Data centers are facilities that house computer servers, data storage systems, and telecommunications equipment. To ensure that these computer systems operate reliably, they must be adequately cooled: The airflow requirement of each server rack must be met, in order to maintain the rack inlet air temperatures within acceptable range.

The airflow distribution and rack inlet temperatures are controlled by complex fluid dynamics processes and depend on a large number of parameters, which often interact in a counter-intuitive manner. These parameters include the layouts of perforated tiles, CRAC units, supply and exhaust ducts, supplemental cooling units, and server racks; the open area of perforated tiles; the heat loads and airflow demands of the racks; and, obstructions under and above the raised floor.

Often data center floor layouts are designed using empirical guidelines based on limited measurements. These guidelines do not consider the complex fluid dynamics processes that control the airflow and temperature distribution. Consequently, the layouts do not produce the expected flow rates and rack inlet temperatures, and must be modified. However, because modifications in one region of the floor influence airflow and temperatures throughout the floor, considerable trial and error is involved in identifying adjustments that will yield the desired changes in the rack inlet temperatures. This design practice is time consuming and expensive, and often the resulting arrangement is not optimum. Computational Fluid Dynamics (CFD) modeling or airflow modeling offers a more scientific and comprehensive design approach.

Computational simulation can be used for a quick setup of any proposed layout, any desired placement of CRAC units and perforated tiles, and any imagined failure scenario. The “computational” trial-and-error process is preferable for two reasons. First, performing a simulation is much faster and more economical than building an actual layout. Second, the computed results provide not only the flow rate distribution through perforated tiles and rack inlet temperatures  but also the underlying velocity, pressure, and temperature fields and thus explain the physics behind the results. This understanding is useful in guiding the computational trial-and-error process in the optimum direction.

• First CFD product dedicated to data centers
• Comprehensive, flexible, and robust
• Unparalleled ease of use
• Unmatched solution speed
• Unlimited technical support
• Modest computing resources
• Extensively validated

• Operating System. TileFlow runs under Microsoft Windows operating system.
• Graphics Card. A discrete graphics card with 512 MB of memory (1 GB or larger preferred) and OpenGL support.
• Memory. RAM of 2 GB is adequate for most data centers. For very large data centers, you will need additional RAM and a 64-bit operating system. Please contact us to discuss this further.
• Processor. The processor speed determines the solution time. The faster the processor, the better.

TileFlow uses efficient and accurate solution technique for calculating the three-dimensional flow field and temperature distribution in data centers.

• The technique of Computational Fluid Dynamics (CFD) is used for solving the equations governing the fluid flow and heat transfer in the data center.
• Use of advanced solution techniques allows calculation of airflow and temperature distribution in practical data centers within a short time on a PC.
• The calculated flow rates and rack inlet temperatures agree well (usually within 10%) with measured values.

The accuracy of the calculated results, the short turnaround times, and the ease-of-use make TileFlow an ideal tool for simulating cooling performance of data centers.

The deployment of temperature sensors is gaining popularity. The sensor temperatures can potentially be used to describe the thermal conditions in the data center and to make thermal-management decisions.

For these tasks, temperatures are needed throughout the data center. However, the number of sensor deployed is usually small. Thus, a interpolation scheme is needed to construct themperature distribution from limited number of sensor temperatures. Such a scheme is available in the sensor module in TileFlow.

The key features of this module are:

• Excel import for sensor positions and temperatures
• Visualization options for sensor positions and temperatures
• Sensor thermometer to read sensor temperatures
• Visualization tools for sensor-based temperature distribution