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An in-rack cooling system connected to an external vapor recompression loop can be an economical solution to harness waste heat recovery in data centers. Validated subsystem-level models of the thermosyphon cooling and recompression loops (evaporator, heat exchangers, compressor, etc.) are needed to predict overall system performance and to perform design optimization based on the operating conditions. This paper specifically focuses on the model of the evaporator, which is a finned-tube heat exchanger incorporated in a thermosyphon cooling loop. The fin-pack is divided into individual segments to analyze the refrigerant and air side heat transfer characteristics. Refrigerant flow in the tubes is modeled as 1-D flow scheme with transport equations solved on a staggered grid. The air side is modeled using differential equations to represent the air temperature and humidity ratio and to predict if moisture removal will occur, in which case the airside heat transfer coefficient is suitably reduced. The louver fins are modeled as individual hexagons and are treated in conjunction with the tube walls. A segment-by-segment approach is utilized for each tube and the heat exchanger geometry is subsequently evaluated from one end to the other, with air property changes considered for each subsequent row of tubes. Model predictions of stream outlet temperature and pressure, refrigerant outlet vapor quality and heat exchanger duty show good agreement when compared against a commercial software.

 

This paper is focused on the modeling of a brazed plate heat exchanger (BPHE) for a novel in-rack cooling loop coupled with heat recovery capability for enhanced thermal management of datacenters. In the proposed technology, the BPHE is acting as a condenser, and the model presented in this study can be applied in either the cooling loop or vapor recompression loop. Thus, the primary fluid enters as either superheated (in the vapor recompression loop) or saturated vapor (in the cooling loop), while the secondary fluid enters as a sub-cooled liquid. The model augments an existing technique from the open literature and is applied to condensation of a low-pressure refrigerant R245fa. The model assumes a two-fluid heat exchanger with R245fa and water as the primary and secondary fluids, respectively, flowing in counterflow configuration; however, the model can also handle parallel flow configuration. The 2-D model divides the heat exchanger geometry into a discrete number of slices to analyze heat transfer and pressure drops (including static, momentum and frictional losses) of both fluids, which are used to predict the exit temperature and pressure of both fluids. The model predicts the exchanger duty based on the local energy balance. The predicted values of fluid output properties (secondary fluid temperature and pressure, and primary fluid vapor quality and pressure) along with heat exchanger duty show good agreement when compared against a commercial software.

 

This paper introduces a novel thermal management solution coupling in-rack cooling and heat recovery system. System-level modeling capabilities are the key to design and analyze thermal performance for different applications. In this study, a semi-empirical model for a hermetically sealed scroll compressor is developed and applied to different scroll geometries. The model parameters are tuned and validated such that the model is applicable to a variety of working fluids. The identified parameters are split into two groups: one group is dependent on the compressor geometry and independent of working fluid, whereas the other group is fluid dependent. By modifying the fluid-dependent parameters using the specific heat ratios of two refrigerants, the model shows promise in predicting the refrigerant mass flow rate, discharge temperature and compressor shaft power of a third refrigerant. Here, the approach has been applied using data for two refrigerants (R22 and R134a) to achieve predictions for a third refrigerant’s (R407c) mass flow rate, discharge temperature, and compressor shaft power, with normalized root mean square errors of 0.01, 0.04 and 0.020, respectively. The normalization is performed based on the minimum and maximum values of the measured variable data. The technique thus presented in this study can be used to accurately predict the primary variables of interest for a scroll compressor running on a given refrigerant for which data may be limited, enabling component-level design or analysis for different operating conditions and system requirements.

 

Two self-developed control schemes, ON/OFF and supervisory control and data acquisition (SCADA), were applied on a hybrid evaporative and direct expansion (DX)-based model data center cooling system to assess the impact of controls on reliability and energy efficiency. These control schemes can be applied independently or collectively, thereby saving the energy spent on mechanical refrigeration by using airside economization and/or evaporative cooling. Various combinations of system-level controls and component-level controls are compared to a baseline no-controls case. The results show that reliability is consistently met by employing only sophisticated component-level controls. However, the recommended conditions are met approximately 50% of the simulated time by employing system-level controls only (i.e., SCADA) but with a reduction in data center cooling system power usage effectiveness (PUE) values from 3.76 to 1.42. Moreover, the recommended conditions are met at all averaged times with an even lower cooling system PUE of 1.13 by combining system-level controls only (SCADA and ON/OFF controls). Thus, the study introduces a simple method to compare control schemes for reliable and energy-efficient data center operation. The work also highlights a potential source of capital expenses and operating expenses savings for data center owners by switching from expensive built-in component-based controls to inexpensive, yet effective, system-based controls that can easily be imbedded into existing data center infrastructure systems management.