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식물 축적량 기반 누출사고 시뮬레이션의 대기 중 불화수소 농도 추정에 관한 연구
양시엽(Seeyub Yang),전정우(Jeongwoo Jeon),이용석(Yongseok Lee),이건학(Gunhak Lee),한종훈(Chonghun Han) 한국위험물학회 2015 한국위험물학회지 Vol.3 No.1
This research deals with the Gumi Hydrogen Fluoride accidental release on September 27th, 2012. When hydrogen fluoride cloud is mixed with the atmosphere, HF can form oligomer up to octamer. To model complex phenomena of atmospheric hydrogen fluoride dispersion, this research used PHAST. Fluoride accumulation by dry deposition on the vegetation data after the accidental release is used for estimation of the ambient fluoride concentration at the time of the accident. Then, estimated concentration is used to validate the dispersion simulation. Geometric mean bias for experiment data and simulation is 1.22, which is in the acceptable range of the model since prediction of the PHAST tends to be underestimated.
이산화탄소 수송을 위한 압축 및 액화 공정 설계 및 비용 평가
양시엽 ( See Yub Yang ),이웅 ( Ung Lee ),임영섭 ( Young Sub Lim ),정영수 ( Yeong Su Jeong ),김정남 ( Jeong Nam Kim ),이차섭 ( Chi Seob Lee ),한종훈 ( Chong Hun Han ) 한국화학공학회 2012 Korean Chemical Engineering Research(HWAHAK KONGHA Vol.50 No.6
이산화탄소 포집 및 저장 기술 중에서 수송 단계를 위한 전처리 과정인 초임계 압축 및 액화 공정에 대해서 압축 방 법에 따른 에너지와 그 때의 비용의 평가가 이루어졌다. 이산화탄소를 초임계상까지 직접 압축하는 경우(공정 1-1), 액 화 후 펌프로 초임계상을 만드는 경우(공정 1-2), 이산화탄소의 가압 팽창으로 액화하는 경우(공정 2), 다른 냉매를 사 용하면서 그 냉매를 가압, 팽창으로 얻는 경우(공정 3-1), 냉매를 흡수 냉각법으로 얻는 경우(공정 3-2), 캐스케이드 방법을 사용한 경우(공정 4)에 대해서 각각 공정 모사되었으며 그 때의 비용이 평가되었다. 비용은 $4~7/ton으로 추정된다. Energy and cost analysis of the preprocessing for carbon capture and storage transportation such as supercritical compression and liquefaction is done using chemical simulation model. Direct compression to supercritical phase (process 1-1), liquefaction and pumping (process 1-2), carbon dioxide compression and expansion as a refrigerant itself (process 2), usage of other refrigerant with compression and expansion (process 3-1), with absorption chiller (process 3-2), cascade refrigeration (process 3-2) have been simulated and evaluated. The specific cost is about 4 to 7 $/ton.
Development of surrogate model using CFD and deep neural networks to optimize gas detector layout
전경우,양시엽,강동주,나종걸,이원보 한국화학공학회 2019 Korean Journal of Chemical Engineering Vol.36 No.3
To reduce damage arising from accidents in chemical processing plants, detection of the incident must be rapid to mitigate the danger. In the case of the gas leaks, detectors are critical. To improve efficiency, leak detectors must be installed at locations after considering various factors like the characteristics of the workspace, processes involved, and potential consequences of the accidents. Thus, the consequences of potential accidents must be simulated. Among various approaches, computational fluid dynamics (CFD) is the most powerful tool to determine the consequences of gas leaks in industrial plants. However, the computational cost of CFD is large, making it prohibitively difficult and expensive to simulate many scenarios. Thus, a deep-neural-network-based surrogate model has been designed to mimic FLACS (FLame ACceleration Simulator), one of the most important programs in the modeling of gas leaks. Using the simulated results of a proposed surrogate model, a sensor allocation optimization problem was solved using mixed integer linear programming (MILP). The optimal solutions produced by the proposed surrogate model and FLACS were compared to verify the efficacy of the proposed surrogate model.