Ground source heat pump (GSHP) system is highly efficient and environment-friendly and supplies heating, cooling and hot water to buildings. For an optimal design of the GSHP system, the ground thermal properties should be determined to estimate the heat exchange rate between ground and borehole heat exchangers (BHE) and the system performance during long-term operating periods. However, the process increases the initial cost and construction period, which causes the system to be hindered in distribution. On the other hand, much research has been applied to the artificial neural network (ANN) to solve problems based on data efficiently and stably. This research proposes the predictive performance model utilizing ANN considering local characteristics and weather data for the predictive performance model. The ANN model predicts the entering water temperature (EWT) from the GHEs to the heat pump for the modular GHEs, which were developed to reduce the cost and spatial disadvantages of the vertical-type GHEs. As a result, the temperature error between the data and predicted results was 3.52%. The proposed approach was validated to predict the system performance and EWT of the GSHP system.

Secondary batteries used in electric vehicles have a potential risk of ignition and explosion. Various safety measures are being taken to prevent these risks. A numerical study was performed using a computational fluid dynamics code on the cases where pressure relief vents that can reduce the blast overpressures of batteries were installed in the through-compression test room, short-circuit drop test room, combustion test room, and immersion test room in facilities rleated to battery used in electric vehicles. This study was conducted using the weight of TNT equivalent to the energy release from the battery, where the the thermal runaway energy was set to 324,000 kJ for the capacity of the lithium-ion battery was 90 kWh and the state of charge (SOC) of the battery of 100%. The explosion energy of TNT (△H_TNT) generally has a range of 4,437 to 4,765 kJ/kg, and a value of 4,500 kJ/kg was thus used in this study. The dimensionless explosion efficiency coefficient was defined as 15% assuming the most unfavorable condition, and the TNT equivalent mass was calculated to be 11 kg. The internal explosion generated in a test room shows the very complex propagation behavior of blast waves. The shock wave generated after the explosion creates reflected shock waves on all inner surfaces. If the internally reflected shock waves are not effectively released to the outside, the overpressures inside are increased or maintained due to the continuous reflection and superposition from the inside for a long time. Blast simulations for internal explosion targeting four test rooms with pressure relief vents installed were herein conducted. It was found that that the maximum blast overpressure of 34.69 bar occurred on the rear wall of the immersion test room, and the smallest blast overpressure was calculated to be 3.58 bar on the side wall of the short-circuit drop test room.

In this study, comparative analysis of energy performance in Taebaek city, a test area, by applying hydrothermal, geothermal source and hybrid heat pump system to office, school and smart farms with different internal heat loads. The conclusion is as follows. In the load characteristics by use of buildings, it was found that office had a large cooling load compared to heating load, school had a large heating load compared to cooling load, and smart farm had only cooling load year-round. Performance analysis of the heat pump system in office shows that the cooling COP of the hydrothermal source is 5.12% and the heating COP is 3.22% lower based on the geothermal source, the cooling COP of the hybrid is 0.41% higher, and the heating COP is the difference in performance appeared sparsely. The performance analysis of the heat pump system in school showed that the cooling COP of the hydrothermal source was 10.44% and the heating COP 3.22% lower based on the geothermal source, and the performance difference between the hybrid cooling and heating COP was insignificant. Heat pump system performance analysis in smart farm only occurred with cooling load. Based on geothermal sources, the cooling COP of the hydrothermal source was 46% and the cooling COP of the hybrid was 19.65%, respectively.