Experimentally Validated Computational Fluid Dynamics Model for Data Center With Active Tiles

Abstract

This paper presents an experimentally validated room-level computational fluid dynamics (CFD) model for raised-floor data center configurations employing active tiles. Active tiles are perforated floor tiles with integrated fans, which increase the local volume flowrate by redistributing the cold air supplied by the computer room air conditioning (CRAC) unit to the under-floor plenum. In a previous study [1], experiments were conducted to explore the potential of active tiles for economically and efficiently eliminating hot spots in data center. Our results indicated that active tiles, as the actuators closest to the racks, can significantly and quickly impact the local distribution of cooling resources. They could therefore be used in an appropriate control framework to rapidly mitigate hot spots, and maintain local conditions in an energy-efficient manner. The numerical model of the data center room operates in an under-floor supply and ceiling return cooling configuration and consists of one cold aisle with 12 racks arranged on both sides and three CRAC units sited around the periphery of the room. The commercial computational fluid dynamics (CFD) software package Future Facilities 6SigmaDCX [2], which is specifically designed for data center simulation, is used to develop the model. First, a baseline model using only passive tiles was developed and experimental data were used to verify and calibrate plenum leakage for the room. Then a CFD model incorporating active tiles was developed for two configurations: (a) a single active tile and 9 passive tiles in the cold aisle; and (b) an aisle populated with 10 (i.e., all) active tiles. The active tiles are modeled as a combination of a grill, fan elements and flow blockages to closely mimic the actual active tile used in the experimental studies. The fan curve for the active tile fans is included in the model to account for changes in flow rate through the tiles in response to changes in plenum pressure. The model with active tiles is validated by comparing the flow rate through the floor tiles, relative plenum pressure and rack inlet temperatures for selected racks with the experimental measurements. The predictions from the CFD model are found to be in good agreement with the experimental data, with an average discrepancy between the measured and computed values for total flow rate and rack inlet temperature less than 4% and 1.7 °C, respectively. These validated models were then used to simulate steady state and transient scenarios following cooling failure. This physics-based and experimentally validated room-level model can be used to predict temperature and flow distributions in a data center using active tiles. These predictions can then be used to identify the optimal number and locations of active tiles to mitigate hot spots, without adversely affecting other parts of the data center.

Genetic algorithm based cooling energy optimization of data centers

“…As mentioned previously, an ANN-based model for rapid temperature prediction in data center is used here. This model was developed using training data by conducting simulations using an experimentally validated CFD model for data center lab described in Section 2 (Athavale et al , 2018c, 2016). The model can be mathematically represented by the following equation: where T rack , inlet is the rack inlet temperature distribution, T a , ret and N CRAC are the return air temperature and blower speed cooling set-points of the CRAC unit, respectively and trueQ˙room is the IT heat load in the room.…”

Validated Thermal Air Management Simulations of Data Centers Using Remote Graphics Processing Units

“…It is then possible to determine airflow and thermal management issues, such as hotspots [7], which can be prevented without overcooling the entire data center and in addition, trends in the rack inlet temperature distributions can be captured. Moreover, transient simulations can be used to analyse different failure scenarios, such as determining the time until overheating of the IT equipment when either the chilled water pump or Computer Room Air Handling (CRAH) fans cease to work [10].…”

Küçük bir veri merkezinin iklimlendirme ünitelerine yönelik baypas yönteminin enerji ve ekonomik analizi

“…Athavale vd. [22] deneysel bir veri merkezinden elde ettiği sonuçlarla teyit edilmiş bir CFD modeli geliştirerek altında fan bulunan aktif menfezlerin plenum basıncı ve sızıntı akışına etkisi olduğunu tespit etmiştir. Ancak aktif menfezlerin klima BP yöntemini uygulamak amacıyla kullanılması ve bu durumlardaki sıcaklık dağılımları ilk olarak Erden [23] ve Ahmadi ve Erden [24] tarafından herhangi bir deneysel çalışma olmaksızın değerlendirilmiştir.…”