Reduced Order Modeling Based Energy Efficient and Adaptable Design

In this chapter, the sustainable and reliable operations of the electronic equipment in data centers are shown to be possible through a reduced order modeling based design. First, the literature on simulation-based design of data centers using computational fluid dynamics/heat transfer (CFD/HT) and low-dimensional modeling are reviewed. Then, two recent proper orthogonal decomposition (POD) based reduced order thermal modeling methods are explained to simulate multiparameter-dependent temperature field in multiscale thermal/fluid systems such as data centers. The methods result in average error norm of ~6% for different sets of design parameters, while they can be up to ~250 times faster than CFD/HT simulation in an iterative optimization technique for a sample data center cell. The POD-based modeling approach is applied along with multiobjective design principles to systematically achieve an energy efficient, adaptable, and robust thermal management system for data centers. The framework allows for intelligent dynamic changes in the rack heat loads, required cooling airflow rates, and supply air temperature based on the actual momentary center heat loads, rather than planned occupancy, to extend the limits of air cooling and/or increase energy efficiency. This optimization has shown energy consumption reduction by 12–46% in a data center cell.