Xuanhang Zhang

Partially Decoupled Aisle Method for Estimating Rack-Cooling Performance in Near-Real Time

The Partially Decoupled Aisle (PDA) method facilitates a near-real-time cooling-performance analysis of a single cluster of racks and, potentially, coolers, bounding a common hot or cold aisle in a data center. With the PDA method, the airflow patterns and related variables need be computed only within an isolated cold or hot aisle “on the fly” through CFD analysis or other means. The analysis is fast because the much larger surrounding room environment is not directly modeled; its effect enters the model through the boundary conditions applied to the top and ends of the isolated aisle. The proper boundary conditions in turn may be estimated from an empirical model determined in advance (“offline”) from the study of a large number of CFD simulations of varying equipment layouts and room environments. A software tool based on the PDA method, which uses a full CFD engine to solve the aisle airflow within the isolated aisle, can analyze a typical cluster of racks and coolers in 10–30 seconds and requires no special user skills. This paper formally introduces the general PDA method and shows several examples of its application with comparisons to corresponding whole-room CFD analyses.Copyright

Experimental Measurement of Server Thermal Effectiveness for Compact Transient Data Center Models

Server thermal mass can significantly affect the rate at which a data center heats up following a loss of cooling and moderate transient temperature fluctuations due to changing CPU utilization. Recently, a compact server model has been introduced which captures the effects of thermal mass while avoiding the impractical level of detail that would be required by an explicit representation of all relevant server components. Inputs to that model include server mass, overall effective specific heat, and a parameter called the “server thermal effectiveness”. The latter characterizes the server’s ability to transfer heat to/from the airstream passing through it and can take values between zero (no heat exchange) and one (maximum possible heat exchange). Server thermal mass is a physical property of a server and is not influenced by external factors.In order to use the compact model for practical applications, we must experimentally measure the thermal effectiveness of actual servers. The present study reviews the compact model and describes the development of an experimental technique for measuring thermal effectiveness. The technique is validated using simple plate fin heat sinks in place of an actual server. This “server proxy” is sufficiently simple so that it can be modeled accurately in detail in CFD, providing well-controlled benchmark data. CFD and experimental measurements both yield a value of server thermal effectiveness of approximately 0.6, providing confidence in the model and measurement technique for the future characterization of actual servers.Copyright

Cooling performance of ceiling-plenum-ducted containment systems in data centers

In an effort to improve the reliability and efficiency of data centers, racks and sometimes entire hot aisles are ducted to a dropped ceiling. The cooling performance of such systems strongly depends on IT and cooler airflow, the number and configuration of ducted objects and perforated ceiling tiles, the leakiness of the ceiling system, ceiling plenum depth, and other factors. Recently, a compact model has been proposed in which a Flow Network Model (FNM) representing the ducted equipment is embedded into a parent CFD model. By eliminating the need to explicitly model difficult-to-characterize leakage paths in CFD, this approach allows for realistic solutions while greatly improving the solutions speed and robustness of the CFD simulation. This paper employs the FNM (without CFD) to characterize and compare the cooling effectiveness of individually-ducted racks and ducted hot aisles subject to a given ceiling plenum pressure. Example resistance values needed in the FNM are provided. Additionally, an example data center layout is studied with the coupled FNM-CFD model to explore cooling performance as a function of ceiling leakiness, plenum depth, ratio of cooling to IT airflow, and rack density (IT airflow). Best-practice type recommendations for ducted equipment are provided.

A method for predicting key data center temperatures by known airflow streams

We present a simplified model for predicting key data-center temperatures, such as those of rack inlets and cooler returns. If the primary airflow streams into and out of all racks and coolers are known, these airflow values can be combined with the assumption of a well-mixed room ambient volume to create a simplified, but energy-balanced, set of temperature equations. Since the temperature estimates are restricted to only a small number of data center objects, solutions can be found quickly. This temperature model can be adapted to quickly address data center design or management issues without multiple Computational Fluid Dynamics (CFD) simulations. Optimized cooler set points can be quickly found with only slight adjustments to the model. In another application, the effects of cooler capacity models are easily understood when incorporated within the temperature model. The object-averaged inlet temperature estimates generated by this temperature model compare favorably to those found by CFD.

Compact Modeling of Data Center Air Containment Systems

The practice of ducting racks to a dropped ceiling or containing entire cold or hot aisles in data centers is being implemented with more frequency in an attempt to improve reliability and efficiency. While CFD and other numerical modeling tools are widely used to optimize data center cooling, they are not particularly effective at modeling containment systems; the performance of such systems is dominated by small and complex leakage paths (e.g., through, around, and under racks), which are difficult or impossible to include in a practical full-scale model. We propose a compact model which uses a flow network to determine airflow rates inside containment systems while the traditional “parent” numerical model continues to handle predictions in the rest of the facility. The two models are coupled at flow boundaries such as where ducting meets a dropped ceiling and leakage paths cross rack surfaces. The compact-model approach has the opportunity to be much faster and more robust than fully-explicit CFD models since leakage path resistances can be established through experimental measurements. We discuss the characterization of rack leakage paths and demonstrate the use of the compact model in a full data center simulation in which the role of parent numerical model is played by a potential flow model.Copyright

Measured-Temperature Interpolation and Visualization for Data Centers

The growing demand for data center facilities has made intelligently managed data center operations necessary. For temperature measurement and thermal management, a common practice is to install a limited number of temperature sensors evenly distributed throughout the room. However, data center operators rarely fully equip facilities with temperature sensors due to their cost, complexity, and maintenance requirements, creating vacancies in the data center temperature and cooling picture. The local nature of sensor data can also be misinterpreted and misused. Without novel methods to interpret and visualize temperatures obtained by prediction or measurement, data center operators cannot easily identify urgent local cooling issues or quickly examine the temperature at other location. This paper presents methods to predict a full three-dimensional temperature field in data centers from a limited number of measurement points. Several different statistical interpolating schemes are discussed. We also validate the interpolated temperature fields against benchmark data from Computation Fluid Dynamics (CFD) and show good agreement.Copyright

Data Center Airflow Prediction With an Enhanced Potential Flow Model

Potential flow models (PFM) have been implemented for a variety of applications, including data center airflow and temperature estimation. As an approximate solution to the data center room physics, potential flow models have great value in their simplicity and the limited computational effort required providing estimates. However, potential flow models lack the ability to capture the effects of buoyancy, which can affect airflow patterns within data centers. We show how this effect can be simulated within PFM; resulting in a model we call Enhanced PFM (EPFM). This model is only marginally more complex to implement than PFM and retains much of the properties of the original PFM, specifically its simplicity and stability. Solution time, about double that of PFM, is still only a small fraction of that of CFD, while empirical tests show a marked improvement in the prediction of key data center temperatures.© 2013 ASME

Development of a Raised-Floor Plenum Design Tool

Existing tools for analyzing raised-floor-plenum airflow distribution focus on the prediction of tile-by-tile airflow rates and therefore necessarily require the input of a specific floor layout. Such CFD-based tools are also typically expensive, potentially slow and are of limited availability. The present study describes a design tool which takes a somewhat more qualitative approach in which overall tile airflow uniformity and the breakdown of cooling airflow (e.g., through the perforated tiles, raised-floor leakage, and cable cutouts) are estimated from only high-level design information. The design tool’s predictions are based on both CFD simulations performed “off line” and an analytical flow network model and can be used at the concept stage in a construction project or as a learning tool to quickly demonstrate the effect of design tradeoffs on plenum airflow distribution. The applicability of the tool to a real facility is confirmed through measured data and the tool is used to investigate the effect of various design choices on perforated tile airflow uniformity and distribution.Copyright

Efficient Implementation of Potential-Flow Airflow Prediction for Data Centers

We present improvements to airflow prediction techniques for data centers, specifically within potential flow models. As a potential-flow model presents a simplified solution to the room airflow physics, additional approximations can be implemented to improve runtime without changing the accuracy of potential-flow. The improvements concentrate on two main components of current prediction methods: namely, the pre-processing task of automatic and efficient grid generation and post-processing task of capture index (CI) calculation. We propose a variable grid oriented around the objects in the room, creating cells with variable sizes (in width, height, and depth). We also show how CI calculations can be made more efficient through an understanding of the local nature of CI. An empirical study of sample data center layouts shows that these improvements can yield significant improvements in speed while maintaining a good level of accuracy.© 2013 ASME