Comprehensive examination of topologically optimized thermo-fluid heat sinks
Journal article
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Publication Details
Author list: Sorravit Waelveerakup; Kasidith Thanomthong; Punnapop Tantivimonkajorn; Vichapol Wanittansirichok; Kanich Mongkholphan; Kittipong Sakamatapan; Patcharapit Promoppatum; Somchai Wongwises;
Publisher: Elsevier
Publication year: 2024
Journal: Energy (0360-5442)
Volume number: 298
ISSN: 0360-5442
Languages: English-Great Britain (EN-GB)
Abstract
This study investigates the thermal performance of topologically optimized heat sinks. The primary aims are to conduct a comprehensive parametric study, compare thermal outputs with the benchmark model, and validate numerical simulations through experimental testing. Multi-objective topology optimization is formulated based on thermal compliance and power dissipation. Selected optimized models were built and tested. The parametric study revealed promising design variables, leading to numerical convergence with interconnected flow paths. The promising variables were found under weighted thermal compliances (wh) between 0.3 and 0.9 and targeted liquid fractions (θFV) between 0.5 and 0.8. Additionally, at low operating pressures, for example, at 0.01 kPa, the temperature difference between optimized and benchmark models could be as much as 30 °C. Nonetheless, the temperature difference between both models became smaller at higher operating pressures. Furthermore, the comparison of temperature measurements, pressure drops, and thermal imaging showed reasonable agreement between experimental and numerical results. Additionally, the effect of design variables on thermal performance was confirmed through experiments. The heat sink with higher wh exhibited a lower temperature than that of the model with lower wh. In summary, this research highlights the crucial role of design variables in achieving a balance between temperature and pressure drop. © 2024 Elsevier Ltd
Keywords
Conjugate heat transfer problem, Experimental testing, Thermo-fluid heat sinks, Topology optimization
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