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Reduced order thermal modeling of data centers via proper orthogonal decomposition: a review

机译:通过适当的正交分解对数据中心进行降阶热建模:回顾

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Purpose - The purpose of this paper is to review the available reduced order modeling approaches in the literature for predicting the flow and specially temperature fields inside data centers in terms of the involved design parameters.rnDesign/methodology/approach - This paper begins with a motivation for flow/thermal modeling needs for designing an energy-efficient thermal management system in data centers. Recent studies on air velocity and temperature field simulations in data centers through computational fluid dynamics/ heat transfer (CFD/HT) are reviewed. Meta-modeling and reduced order modeling are tools to generate accurate and rapid surrogate models for a complex system. These tools, with a focus on low-dimensional models of turbulent flows are reviewed. Reduced order modeling techniques based on turbulent coherent structures identification, in particular the proper orthogonal decomposition (POD) are explained and reviewed in more details. Then, the available approaches for rapid thermal modeling of data centers are reviewed. Finally, recent studies on generating POD-based reduced order thermal models of data centers are reviewed and representative results are presented and compared for a case study. Findings - It is concluded that low-dimensional models are needed in order to predict the multi-parameter dependent thermal behavior of data centers accurately and rapidly for design and control purposes. POD-based techniques have shown great approximation for multi-parameter thermal modeling of data centers. It is believed that wavelet-based techniques due to the their ability to separate between coherent and incoherent structures - something that POD cannot do - can be considered as new promising tools for reduced order thermal modeling of complex electronic systems such as data centers Originality/value - The paper reviews different numerical methods and provides the reader with some insight for reduced order thermal modeling of complex convective systems such as data centers.
机译:目的-本文的目的是回顾文献中可用的降阶建模方法,以根据涉及的设计参数来预测数据中心内部的流量和温度场.rn设计/方法/方法-本文从动机出发流量/热量建模的需求,需要在数据中心设计节能的热量管理系统。通过计算流体动力学/传热(CFD / HT),对数据中心中空气速度和温度场模拟的最新研究进行了综述。元建模和降阶建模是为复杂系统生成准确,快速的替代模型的工具。这些工具,重点是湍流的低维模型进行了审查。基于湍流相干结构识别的降阶建模技术,尤其是适当的正交分解(POD),将得到详细解释和审查。然后,回顾了用于数据中心快速热建模的可用方法。最后,对有关生成基于POD的数据中心降阶热模型的最新研究进行了回顾,并给出了代表性的结果并进行了案例比较。发现-结论是需要低维模型,以便为设计和控制目的准确快速地预测数据中心的多参数相关热行为。基于POD的技术对于数据中心的多参数热建模显示出非常近似的效果。人们认为,基于小波的技术由于具有分离相干结构和非相干结构的能力(POD无法做到这一点),可以被认为是用于降低复杂的电子系统(例如数据中心)热模型的有希望的新工具。 -本文回顾了不同的数值方法,并为读者提供了对复杂对流系统(如数据中心)降阶热模型的一些见解。

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