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<p>Efficient thermal management of high heat flux devices has become a critical challenge in modern engineering applications, including power electronics, electronic cooling, and advanced energy systems. Liquid jet impingement cooling is recognized as one of the most effective methods for achieving high heat transfer rates; however, the combined influence of geometric parameters, flow conditions, nanoparticle concentration, and surface characteristics on thermal performance is not yet fully understood. In addition, only a limited number of studies have combined experimental investigations with optimization techniques to identify the best operating conditions for maximizing heat transfer. To address these gaps, the present study experimentally investigates the heat transfer characteristics of water and aluminum oxide nanofluid jet impingement on a uniformly heated copper surface subjected to constant heat flux. The effects of flow Reynolds number, nozzle-to-surface spacing ratio, nozzle diameter, jet inclination angle, nanoparticle concentration, and surface roughness on local and average heat transfer coefficients are systematically examined. Experiments are performed using nozzle diameters of 4, 6, and 8&#xa0;mm, flow rates ranging from 1 to 3&#xa0;L per minute, nanoparticle concentrations between 0.1 and 0.5 percent by volume, nozzle-to-surface spacing ratios from 2 to 18, and jet inclination angles from 0 to 30°. Temperature measurements at eight locations on the heated surface are used to analyze spatial variations in heat transfer and stagnation region behavior. The novelty of this work lies in the integrated experimental and optimization-based investigation of inclined nanofluid jet impingement cooling, considering multiple interacting parameters simultaneously. A particle swarm optimization technique is employed to determine the operating conditions that maximize the Nusselt number. The optimization results indicate that a Reynolds number of 8500, a jet inclination angle of 15°, a nozzle-to-surface spacing ratio of 10, and an aluminum oxide nanofluid concentration of 0.2 percent by volume provide the best thermal performance, resulting in a 28 percent increase in the heat transfer coefficient compared with the baseline case. Furthermore, a generalized heat transfer correlation relating the Nusselt number, Reynolds number, Prandtl number, and nozzle-to-surface spacing ratio is developed from the experimental data. The results demonstrate that stagnation point characteristics, jet inclination, surface roughness, and nanoparticle concentration significantly influence heat transfer enhancement. The proposed experimental database, predictive correlation, and optimized operating conditions provide valuable guidance for the design and thermal management of high-performance cooling systems based on liquid jet impingement technology.</p> Graphic Abstract <p></p>

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Experimental and optimization study on heat transfer in liquid jet impingement using particle swarm optimization for thermal management

  • 期刊论文

  • 发表日期：

    2026年8月5日

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  • Sonali Anant Deshmukh,
  • Tuqa Abdulrazzaq,
  • Jatoth Heeraman,
  • Praveen Barmavatu,
  • Dadapeer Doddamani,
  • Ramalinga Viswanathan Mangalaraja,
  • Vineet Singh Sikarwar

摘要

Efficient thermal management of high heat flux devices has become a critical challenge in modern engineering applications, including power electronics, electronic cooling, and advanced energy systems. Liquid jet impingement cooling is recognized as one of the most effective methods for achieving high heat transfer rates; however, the combined influence of geometric parameters, flow conditions, nanoparticle concentration, and surface characteristics on thermal performance is not yet fully understood. In addition, only a limited number of studies have combined experimental investigations with optimization techniques to identify the best operating conditions for maximizing heat transfer. To address these gaps, the present study experimentally investigates the heat transfer characteristics of water and aluminum oxide nanofluid jet impingement on a uniformly heated copper surface subjected to constant heat flux. The effects of flow Reynolds number, nozzle-to-surface spacing ratio, nozzle diameter, jet inclination angle, nanoparticle concentration, and surface roughness on local and average heat transfer coefficients are systematically examined. Experiments are performed using nozzle diameters of 4, 6, and 8 mm, flow rates ranging from 1 to 3 L per minute, nanoparticle concentrations between 0.1 and 0.5 percent by volume, nozzle-to-surface spacing ratios from 2 to 18, and jet inclination angles from 0 to 30°. Temperature measurements at eight locations on the heated surface are used to analyze spatial variations in heat transfer and stagnation region behavior. The novelty of this work lies in the integrated experimental and optimization-based investigation of inclined nanofluid jet impingement cooling, considering multiple interacting parameters simultaneously. A particle swarm optimization technique is employed to determine the operating conditions that maximize the Nusselt number. The optimization results indicate that a Reynolds number of 8500, a jet inclination angle of 15°, a nozzle-to-surface spacing ratio of 10, and an aluminum oxide nanofluid concentration of 0.2 percent by volume provide the best thermal performance, resulting in a 28 percent increase in the heat transfer coefficient compared with the baseline case. Furthermore, a generalized heat transfer correlation relating the Nusselt number, Reynolds number, Prandtl number, and nozzle-to-surface spacing ratio is developed from the experimental data. The results demonstrate that stagnation point characteristics, jet inclination, surface roughness, and nanoparticle concentration significantly influence heat transfer enhancement. The proposed experimental database, predictive correlation, and optimized operating conditions provide valuable guidance for the design and thermal management of high-performance cooling systems based on liquid jet impingement technology.

Graphic Abstract