Mobile QR Code QR CODE : Korean Journal of Air-Conditioning and Refrigeration Engineering
Korean Journal of Air-Conditioning and Refrigeration Engineering

Korean Journal of Air-Conditioning and Refrigeration Engineering

ISO Journal TitleKorean J. Air-Cond. Refrig. Eng.
Open Access Monthly
  • ISSN : 1229-6422 (Print)
  • ISSN : 2465-7611 (Online)

해수파울링이 판형 열교환기 성능에 미치는 실험적 연구 Experimental Study on the Effects of Seawater Fouling on a Plate-Frame Heat Exchanger

https://doi.org/10.6110/KJACR.2018.30.5.205

Won Keun Baik ; Jaehyeok Heo ; Rin Yun

Two plate type heat exchangers were tested. One was under fouling conditions from seawater and the other was under clean condition. Overall heat coefficient, heat transfer coefficient, fouling thermal resistance, and pressure drop of the heat exchangers were obtained. Effects of fouling on plate type heat exchangers were then investigated. The test heat exchanger, a differential pressure transducer, and two mass flow meters were installed. The working fluid used in the experiment was water on the seawater side and brine on the other side of the heat exchanger. Operational temperatures for seawater side were 10℃, 20℃, and 30℃. The brine side temperatures were 5℃, 15℃, and 25℃. Operational flow rates at both sides were 20-30 lpm. The overall heat transfer coefficient for seawater side was increased by an average of 21% in clean condition without fouling. Pressure drop was less than 2 kPa with temperature variation. However, pressure drop for seawater side was increased four times under fouling conditions.

국가지정 음압격리 입원치료병상의 슬라이딩 도어의 개폐속도 및 의료진의 이동속도에 따른 오염공기 유출에 관한 해석적 연구 A Numerical Study on Contaminated Air Outflows according to Sliding Door Closing & Opening Speed and Medical workers' Moving Speed of National Negative Pressure Isolation Units

https://doi.org/10.6110/KJACR.2018.30.5.211

Du Ru Na Lee ; Jin Kwan Hong

To prevent secondary infections in national inpatient isolation units, this study conducted flow analysis for opening/closing speeds of sliding doors of negative pressure isolation rooms and medical workers' moving speeds among various factors that might cause outflow of contaminated air from negative pressure isolation rooms to the outside. Subject situations were divided into cases where medical workers' moving speed remained the same while opening/closing speed of doors changed and cases where opening/closing speed of doors changed while medical workers' moving speed remained the same to figure out internal flow characteristics of negative pressure isolation rooms and anteroom. Three speeds were designated for each of sliding door opening/closing speeds and medical workers' moving speeds. Results showed that the outflow of contaminated air decreased as sliding door opening/closing speeds increased and as medical workers' moving speeds decreased. Results of this study can be used as evidentiary material to set standard operation procedures to minimize diffusion of contaminated air where national inpatient isolation units are designed and operated.

간이수식을 통한 태양광모듈에 발생하는 그림자 예측에 관한 연구 A Study on Shadow Prediction in Photovoltaic Module by Simplified Equations

http://dx.doi.org/10.6110/KJACR.2018.30.5.222

Jung Uk Choi ; Sung Woo Cho

The objective of this study was to develop simplified equation for shadow ratio of photovoltaic module using field measuring data to affect photovoltaic power. Comparison between simplified equation results and Ecotect program simulation on 3 kW photovoltaic on house roof top at solstice in Changwon district showed 2% errors. Shadow ratio was increased with increasing number of floors. The shadow is generated until 6 floors at 1 m of the distance between building and photovoltaic module, until 8 floors at 2 m of the distance between building and photovoltaic module, and until 8 floors at 3 m of the distance between building and photovoltaic module. The shadow generation time was decreased when the distance between building and photovoltaic module was increased. The shadow generation and shadow ratio are high at noon.

건물 직하 유닛형 지중열교환기의 채열 성능 및 도입 타당성 분석 Performance and Feasibility Analysis on the Unit-Type Ground Heat Exchanger under a Building

http://dx.doi.org/10.6110/KJACR.2018.30.5.228

Jae Min Kim, Sangmu Bae, Yu Jin Nam

Ground source heat pump (GSHP) systems using annually stable underground temperature have higher coefficient of performance than conventional air-source systems. However, it is difficult to install GSHP system in small-scale building because the initial cost including boring and heat exchanger is relatively expensive compared to other construction cost. To reduce installation cost of GSHP system, a low-depth unit-type ground heat exchanger (GHX) was developed for small-scale building. In this study, numerical simulation of low-depth unit-type GHX was conducted according to arrangement type and installation depth. As a result, heat exchange rates of parallel type (Case 1-1) and serial type (Case 1-4) were 12.27 W/m and 9.10 W/m, respectively. Based on simulation results, payback period of GSHP system was compared to that of conventional air-source system. Vertical closed-loop type recouped the initial installation cost in 14 years while low-depth unit-type did it in 9 years. Results of feasibility analysis indicated that low-depth unit-type GHX could reduce the initial installation cost of the GSHP system. Thus, it could be sufficiently economical for small-scale buildings.

냉동고 작동오류 진단방법 개발 Developing Operation Fault Detection for Freezer : A Comparative Study of Machine Learning Algorithms

https://doi.org/10.6110/KJACR.2018.30.5.237

Bok Han Kim ; Seung Yeon Choi ; Sean Hay Kim

This study aims to diagnose operation faults of freezer such as door left open by mistakes and refrigerant leaks by using machine learning approach. Machine learning algorithms can take training raw data and then output trained model that contains prediction rules. Active power of freezer, laboratory ambient temperature, and freezer inside surface temperature are selected as monitoring variables. Heat capacity, refrigerant mass, and door opening also varied upon actual operation scenarios. About 190,000 raw data were collected. We selected five machine learning algorithms: SVM, DT, KNN, ANN, and Naive Bayesian Classification. Kernel-based classification algorithms such as KNN and SVM were found to have better performance in diagnosing operation faults of freezer than other machine learning algorithms.