Data Center Transient Flow Analysis Using Proper Orthogonal Decomposition

Abstract

Real-time analysis of the transient temperature distribution and flow field in a data center is not possible using well-resolved computational fluid dynamics (CFD) simulations. Reduced order models must be used to predict the optimum operating and control conditions to achieve better energy-efficiency. Here, the proper orthogonal decomposition (POD) method is used to model transient behavior of a simple hot aisle/cold aisle data center configuration. Verified CFD simulation results were used to generate snapshots for building a reduced order POD model corresponding to transient variation of the computer room air conditioner (CRAC) operating conditions. Good agreement is achieved between the CFD and reduced order model predictions for the evolving flow structure over a range of CRAC supply operating conditions. Once constructed, the computational time required to obtain the POD results for the transient response is considerably reduced compared to the CFD simulations. The advantages and disadvantages of the POD method for this type of transient behavior are discussed, and recommendations are made on using this type of compact modeling approach to develop a real-time predictive tool for data center design and control to enhance energy efficiency.