流网络建模和CFD在计算机系统设计中的应用

S.S. Kang
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引用次数: 6

摘要

本文描述了利用市售的流动网络建模(FNM)和计算流体动力学(CFD)软件设计计算机系统的气流,并提出了一种结合两者最佳特性的新的混合方法。所提出的方法的基础在于认识到在计算机系统的不同区域内的气流可以分为两类。一类由流动方向明确的区域或子系统组成(例如,在卡阵列、电源、磁盘驱动器阵列之间形成的通道等),可以使用FNM表示中的流动阻抗组件很好地建模,而第二种类型的区域,其流动模式定义不清(例如,气流整体),高度依赖于相邻子系统的特性,需要CFD进行充分的建模。样品设计问题的FNM模型提供了快速的结果,并允许对许多设计方案进行评估,但不可避免地要以过度简化第二类区域为代价。完整的系统CFD模型规模很大,需要大量的计算时间和大量的后处理工作来理解结果。这些问题通过混合方法解决,混合方法的关键属性及其在FNM和CFD代码中的实现被描述。一个CFD模型被用来说明所提出的方法,并证明,对于这里使用的特定设计问题,与完整的CFD模型相比,该方法在模型尺寸减少14/spl倍/和模拟时间减少30/spl倍/的同时,产生了良好的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of flow network modeling and CFD to computer system design
This paper describes the air flow design of a computer system using commercially available flow network modeling (FNM) and computational fluid dynamics (CFD) software and proposes a new Hybrid approach that combines the best features of both. The basis of the proposed approach lies in the recognition that air flow within different regions of a computer system can be divided into two categories. One category, consisting of regions or subsystems through which the flow direction is well defined (e.g. Channels formed between card arrays, power supplies, an array of disk drives etc.) is well modeled using a flow impedance component in a FNM representation whereas the second type of region where the flow pattern is poorly defined (e.g. Air flow plenums) and highly dependent on the characteristics of adjoining subsystems requires CFD to model adequately. The FNM model of the sample design problem provides quick results and allows many design alternatives to be assessed but at the inevitable cost of oversimplifying the second type of region. The full system CFD model is large in size, requires a large computational time and significant post processing effort to understand the results. These issues are addressed by the Hybrid method whose key attributes and implementation within FNM and CFD codes is described. A CFD model is used to illustrate the proposed approach and demonstrate that, for the specific design problem used here, the method yields good accuracy while achieving 14/spl times/ reduction in model size and 30/spl times/ reduction in simulation time compared to the full CFD model.
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