A software tool has been developed that estimates the cooling performance of racks bounding a common cold aisle in a raised-floor data center. The tool predicts, in real time, the effect of row length, rack power and airflow distribution, and perforated tile flow rate on cooling performance. For any scenario of interest, airflow patterns within the cold aisle are computed based on the superposition of elemental airflow patterns that have been determined in advance (“offline”) from computational fluid dynamics (CFD) simulations and stored as empirical curve fits. Rack-cooling performance is based on the recirculation index (RI), which is defined as the percentage of airflow ingested by a rack, which originated outside the cold aisle.

This paper discusses the algorithm upon which the software tool is based and provides examples of its application. Novel aspects of this work include the real-time prediction of rack-cooling performance, the definition and use of the recirculation index as a cooling performance metric, and the computation of cold-aisle airflow patterns based on superposition and empirical correlations.