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1. Introduction
About 2 per cent of the total electricity generated is consumed by data centers in the USA (Brown et al., 2008). The power consumption in data centers is dominated by the servers and cooling units (Koomey, 2011). Server power consumption is vital, and hence cannot be minimized but cooling unit consumption can be reduced. Cooling units of raised floor plenum (RFP) data centers provide airflow to the servers. Data center environment involves the circulation of hot and cold air flows that make the system highly dynamic. An efficient way to understand these dynamics is through the response experiments and Computational Fluid Dynamics (CFD) modeling.
1.1 Literature background
RFP data centers have a distinctive pattern of airflow to supply the cold air to each server in the rack. Computer Room Air Conditioning (CRAC) units provide cold air to the server racks via perforated tiles on the plenum. Heated air collected toward the ceiling from the rear side of the racks and directed at the top of CRAC. This airflow pattern creates alternate cold and hot aisle zones inside RFP data center. Because of such pattern, there are chances of recirculation of hot air into cold aisle, and hence a proper ceiling is necessary (Makwana et al., 2014). Therefore, various parameters such as rack inlet–outlet temperatures, tile airflow rates and CRAC air supply temperature have been studied for different data center configurations using steady-state CFD analysis (Schmidt et al., 2005; Shrivastava et al., 2005; Fulpagare and Bhargav, 2015; Fulpagare et al., 2015; Zhang et al., 2008; Rambo and Joshi, 2003; Bhopte et al., 2006).
Thermal conditions within a data center are dynamic due to many parameters and hence cannot be captured through steady-state analysis alone (Jonas et al., 2012). The first transient numerical analysis was performed by Beitelmal and Patel (2007) to study the impact of CRAC failure on the temperature variations within the data center. The thermal mass characteristics with detailed transient boundary conditions for data center system-level simulations were highlighted by Ibrahim et al. (2012, 2010). However, the airflow rate entering rack cabinet can vary based on the pressure difference across the servers. This can be quantified based on the characterization of server fans (Nemati