This study uses a combination of computational fluid dynamics consisting of the discrete phase model (CFD-DPM) coupled with support vector regression-particle swarm optimization (SVR-PSO) techniques to maximize the cooling performance of Al₂O₃water nanofluids in a microchannel heat sink (MCHS) with multiple synthetic jets (SJs). First, a CFD parametric study is carried out to understand the effect of influential parameters, including orifice spacing, particle volume fraction, orifice height, diaphragm length, phase actuation of jets, frequency and amplitude of oscillating diaphragms. A hybrid SVR-PSO algorithm is then adopted to predict the optimum values of the influential parameters for the maximum homogeneous heat transfer. The results predicted by the machine learning algorithm (MLA) are also compared to CFD findings. 0.15% and 3.5% deviations are found between predicted and actual values for the minimum average temperature and temperature uniformity, respectively. The parametric study reveals that heat transfer increases when the two jets are placed apart from each other. Based on the parametric study, the average temperature drops by 4.3 K as the membrane length increases from 0.95 mm to 1.96 mm. The highest heat transfer is obtained at a particle volume fraction of 5% in both jet arrangements. It is found that increasing the amplitude and frequency of the membranes results in better cooling performance. The results also confirm that larger orifice heights allow the creation of longer and stronger flows in the orifices that propagate the furthest in the microchannel. Overall, in-phase jet configurations show more uniform and lower temperatures (e.g., better heat transfer) at higher particle concentrations compared to the 180° out-of-phase jet arrangements.

这项研究结合了由离散相模型（CFD-DPM）和支持向量回归粒子群优化（SVR-PSO）技术组成的计算流体动力学的组合，以最大限度地提高Al ₂ O ₃的冷却性能具有多个合成喷嘴（SJ）的微通道散热器（MCHS）中的水纳米流体。首先，进行CFD参数研究以了解影响参数的影响，包括孔间距，颗粒体积分数，孔高度，膜片长度，射流的相位驱动，振动膜片的频率和振幅。然后采用混合SVR-PSO算法来预测影响参数的最佳值，以实现最大的均匀传热。还将机器学习算法（MLA）预测的结果与CFD发现进行比较。最小平均温度和温度均匀性的预测值和实际值之间分别存在0.15％和3.5％的偏差。参数研究表明，当两个喷嘴彼此分开放置时，传热会增加。根据参数研究，随着膜长度从0.95 mm增加到1.96 mm，平均温度下降4.3K。在两个喷射装置中，当颗粒体积分数均为5％时，可获得最高的热传递。发现增加膜的振幅和频率导致更好的冷却性能。结果还证实，较大的孔高度允许在孔中产生更长和更强的流动，从而在微通道中传播最远。总体而言，与180°异相射流装置相比，同相射流配置在较高的颗粒浓度下显示出更均匀且温度更低（例如，更好的传热）。在两个喷射装置中，当颗粒体积分数均为5％时，可获得最高的热传递。发现增加膜的振幅和频率导致更好的冷却性能。结果还证实，较大的孔高度允许在孔中产生更长和更强的流动，从而在微通道中传播最远。总体而言，与180°异相射流装置相比，同相射流配置在较高的颗粒浓度下显示出更均匀且温度更低（例如，更好的传热）。在两个喷射装置中，当颗粒体积分数均为5％时，可获得最高的热传递。发现增加膜的振幅和频率导致更好的冷却性能。结果还证实，较大的孔高度允许在孔中产生更长和更强的流动，从而在微通道中传播最远。总体而言，与180°异相射流装置相比，同相射流配置在较高的颗粒浓度下显示出更均匀且温度更低（例如，更好的传热）。结果还证实，较大的孔高度允许在孔中产生更长和更强的流动，从而在微通道中传播最远。总体而言，与180°异相射流装置相比，同相射流配置在较高的颗粒浓度下显示出更均匀且温度更低（例如，更好的传热）。结果还证实，较大的孔高度允许在孔中产生更长和更强的流动，从而在微通道中传播最远。总体而言，与180°异相射流装置相比，同相射流配置在较高的颗粒浓度下显示出更均匀且温度更低（例如，更好的传热）。