首页> 外文会议>ASME international technical conference and exhibition on packaging and integration of electronic and photonic microsystems >NUMERICAL OPTIMIZATION OF ADVANCED MONOLITHIC MICROCOOLERS FOR HIGH HEAT FLUX MICROELECTRONICS
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NUMERICAL OPTIMIZATION OF ADVANCED MONOLITHIC MICROCOOLERS FOR HIGH HEAT FLUX MICROELECTRONICS

机译:高通量微电子学中高级单分子微冷却器的数值优化

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This study considers the optimization of a complex micro-scale cooling geometry that represents a unit-cell of a full heat sink microstructure. The configuration consists of a channel with a rectangular cross section and a hydraulic diameter of 100 μm, where the fluid flows between two cooling fins connected by rectangular crossbars (50 × 50 μm). A previous investigation showed that adding these crossbars at certain locations in the flow can increase the heat transfer in the microchannel, and in the present work we perform an optimization to determine the optimal location and number of crossbars. The optimization problem is defined using 12 discrete design parameters, which represent 12 crossbars at different locations in the channel that can either be turned off and become part of the fluid domain, or turned on and become part of the solid domain. The optimization was done using conjugate heat transfer computational fluid dynamics (CFD) simulations using Fluent 15.0. All possible 4096 configurations were simulated for one set of boundary conditions. The domain was discretized using about 1 million nodes combined for the fluid and solid domains and the computational time was around 1 CPU hour per case. The results show that further improvements in heat transfer are feasible at an optimized pressure drop. The results cover a range of pressure drops from 25 kPa to almost 90 kPa and the heat transfer coefficient varies from 60 to 120 kW/m~2K. The configurations on the Pareto front show the trend that crossbars closer to the maximal fluid-solid interface result in a more optimal performance than crossbars positioned farther away. In addition to performing simulations for all possible configurations, the potential of using a genetic algorithm to identify the configurations that define the Pareto front was explored, demonstrating that a 80% reduction in computational time can be achieved. The results of this study demonstrate the significant increase in performance that can be obtained through the use of computational tools and optimization algorithms for the design of single phase cooling devices.
机译:这项研究考虑了复杂的微尺度冷却几何结构的优化,该几何结构代表了完整的散热器微结构的晶胞。该配置由一个横截面为矩形且水力直径为100μm的通道组成,在该通道中,流体在两个通过矩形横杆(50×50μm)连接的散热片之间流动。先前的研究表明,在流中的某些位置添加这些横杆可以增加微通道中的传热,并且在当前工作中,我们进行了优化以确定横杆的最佳位置和数量。使用12个离散的设计参数定义优化问题,这些参数代表通道中不同位置的12个交叉开关,这些交叉开关可以关闭并成为流体域的一部分,也可以打开并成为实体域的一部分。使用Fluent 15.0使用共轭传热计算流体动力学(CFD)模拟进行了优化。针对一组边界条件模拟了所有可能的4096配置。使用大约100万个用于流体和固体域的节点离散化该域,每个案例的计算时间约为1个CPU小时。结果表明,在最佳压降下,进一步改善传热是可行的。结果涵盖了从25 kPa到几乎90 kPa的压降范围,传热系数从60到120 kW / m〜2K不等。 Pareto前端的配置显示出这样一种趋势,即靠近最大流体-固体界面的横杆比位置较远的横杆具有更好的性能。除了对所有可能的配置进行仿真之外,还探索了使用遗传算法识别定义Pareto前沿的配置的潜力,这表明可以将计算时间减少80%。这项研究的结果表明,通过使用计算工具和优化算法来设计单相冷却设备,可以显着提高性能。

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