医疗设备微尺度冷却用水-金刚石纳米流体流动的数值模拟及人工神经网络设计

M. Sepehrnia, Golnoush Abaei, Zahra Khosromirza, Faezeh RooghaniYazdi
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引用次数: 4

摘要

近年来,微机电系统(MEMS)和纳米技术系统在微型电气设备冷却中的同步应用引起了研究人员的广泛关注。本文主要讨论了电子电路板医疗设备的冷却问题。为此,采用体积分数分别为1%、2%、3%和4%的水和水-金刚石纳米流体作为微尺度冷却系统的冷却剂。冷却剂以5,15,25和35kpa的压力泵入散热器。板上的电子芯片嵌入散热器底板内,产生均匀的热流密度85kW/m2。采用基于有限元的有限体积法求解了控制方程。结果表明:水-金刚石纳米流体与纯水相比,对冷却效果有明显改善,体积分数为4%的水-金刚石纳米流体对冷却效果的改善幅度在4.46% ~ 7.22%之间;当压降从5 kPa增加到35 kPa时,冷却指标的改善幅度在17.86% ~ 25.52%之间。设计径向基函数人工神经网络,数值模拟结果与预测结果吻合较好。
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Numerical Simulation and Designing Artificial Neural Network for Water-Diamond Nanofluid Flow for Micro-Scale Cooling of Medical Equipment
Simultaneous using of MEMS (Micro Electro Mechanical Systems) and nanotechnology systems in the cooling of micro-scale electrical equipment has attracted researchers in recent years. In the present study, cooling of medical equipment with electronic board is discussed. For this purpose, water and water-diamond nanofluid with a volume fraction of 1%, 2%, 3% and 4% are used as a coolant of micro-scale cooling system. Coolants are pumped into heat sink at pressures of 5, 15, 25 and 35 kPa. The electronic chip on the board is embedded in the base plate of heat sink and generates uniform heat flux of 85kW/m2. The governing equations have been solved using finite volume method based on finite element. The results show that utilizing water-diamond nanofluid compared to water improves the cooling process so that utilizing water-diamond nanofluid with volume fraction of 4% improves the cooling process between 4.46% and 7.22%. Moreover, increasing pressure drop from 5 kPa to 35 kPa improves cooling indexes between 17.86% and 25.52%. Moreover, designing radial basis function artificial neural network shows good agreement between numerical simulation and predicted results.
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