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열교환기 내장형 어큐뮬레이터의 성능특성에 관한 해석적 연구
최광민(Kwangmin Choi),강훈(Hoon Kang),김용찬(Yongchan Kim) 대한기계학회 2005 대한기계학회 춘추학술대회 Vol.2005 No.11
An AHX(Accumulator Heat eXchanger) consists of a commercial accumulator and an inner heat exchanger located inside of the accumulator. The AHX is used in multi air-conditioners to assure the liquid-phase refrigerant entering into the expansion device, which is achieved by heat transfer between the refrigerant leaving the evaporator and the refrigerant leaving the condenser. In this study, a CFD simulation on the heat transfer and pressure drop in the AHX using R-22 as a working fluid, is conducted. The simulation was performed with various accumulator inner volume and inner heat exchanger length to show geometrical effects on the heat transfer and pressure drop characteristics.
전자산업에서 사용하는 화학물질의 독성예측을 위한 QSAR 접근법
김지영,최광민,김관식,김동일,Kim, Jiyoung,Choi, Kwangmin,Kim, Kwansick,Kim, Dongil 한국환경보건학회 2014 한국환경보건학회지 Vol.40 No.2
Objectives: It is necessary to apply quantitative structure activity relationship (QSAR) for the various chemicals with insufficient toxicity data that are used in the workplace, based on the precautionary principle. This study aims to find application plan of QSAR software tool for predicting health hazards such as genetic toxicity, and carcinogenicity for some chemicals used in the electronics industries. Methods: Toxicity prediction of 21 chemicals such as 5-aminotetrazole, ethyl lactate, digallium trioxide, etc. used in electronics industries was assessed by Toxicity Prediction by Komputer Assisted Technology (TOPKAT). In order to identify the suitability and reliability of carcinogenicity prediction, 25 chemicals such as 4-aminobiphenyl, ethylene oxide, etc. which are classified as Group 1 carcinogens by the International Agency for Research on Cancer (IARC) were selected. Results: Among 21 chemicals, we obtained prediction results for 5 carcinogens, 8 non-carcinogens and 8 unpredictability chemicals. On the other hand, the carcinogenic potential of 5 carcinogens was found to be low by relevant research testing data and Oncologic TM tool. Seven of the 25 carcinogens (IARC Group 1) were wrongly predicted as non-carcinogens (false negative rate: 36.8%). We confirmed that the prediction error could be improved by combining genetic toxicity information such as mutagenicity. Conclusions: Some compounds, including inorganic chemicals and polymers, were still limited for applying toxicity prediction program. Carcinogenicity prediction may be further improved by conducting cross-validation of various toxicity prediction programs, or application of the theoretical molecular descriptors.