results obtained show that: (1) the proposed GATO method could successfully determine the optimal flow channel configuration of the heat sink, minimizing the Tpeak at the heating surface; (2) The obtained optimal configuration depends on the design and operating parameters while the effectiveness and robustness of the GATO method are verified; (3) Compared to conventional straight channel heat sink, the GATO heat sink could always achieve a better cooling performance under the same working condition, with a reasonable and acceptable increase of the pressure drop. The method developed in this study could be a useful contribution to the TO of heat sinks/exchangers with demonstrated potential in engineering thermal design and optimization
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Dates et versions

hal-04487946 , version 1 (27-03-2024)

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Yijun Li, Stéphane Roux, Cathy Castelain, Yilin Fan, Lingai Luo. A genetic algorithm-based topology optimization (GATO) method for convective cooling of a heating surface with multiple heat sources. International Journal of Heat and Mass Transfer, 2024, 224, pp.125349. ⟨10.1016/j.ijheatmasstransfer.2024.125349⟩. ⟨hal-04487946⟩
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