A Comparison of Parametric and Multivariable Optimization Techniques in a Raised Floor Data Center

Abstract

It is well known that the flow distribution in data centers can be effected by a variety of parameters such as rack and computer room air conditioning (CRAC) positions, raisedfloor height, ceiling height, and percentage opening of perforated tiles. In the present paper, numerical simulations are conducted to optimize the layout of a raisedfloor data center with respect to these parameters. Two different approaches have been used: parametric optimization; and a multivariable approach using response surface optimization. In the parametric optimization procedure, the data center is optimized with respect to the maximum temperature in the room. While in the multivariable approach, a cost function is constructed from all the rack inlet temperatures and is minimized. The results show that the multivariable approach is computationally economical and the optimized layout gives a better thermal performance compared to that of parametric optimization.