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...zero 100%; higher values generally imply good cooling performance and scalability of a cooling architecture. In many applications, the capture index provides additional information relative to rack-inlet temperatures and other cooling indices. In some applications, capture index may be computed in lieu of other metrics. Two variants of capture index are defined: one for cold- and another for hot-aisle analyses. A technique for computing CIs numerically, based on tracking airflow with passive concentrations, is provided along with examples based on CFD simulations. A cluster-wide cooling performance metric based on CI, the total escaped power, is also proposed. Finally, an example shows how CI and total escaped power may be used alongside other metrics to determine an optimized physical arrangement of a given inventory of racks and coolers bounding a hot aisle.
INTRODUCTION
Racks of electronics equipment in a data center are typically arranged in rows with cooling air supplied via a raised floor through perforated floor tiles; warm air is typically returned to the room environment and ultimately to cooling units located around the perimeter of the room. Another option is to locate cooling units directly within or around the rows of racks; this allows a close match between rack load and cooling resources and, because all required cooling is supplied locally, is inherently scalable. With either architecture, equipment is often arranged in alternating cold and hot aisles to promote greater separation of the cold supply and warm return streams. Further, for cooling system design, it is often particularly useful to focus on a "cluster" of racks and, possibly, coolers--two rows bounding a common cold or hot aisle--as a fundamental design unit.
Figure 1a shows a simple cold-aisle cluster in a raised-floor environment. The cooling design goal is to ensure that all rack inlet temperatures are maintained within a specified range. The strategy here is to ensure that racks primarily ingest cooling airflow from the perforated tiles rather than warm recirculated air that has already been heated by the electronics equipment. As the racks often have differing airflow requirements, they compete with one another for cooling airflow supplied by all of the perforated tiles in the immediate neighborhood, which may include the entire cold aisle. Thus, it is the airflow dynamics within and around the cold aisle--along with supply and surrounding room temperatures--that determines cooling performance, and a cold-aisle cluster is a particularly useful design unit.
Figure 1b shows a simple hot-aisle cluster in a hard-floor environment with local coolers. The coolers in the figure are one-half the width of a rack and move air in the opposite direction; warm air is drawn in from the hot aisle and cool air is supplied into the cold aisle. Whenever hot rack exhaust is captured locally, as in Figure 1b, a "room-neutral" design strategy may be used: local coolers (or return vents) are configured to capture most of the hot rack exhaust airflow while cooling airflow is supplied at room temperature. If the room-neutral goal is achieved, many such clusters may be deployed throughout the data center with no net heating of the overall room environment, and all equipment inlets will receive uniformly conditioned air. Hence, the cooling design is "scalable." (By contrast, there are typically substantial variations in inlet temperatures in a traditional raised-floor application, particularly in the vertical direction.) A limiting example of the room-neutral design strategy is to physically enclose the hot aisle, thereby isolating it from the surrounding data center environment. (For examples, see Niemann [2006] and Rasmussen [2005].) Thus, it is the airflow dynamics within and around the hot aisle that determine the success of the room-neutral design strategy, so a hot-aisle cluster is a particularly useful design unit. (Note that, while a departure from the room-neutral strategy, with local cooling, a cold-aisle cluster may also be a useful design unit. This is analogous to the raised-floor cold-aisle cluster with the cooling airflow supplied by local coolers rather than through perforated tiles.)
[FIGURE 1 OMITTED]
Since the capture index for each rack is typically defined with reference to local cooling resources (e.g., perforated tile airflow or cooler extract airflow in the immediate vicinity of the rack), discussion and examples in this paper focus on individual clusters. However, the use of capture index is not restricted to the types of clusters shown in Figure 1; a cold-aisle cluster could be, for example, defined as a single row of racks served by a number of perforated tiles, which need not even be immediately adjacent to the racks.
CAPTURE INDEX DEFINED
The cold-aisle capture index is defined as the fraction of air ingested by the rack that originates from local cooling resources (e.g., perforated floor tiles or local coolers). The hot-aisle capture index is defined as the fraction of air exhausted by a rack that is captured by local extracts (e.g., local coolers or return vents). CI, therefore, varies between and 100%, with better cooling performance generally indicated by greater CI values. In a cold-aisle analysis, high CIs ensure that the bulk of the air ingested by a rack comes from local cooling resources rather than being drawn from the room environment or from air that may have already been heated by electronics equipment. In this case, rack inlet temperatures will closely track the perforated-tile airflow temperatures and, assuming these temperatures are within the desired range, acceptable cooling will be achieved. In a hot-aisle analysis, high CIs ensure that rack exhaust is captured locally and there is little heating of the surrounding...
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