From Chip to Cooling Tower Data Center Modeling:

The chiller cooled data center environment consists of many interlinked elements that are usually treated as individual components. This chain of components and their influences on each other must be considered in determining the benefits of any data center design and operational strategies seeking to improve efficiency, such as temperature controlled fan algorithms. Using the models previously developed by the authors, this paper extends the analysis to include the electronics within the rack through considering the processor heat sink temperature. This has allowed determination of the influence of various cooling strategies on the data center coefficient of performance. The strategy of increasing inlet aisle temperature is examined in some detail and found not to be a robust methodology for improving the overall energy performance of the data center, while tight temperature controls at the chip level consistently provide better performance, yielding more computing per watt of cooling power. These findings are of strong practical relevance for the design of fan control algorithms at the rack level and general operational strategies in data centers. Finally, the impact of heat sink thermal resistance is considered, and the potential data center efficiency gains from improved heat sink designs are discussed

HT-FED2004-56528 DEVELOPMENT AND EXPERIMENTAL VALIDATION OF AN EXERGY-BASED COMPUTATIONAL TOOL FOR DATA CENTER THERMAL MANAGEMENT

ABSTRACT The recent miniaturization of electronic devices and compaction of computer systems will soon lead to data centers with power densities of the order of 300 W/ft 2 . At these levels, traditional thermal management techniques are unlikely to suffice. To enable the dynamic smart cooling systems necessary for future data centers, an exergetic approach based on the second law of thermodynamics has recently been proposed. However, no experimental data related to this concept is currently available. This paper discusses the development and subsequent validation of an exergy-based computer model at an instrumented data center in Palo Alto, California. The study finds that when appropriately calibrated, such a computational tool can successfully predict information about local and global thermal performance that cannot be perceived intuitively from traditional design methods. Further development of the concept has promising potential for efficient data center thermal management

Guidelines for developing efficient thermal conduction and storage models within building energy simulations

Improving building energy efficiency is of paramount importance due to the large proportion of energy consumed by thermal operations. Consequently, simulating a building's environment has gained popularity for assessing thermal comfort and design. The extended timeframes and large physical scales involved necessitate compact modelling approaches. The accuracy of such simulations is of chief concern, yet there is little guidance offered on achieving accurate solutions whilst mitigating prohibitive computational costs. Therefore, the present study addresses this deficit by providing clear guidance on discretisation levels required for achieving accurate but computationally inexpensive models. This is achieved by comparing numerical models of varying discretisation levels to benchmark analytical solutions with prediction accuracy assessed and reported in terms of governing dimensionless parameters, Biot and Fourier numbers, to ensure generality of findings. Furthermore, spatial and temporal discretisation errors are separated and assessed independently. Contour plots are presented to intuitively determine the optimal discretisation levels and time-steps required to achieve accurate thermal response predictions. Simulations derived from these contour plots were tested against various building conditions with excellent agreement observed throughout. Additionally, various scenarios are highlighted where the classical single lumped capacitance model can be applied for Biot numbers much greater than 0.1 without reducing accuracy

Universal approach to modelling multi-layer structures in building energy simulations

Building energy simulations have found widespread use as decision-making tools for determining design and retrofitting actions. Despite their popularity, there exists a well-reported issue regarding the numerical treatment of structural thermalstorage components in these models. The optimal means of discretising multi-layer structures is complicated by the different thermo-physical properties, material configurations and boundary conditions encountered within building energy models. This paper addresses this information gap by proposing a methodology that can be universally applied to all multi-layer structures, ensuring accurate predictions while avoiding excessive computational cost. Governing dimensionless quantities of Biot and Fourier numbers are utilised within the discretisation process, making the methodology equally applicable to all materials. The presented methodology also accounts for the configuration of materials within multi-layer structures when assigning discretisation levels, leading to nodes being distributed in accordance with expected thermal gradients. The proposed discretisation methodology has been examined for a number of boundary conditions and wall types with excellent prediction accuracy achieved throughout. Additionally, the utility of resistance-only layers has been explored as a means of increasing computational efficiency. This highlighted the importance of considering both layer position and local thermal properties when simulating multi-layer structures