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Massive data center (DC) energy demands lead to water consumption concerns. This study quantifies on-site and off-site DC water consumption and its holistic impact on regional water availability. This study proposes a new DC sustainability metrics, Water Scarcity Usage Effectiveness (WSUE), that captures the holistic impacts of water consumption on regional water availability by considering electricity and water source locations and their associated water scarcity. We examine the water consumption of various DC cooling systems by tracking on-site water consumption along with the direct and indirect water transfers associated with electricity transmission at the contiguous U.S. balancing authority (BA) level. This study then applies the WSUE metric for different DC cooling systems and locations to compare the holistic water stress impact by large on-site water consuming systems (e.g., via cooling towers) versus systems with higher electrical consumption and lower on-site water consumption such as the conventional use of computer room air conditioner (CRAC) units. Results suggest that WSUE is strongly dependent on location, and a water-intensive cooling solution could result in a lower WSUE than a solution requiring no or less on-site water consumption. The use of the WSUE metric aids in DC siting decisions and DC cooling system design from a sustainability point of view. 

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 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. 

Predicting the embodied scope 3 carbon dioxide equivalent (CO2e) emissions from purchased electricity for end users in the United States is challenging due to electricity transmission within interconnected power grids. Existing methods only focus on large aggregation areas, thereby ignoring potentially significant emission factor (EF) variations, so this study proposes a novel method to translate the CO2e emissions from the balancing authority (BA)-level to the county-level by utilizing explicit finite-difference theory for electricity flow predictions, and then employing economic input–output theory to evaluate the scope 3 embodied lifecycle CO2e emissions. Results show that the generation-based EFs at the BA-level range from 0.007 to 0.905 MT-CO2e/MWh with a mean value of 0.400 MT-CO2e/MWh and a standard deviation of 0.229 MT-CO2e/MWh. The consumption-based EFs at the BA-level range from 0.008 to 0.836 MT-CO2e/MWh with a mean value of 0.378 MT-CO2e/MWh and a standard deviation of 0.019 MT-CO2e/MWh. Results also show that sixteen BA consumption-based EFs deviate by more than 20% compared to their generation-based EFs, which indicates the significance of accounting for electricity interchanges in emissions quantification processes. A larger range of possible consumption-based EFs is revealed at the county-level: 0.007 to 0.902 MT-CO2e/MWh, with a mean value of 0.452 MT-CO2e/MWh and a standard deviation of 0.123 MT-CO2e/MWh. Results also indicate significant variations in EFs of counties within each BA: 20 BAs have county-level EFs range greater than 0.1 MT-CO2e/MWh, 13 BAs have county-level EFs range greater than 0.2 MT-CO2e/MWh and 6 BAs have county-level EFs range beyond 0.3 MT-CO2e/MWh.