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Ground heat accumulation caused by imbalanced heating and cooling loads in a building can cause the heat-source temperature to increase as the operating age of a geothermal heat pump (GHP) system increases. An alternative system to improve upon this situation is the hybrid GHP system. This study reviews existing research on GHP systems and hybrid GHP systems, variable water flow (VWF) control, and coefficient of performance (COP) prediction. Generally, constant flow control is applied to the circulating pump to provide a flow rate according to the maximum load. The need for VWF control was identified because the hybrid GHP system is used mainly as a heating and cooling heat source system for partial loads rather than the entire building load. Previous studies on predicting the COPs of GHP systems developed prediction models by selecting input values based on mathematical models, collecting data through multiple measurement points, and utilizing data from production environments. The model can be limited by the field environment, and it is necessary to predict the COP using machine learning based on existing field monitoring data.

The installation and operation of geothermal systems increased due to the expectation of good cooling and heating performance due to stable heat source temperatures. In actual geothermal system operations, heat source temperature rises or falls due to an imbalance of heating and cooling energy usage. Problems of source side temperature result in reduced geothermal system performance. The purpose of this study is to develop hybrid geothermal system operation technology to stabilize temperature and improve system performance by utilizing auxiliary heat source system. The auxiliary heat source system is operated by comparing the performance when operating the geothermal heat pump system alone and the performance when operating the hybrid geothermal heat pump system. The performance of a hybrid geothermal system is determined by the circulating water temperature of the geothermal system and the circulating water temperature of the auxiliary heat source system. Hybrid geothermal heat pump system performance is predicted through numerical analysis and collection of hybrid geothermal system performance data at various temperature ranges through field test. An operating method was developed using the predicted performance as the changeover operating point of the hybrid geothermal heat pump system. When applying the development and operation technology, it handled about 11% more load than the existing geothermal system operation. The addition of an auxiliary heat source increases the initial investment cost compared to the existing geothermal system, but decreases energy consumption, confirming that the initial investment cost of 15.3 years is recovered.

AT-rich interactive domain 1A (ARID1A) is one of the most frequently mutated genes in hepatocellular carcinoma (HCC), but its clinical significance is not clarified. We aimed to evaluate the clinical significance of low ARID1A expression in HCC. By analyzing the gene expression data of liver from Arid1a-knockout mice, hepatic Arid1a-specific gene expression signature was identified (p < 0.05 and 0.5-fold difference). From this signature, a prediction model was developed to identify tissues lacking Arid1a activity and was applied to gene expression data from three independent cohorts of HCC patients to stratify patients according to ARID1A activity. The molecular features associated with loss of ARID1A were analyzed using The Cancer Genome Atlas (TCGA) multi-platform data, and Ingenuity Pathway Analysis (IPA) was done to uncover potential signaling pathways associated with ARID1A loss. ARID1A inactivation was clinically associated with poor prognosis in all three independent cohorts and was consistently related to poor prognosis subtypes of previously reported gene signatures (highly proliferative, hepatic stem cell, silence of Hippo pathway, and high recurrence signatures). Immune activity, indicated by significantly lower IFNG6 and cytolytic activity scores and enrichment of regulatory T-cell composition, was lower in the ARID1A-low subtype than ARID1A-high subtype. Ingenuity pathway analysis revealed that direct upstream transcription regulators of the ARID1A signature were genes associated with cell cycle, including E2F group, CCND1, and MYC, while tumor suppressors such as TP53, SMAD3, and CTNNB1 were significantly inhibited. ARID1A plays an important role in immune activity and regulating multiple genes involved in HCC development. Low-ARID1A subtype was associated with poor clinical outcome and suggests the possibility of ARID1A as a prognostic biomarker in HCC patients.

Accurate measurement of air flow rate is essential in automatic building control using the variable air volume (VAV) system. In order to solve the problems of the existing air flow measurement method and improve the accuracy of air flow control, this study developed a data-based multiple regression air flow prediction model. The independent variables used in the development of the predictive model were selected as the factors used for control and monitoring when operating with variable air flow rate in the existing air conditioning system. Data collection and correlation between independent variables and air flow rate of the terminal unit were analyzed. Using the IBM SPSS statistics version 25, an air flow rate prediction model was developed using multiple regression analysis. Reliability of model was evaluated by comparing the measured airflow. The relative error of −9.3% to 10.4% is shown when comparing the estimated air flow rate by the developed model with the measured air flow rate.

As the global energy trend continues, the importance of energy savings and efficient use is being emphasized, and the installation and operation of geothermal heat pump systems is increasing. In many buildings, where an actual geothermal heat pump system has been installed, problems of efficiency deterioration occur frequently because of the inefficient operation after installation of the heat pump system. The purpose of this study was to develop and verify the operating method for energy saving and performance improvement of multiple geothermal systems. A coefficient of performance (COP) prediction model using an artificial neural network for real-time COP predictions was developed. The operating method of a multi-geothermal heat pump system using a variable water flow rate control method and COP prediction model was developed. The geothermal heat pump system operates sequentially depending on the water flow rate of the circulation pump. The COP prediction model enabled real-time performance prediction during system operation. The circulation water flow rate was reduced by up to 29% compared to the existing operating method. Approximately 23% of the energy was saved. The COP system, including the consumption power of the circulation pump, was improved.

As policies for energy efficiency of buildings are being actively implemented, building energy performance improvement is urgently required. However, in Korea, information on measures and technologies for building energy efficiency is dispersed and concrete methods are not established, making it difficult to apply effective measures. Therefore, it is required to apply and evaluate energy efficiency measures through database construction integrating diverse information. In this study, the energy efficiency measures in the architectural sector that satisfy domestic legal standards are built. Because of the economic evaluation is necessary for the constructed alternatives, an economic efficiency database was established. The target building was set up, and energy efficiency measures were derived. In addition, a methodology that can induce energy efficient decision making of buildings was proposed, and the energy use evaluation and the economic analysis for each of the alternatives derived from applying the methodology to the target building were carried out. Furthermore, the optimal energy efficiency measures for the target building were suggested through the application of the decision-making process.