https://doi.org/10.6110/KJACR.2025.37.4.159

Ji Ho Park ; Yul Ho Kang ; Dong Hyun Shin ; Hyo Kyung Sung ; Young Chull Ahn

This study analyzed the pressure drop characteristics of finned-tube heat exchangers, a key component of EHP systems, during repeated cycles that included fouling acceleration, cleaning, and air-blowing drying. Each cycle consisted of 60 minutes of fouling acceleration under 1.5 m/s conditions, followed by 10 minutes of cleaning and 30 minutes of drying, and was repeated three times. The pressure drop characteristics were compared based on fin spacing and fin shape. The results indicated that for a fin spacing of 16 FPI, which is relatively narrow, the pressure drop increased more significantly during fouling acceleration with each cycle, and the recovery rate of the pressure drop after cleaning was lower. While the pressure drop for louvered fin heat exchangers remained elevated during the initial phase of fouling acceleration, corrugated fin heat exchangers exhibited a sharp increase in pressure drop near the end of this phase. Additionally, the rate of pressure drop increase after cleaning was higher for louvered fin heat exchangers. Regardless of fin spacing and shape, it was observed that as the cycles were repeated, residual particles on the surface formed aggregates, leading to a gradual increase in pressure drop, which was particularly pronounced during the third cycle.

https://doi.org/10.6110/KJACR.2025.37.4.167

Bo Ra Kim ; Bong Kyu Shin ; Jae Won Lee

This study evaluated the thermal management and CO₂ capture performance of LED heatsinks coated with multi-walled carbon nanotubes (MWCNT) and polyethyleneimine (PEI), demonstrating their potential for enhancing heatsink efficiency. By combining MWCNT, a physical adsorbent, with PEI, a chemical adsorbent, a porous material was created and applied to the heatsink surfaces. The heatsink containing 16 wt% MWCNT showed a maximum temperature 9.99% lower than that of an uncoated heatsink, indicating improved thermal management capabilities. The endothermic effect during CO₂ desorption significantly mitigated temperature increases, further enhancing the cooling effect. The heatsink with 12 wt% MWCNT-PEI achieved the highest CO₂ capture capacity at 4.25 mmol g?¹. This material effectively utilized heat from the LEDs to promote CO₂ desorption, reducing heat generation from the LEDs. The released CO₂ can be applied in areas such as indoor agriculture to optimize plant growth. These findings underscore the potential for integrating LED heatsink technology with CO₂ capture systems to enhance environmental sustainability and energy efficiency.

https://doi.org/10.6110/KJACR.2025.37.4.175

Jea Yoon Byun ; Tae Won Kim ; Eun Ji Choi ; Jin Woo Moon

Amid growing concerns about health risks, the demand for safer indoor air quality has significantly increased, necessitating advanced control solutions. Previous studies focused on ventilation, air purification control, and the proactive management of indoor air pollutants. However, most of these studies relied on computer simulations, with few applications in real-world environments. In response, this study developed an AI-based integrated control algorithm for indoor PM_2.5 and CO₂ using empirical data. The algorithm incorporates prediction models for indoor PM_2.5 and CO₂ based on artificial neural networks, enabling proactive control. It was applied in a living lab to validate its effectiveness in improving indoor air quality and reducing energy consumption. The integrated control algorithm demonstrated an average reduction of 19.69% in indoor PM_2.5 concentrations and 6.59% in CO₂ concentrations compared to the existing rule-based algorithm, while also decreasing energy consumption by 9.42%. Furthermore, the algorithm maintained indoor PM_2.5 and CO₂ concentrations below established criteria for a longer duration, confirming its superior performance. The integrated control algorithm developed in this study effectively achieved both indoor air quality management and energy consumption reduction, contributing to the sustainable development of building environment management and control.

https://doi.org/10.6110/KJACR.2025.37.4.185

Doyun Lee ; Sang Min Lee ; Eun Jung Choi

The rapid growth of the global population and urbanization has significantly reduced the availability of arable land, threatening food supply chains. In response, urban agriculture has emerged as a viable solution to address future food security challenges while promoting sustainability in urban settings. Among various urban agriculture models, building-integrated rooftop greenhouses (BiRTGs) present a promising approach by utilizing underused building spaces and enhancing energy efficiency through dynamic energy exchanges between buildings and greenhouses. This study developed a predictive model to optimize the operational control of BiRTGs, focusing on how greenhouse control variables impact the heating and cooling loads of both the building and the greenhouse. An artificial neural network (ANN) was used to simulate the complex thermal interactions between the two structures. The ANN models were trained with simulation data from a validated TRNSYS model, and their predictive accuracy was assessed using performance metrics outlined in ASHRAE Guideline 14. The results indicated that the ANN models achieved high accuracy in predicting the heating and cooling loads of BiRTGs, establishing a strong foundation for the development of real-time optimization algorithms for these systems.

https://doi.org/10.6110/KJACR.2025.37.4.196

Won-Jong Choi ; Wang-Je Lee ; Jongkyu Kim ; Jae-Weon Jeong ; Min-Hwi Kim

To address climate change and achieve carbon neutrality in the building sector, improving the efficiency of heating and cooling systems and integrating renewable energy sources are emerging as key technologies. Existing district heating systems face limitations in enhancing energy efficiency due to high thermal losses in pipelines. To overcome these challenges, a fifth-generation district heating and cooling system has been proposed. This study investigates the application of a fifth-generation district heating and cooling system to existing campus buildings with various load characteristics and evaluates their energy efficiency through simulations, comparing them to existing air-source heat pumps. Additionally, the study analyzes the improvement in self-consumption and self-sufficiency. The simulation results indicate that the self-consumption rate increased from 25% to 71% as the capacity of the roof photovoltaic system rose from 25 kWp to 100 kWp, and the balance between self-consumption and self-sufficiency increased from 39.2% to 61.2%.