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Received January 8, 2014
Accepted March 18, 2014
- This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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잠재적 폭발 위험성을 고려한 단단 혼합냉매 LNG 공정의 설계 변수 최적화
Optimization of Single-stage Mixed Refrigerant LNG Process Considering Inherent Explosion Risks
서울대학교 화학생물공학부, 151-744 서울시 관악구 관악로 1 1한국교통대학교 화공생물공학과, 380-702 충청북도 충주시 대학로 50
School of chemical and biological engineering, 1 Gwanak-ro., Gwanak-gu, Seoul 151-744, Korea 1Department of Chemical and Biological Engineering, Korea National University of Transportation, 50 Daehak-ro, Chungju-si, Chungbuk 380-702, Korea
Korean Chemical Engineering Research, August 2014, 52(4), 467-474(8), 10.9713/kcer.2014.52.4.467 Epub 30 July 2014
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Abstract
화학공정의 기초설계는 물질수지와 열수지 계산을 기초로 공정의 경제성을 확보하고 주어진 조건 내에서 원하는 제품을 생산 가능하도록 한다. 이 단계를 통해 공정은 사용될 물질과 반응, 설비의 구조와 운전 조건 등이 결정되기 때문에 이후 바뀔 수 없는 고유한 특성을 갖게 된다. 고유한 특성은 뛰어난 경제성일 수도 있지만 다양한 잠재적 위험요인을 내포하는 것일 수도 있다. 따라서 기초설계를 위한 공정모사와 정량적 위험성 평가 기법의 통합을 통해 보다 안전하면서도 경제적인 공정을 설계하는 것이 중요하다. 본 논문에서는 LNG 액화공정을 Aspen HYSYS를 이용하여 모사하고, 폭발 사고에 대한 정량적 위험성 평가를 수행함으로써 잠재적 위험성을 최소화하면서도 경제성을 고려하도록 설계변수를 결정하였다. 이를 위해 확률적 최적화 방법론을 이용하여 Aspen HYSYS의 최적화 한계를 극복하였고,_x000D_
Aspen HYSYS와 Matlab의 연동을 통해 정량적 위험성 평가의 정확성을 높이며 최적화를 용이하게 하였다. 정량적 위험성 평가 결과, 공정 변수 중 안전성 확보를 위해 중요한 변수는 혼합냉매의 압력이었고, 0.5~10%의 운전비용 증가를 통해 잠재적 위험성을 4~18% 줄일 수 있었다. 비용을 크게 증가시킬수록 위험성의 절대적 수치는 낮아지지만 비용 대비 위험성 감소의 효과는 떨어졌다. 이처럼 공정모사와 정량적 위험성 평가 기법의 통합은 태생적으로 보다 안전한 공정의 설계가 가능하게 하고, 기초설계 단계에서부터 공정 내 위험요인을 수치적으로 확인할 수 있어 위험요인이 적은 특성을 갖도록 공정을 설계하는데 도움이 될 것이다.
Preliminary design in chemical process furnishes economic feasibility through calculation of both mass balance and energy balance and makes it possible to produce a desired product under the given conditions. Through this design stage, the process possesses unchangeable characteristics, since the materials, reactions, unit configuration, and operating conditions were determined. Unique characteristics could be very economic, but it also implies various potential_x000D_
risk factors as well. Therefore, it becomes extremely important to design process considering both economics and safety by integrating process simulation and quantitative risk analysis during preliminary design stage. The target of this study is LNG liquefaction process. By the simulation using Aspen HYSYS and quantitative risk analysis, the design variables of the process were determined in the way to minimize the inherent explosion risks and operating cost. Instead_x000D_
of the optimization tool of Aspen HYSYS, the optimization was performed by using stochastic optimization algorithm (Covariance Matrix Adaptation-Evolution Strategy, CMA-ES) which was implemented through automation between Aspen HYSYS and Matlab. The research obtained that the important variable to enhance inherent safety was the operation pressure of mixed refrigerant. The inherent risk was able to be reduced about 4~18% by increasing the operating cost about 0.5~10%. As the operating cost increases, the absolute value of risk was decreased as expected, but costeffectiveness of risk reduction had decreased. Integration of process simulation and quantitative risk analysis made it possible to design inherently safe process, and it is expected to be useful in designing the less risky process since risk factors in the process can be numerically monitored during preliminary process design stage.
Keywords
References
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Hansen N, “The CMA Evolution Strategy: A Tutorial,” https://www.lri.fr/~hansen/cmatutorial.pdf (2011)
AspenTech, Aspen HYSYS Customization Guide, Aspen Technology, Inc. (2011)
So W, Kim YH, Lee CJ, Shin D, Yoon ES, Korean J. Chem. Eng., 28(3), 656 (2011)
Kim YH, So W, Shin D, Yoon ES, Korean J. Chem. Eng., 28(6), 1322 (2011)
Park K, Koo J, Shin D, Lee CJ, Yoon ES, Korean J. Chem. Eng., 28(4), 1009 (2011)
Park J, Lee Y, Yoon Y, Kim S, Moon I, Korean J. Chem. Eng., 28(11), 2110 (2011)
Jang N, Dan S, Shin D, Lee G, Yoon ES, Korean Chem. Eng. Res., 51(2), 221 (2013)
Shariff AM, Rusli R, Leong CT, Radhakrishnan VR, Buang A, J. Loss Prevent. Proc., 19, 409 (2006)
Shah NM, Hoadley AFA, Rangaiah GP, Ind. Eng. Chem. Res., 48(10), 4917 (2009)
Aspelund A, Gundersen T, Myklebust J, Nowak MP, Tomasgard A, Comput. Chem. Eng., 34(10), 1606 (2010)
Venkatarathnam G, Cryogenic mixed refrigerant processes, Springer (2008)
Woodward JL, Estimating the flammable mass of a vapor cloud, CCPS of the AIChE (1998)
GPSA, GPSA Engineering data book, 12th ed., Volume II, Gas Processors Suppliers Association (2004)
CEPPO, Risk management program guidance for offsite consequence analysis, United States Environmental Protection Agency (1999)
TNO, Method for the calculation of physical effects (Yellow Book), Committee for the Prevention of Disasters (1997)
Swenson LK, Single mixed refrigerant, closed loop process for liquefying natural gas, U.S. Patent 4,033,735 (1997)
Seider WD, Seader JD, Lewin DR, Widagdo S, Product and Process Design Principles: Synthesis, Analysis and Design, 3rd ed., Wiley (2009)
Hansen N, Ostermeier A, Evol. Comput., 9(2), 159 (2001)
Hansen N, Ostermeier A, “Adapting Arbitrary Normal Mutation Distributions in Evolution Strategies: the Covariance Matrix Adaptation,” Proceedings of IEEE International Conference on Evolutionary Computation, 312-317 (1996)
Hansen N, Muller SD, Koumoutsakos P, Evol. Comput., 11(1), 1 (2003)
Hansen N, Kern S, Lect. Notes Comput. SC., 282 (2004)
Beyer HG, Schwefel HP, Nat. Comp., 1(1), 3 (2002)
Hoffmeister F, XBack T, “Genetic Algorithms and Evolution Strategies: Similarities and Differences,” Lect. Notes Comput. SC., Springer, 455-469 (1991)
Hansen N, Auger A, Ros R, Finck S, Posik P, “Comparing Results of 31 Algorithms from the Black-Box Optimization Benchmarking BBOB-2009,”Workshop Proceedings of the GECCO Genetic and Evolutionary Computation Conference 2010 (2010)
https://www.lri.fr/~hansen/cmaapplications.pdf.
Hansen N, “The CMA Evolution Strategy: A Tutorial,” https://www.lri.fr/~hansen/cmatutorial.pdf (2011)
AspenTech, Aspen HYSYS Customization Guide, Aspen Technology, Inc. (2011)