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화학공정의 확률적 동적모사를 위한 몬테카를로 시뮬레이션 기법
A Monte Carlo Method for Stochastic Dynamic Simulation of Chemical Processes
HWAHAK KONGHAK, April 1999, 37(2), 344-348(5), NONE
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Abstract
화학공정에는 설계 및 운전 단계에서 여러 가지 불착실성이 복합적으로 존재한다. 이를 정량적으로 해석하기 위하여서는 화학공정의 확률적 동적모사 기술이 요구된다. 확률적 동적 모사기능을 갖춘 범용 화학공정 모사기 개발을 위한 기존의 몬테카를로 시뮬레이션 연구에서는 변수에 대한 불확실성의 크기만 다루었으나, 본 연구에서는 변화발생시점의 불확실성까지 함께 다루기 위하여 새로운 매개변수 MTBD(Mean Time Between Disturbances)를 제안한다. 또한 제안된 방법을 수행하기 위한 씨스템 구축 방법을 제시한다. 사례연구결과는 제안된 방법론이 화학공정의 불확실성을 다루는데 효과적으로 활용될 수 있음을 보여준다.
Chemical processes involve various and complicated uncertainties in the design and operation stages. Quantitative analysis of these uncertainties requires a method for stochastic dynamic simulation of chemical processes. In the previous work for the development of a general purpose chemical process simulator capable of stochastic dynamic simulation, only the extent of the uncertainty of a variable was considered. In this work, however, a new parameter MTBD (Mean Time Between Disturbances) is proposed in order to consider the uncertainty on when a change is to occur also. A method for construction of a system which implements the proposed method is also presented. The results of case studies_x000D_
indicate that the proposed methodology can be electively applied to dealing with uncertainties in chemical processes.
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Suh SH, Korean J. Chem. Eng., 12(4), 491 (1995)
Suh SH, Kim BH, Kim SC, Korean J. Chem. Eng., 13(1), 30 (1996)
Kim H, Rajagopalan R, HWAHAK KONGHAK, 32(5), 659 (1994)
Kim H, Pyun MS, Korean J. Chem. Eng., 12(4), 488 (1995)
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Yoon IH, Lee SY, "Modern Statistics," Samyoung, Seoul, Korea (1997)
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