UPS (Uninterruptible Power Supply) units and batteries are essential subsystems in data centers or telecom industries to protect equipment from electrical power spikes, surges and power outages. UPS units handle electrical power and dissipate a large amount of heat, and possess a high efficiency. Therefore, cooling units (e.g., CRACs) are needed to manage the thermal reliability of this equipment. On the other hand, battery operating conditions and reliability are closely related to the ambient temperature according to battery manufacturers; reliability increases when the ambient room temperature is around 25ºC. This study analyzed different room configurations and scenarios using the commercial CFD software 6Sigma Room DCXTM. As a first approach, we evaluated the thermal behavior and cooling degradation using standard thermal performance metrics SHI (Supply Heat Index) and RHI (Return Heat Index). These are frequently implemented in data centers to measure the level of mixing between cold and hot air streams. The results from this evaluation showed that standard cooling practices are inefficient, as values for the two metrics differed considerably from industry recommendations. We also considered a metric from the second law of thermodynamics using exergy destruction. This technique allowed us to find the mechanisms that increase entropy generation the most, including viscous shear and air stream mixing. Reducing exergy destruction will result in lessening lost thermodynamic work and thus reduce energy required for cooling. Typically, UPS and batteries are located in different rooms due to the hydrogen generation by the batteries. The integration of both equipment in the same room is a new concept, and this study aims to analyze the thermal performance of the room. Adding controllability showed improvements by reducing the exergy destruction due to viscous dissipation while slightly increasing thermal mixing in the rooms. Ducting the return flows to avoid flow mixing increased pressure drop, but reduced heat transfer between the hot and cold air streams, which in turn, improved the thermal performance. In the study, we determined the optimal configuration and possible strategies to improve cooling while maintaining desirable battery temperatures. 
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                            Open-Source Wearable Sensors for Behavioral Analysis of Sheep Undergoing Heat Stress
                        
                    
    
            Heat stress (HS) negatively affects animal productivity and welfare. The usage of wearable sensors to detect behavioral changes in ruminants undergoing HS has not been well studied. This study aimed to investigate changes in sheep’s behavior using a wearable sensor and explore how ambient temperature influenced the algorithm’s capacity to classify behaviors. Six sheep (Suffolk, Dorset, or Suffolk × Dorset) were assigned to 1 of 2 groups in a cross-over experimental design. Groups were assigned to one of two rooms where they were housed for 20d prior to switching rooms. The thermal environment within the rooms was altered five times per period. In the first room, the temperature began at a thermoneutral level and gradually increased before decreasing. Simultaneously, in the second room, the temperature began at hot temperatures and gradually decreased before increasing again. Physiological responses (respiratory rate, heart rate, and rectal temperature) were analyzed using a linear mixed-effects model. A random forest algorithm was developed to classify lying, standing, eating, and ruminating (while lying and standing). Thermal stress shifted daily animal behavior budgets, increasing total time spent standing in hot conditions (p = 0.036). Although models had a similar capacity to classify behaviors within a temperature range, their accuracy decreased when applied outside that range. Although wearable sensors may help classify behavioral shifts indicative of thermal stress, algorithms must be robustly derived across environments. 
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                            - Award ID(s):
- 2106987
- PAR ID:
- 10469216
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Applied Sciences
- Volume:
- 13
- Issue:
- 16
- ISSN:
- 2076-3417
- Page Range / eLocation ID:
- 9281
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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