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Management and predictions of operational changes and growth in mission critical facilities

机译:管理和预测使命关键设施的运营变化和增长

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The main challenge in understanding the cooling performance in a legacy data center is the invisible transport medium (air). This emphasizes the need for smart and meticulous measurement techniques. However, the nature of measurements is finite (e.g. top, middle and bottom) and the variation between often non-linear, therefore to capture the gradients between measured points a validated CFD simulation is needed. In this paper a brief description of an experimental characterization of a new data center lab is discussed. Airflow and temperature measurements are utilized to understand the facility's performance at different operational stages, until reaching the designed capacity. Since the facility houses a wide range of different IT equipment (servers, switches, storage and blades), it is important to understand the airflow demand of each. To do that, each type of IT was tested separately and flow characteristics were obtained (i.e. free delivery, critical pressure and flow curves). In the second part, all the characterization data is integrated via compact models into a full CFD simulation. The measured points are used for validation and the full field of air temperature and flow is resolved. Both the measurements and simulation data will now be used to answer important design, deployment and operational change questions.
机译:在理解传统数据中心的冷却性能方面的主要挑战是看不见的传输介质(空气)。这强调需要智能和细致的测量技术。然而,测量的性质是有限的(例如,顶部,中间和底部),并且通常非线性之间的变化因此需要在测量点之间捕获验证的CFD模拟之间的梯度。在本文中,讨论了新数据中心实验室的实验表征的简要描述。气流和温度测量用于了解设施在不同运营阶段的工厂的性能,直到达到设计的容量。由于该设施包括各种不同的IT设备(服务器,开关,存储和刀片),因此了解每个的气流需求非常重要。为此,将每种类型分别测试,获得流动特性(即自由递送,临界压力和流动曲线)。在第二部分中,所有特征数据都通过Compact模型集成到完整的CFD仿真中。测量的点用于验证,并解决空气温度和流动的整个领域。现在,测量和仿真数据都将用于回答重要的设计,部署和操作变更问题。

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