Issue
Korean Chemical Engineering Research,
Vol.45, No.6, 582-590, 2007
Water Gas Shift Reactor의 Multiscale 모델링 및 모사
Multiscale Modeling and Simulation of Water Gas Shift Reactor
Water gas shift reaction(WGSR)이 일어나는 파이럿 규모 고온반응기에서의 거동 및 성능을 예측하기 위하여 수학적 모델을 수립하고 모사를 수행하였다. 반응기의 형상, 유체 및 열 이동에 대해 상세한 모델링이 가능한 전산유체역학 기법과 공정시스템 공학에서 사용되는 공정모사 기법을 함께 사용한 multiscale 모델링 및 모사를 수행하였으며, 그 결과를 일반 공정모사와 비교하였다. Multiscale 모사를 통해 CO의 전환율은 최고 0.85, 발열반응으로 인해 충전층의 온도는 약 720 K까지 오름을 알 수 있었다. 또한 동적모사를 통해 시간에 따른 반응기내에서의 온도분포, 전환율 분포 등의 주요한 변수 및 성능들의 시간에 따른 변화를 예측할 수 있었다. Multiscale 모사 기법은 파이럿 규모의 반응기뿐 아니라 상업규모의 공정에 대해 실제 상황을 상세히 반영하여 정확한 예측이 가능하므로, 상업공정 설계에 주요한 기술로 사용될 수 있다.
In view of the analysis of the phenomena and the prediction of the performance, mathematical modelling and simulation of a high temperature pilot reactor for water gas shift reaction (WGSR) has been carried out. Multiscale simulation incorporated computational fluid dynamics (CFD) technique, which has the capability to deal with the reactor shape, fluid and energy transport with extensive degree of accuracy, and process modeling technique, which, in turn is responsible for reaction kinetics and mass transport. This research employed multiscale simulation and the results were compared with those from process simulation. From multiscale simulation, the maximum conversion of was predicted approximately 0.85 and the maximum temperature at the reactor was calculated 720 K, resulting from the heat of reaction. Dynamic simulation was also performed for the time transient profile of temperature, conversion, etc. Considering the results, it is concluded that multiscale simulation is a safe and accurate technique to predict reactor behaviors, and consequently will be available for the design of commercial size chemical reactors as well as other commercial unit operations.
[References]
  1. Kirk-Othermer, “Hydrocarbons,” Encyclopedia Chemical Technology, 5thed., 13, 2005
  2. Newsome DS, Catal. Rev.-Sci. Eng., 21(2), 275, 1980
  3. Singh CPP, Saraf DN, Ind. Eng. Chem. Process Des. Dev., 16(3), 313, 1977
  4. Singh CPP, Saraf DN, Ind. Eng. Chem. Process Des. Dev., 19(3), 393, 1980
  5. Choi Y, Stenger HG, J. Power Sources, 124(2), 432, 2003
  6. Ovesen CV, Clausen BS, Hammershoi BS, Steffensen G, Askgaard T, Chorkendorff I, Norskov JK, Rasmussen PB, Stoltze P, Taylor P, J. Catal., 158(1), 170, 1996
  7. Ovensen CV, Stolze P, Norskov JK, Campbell CT, J. Catal., 134, 445, 1992
  8. Botes FG, Appl. Catal. A: Gen., 328, 237, 2007
  9. Koryabkina NA, Phatak AA, Ruettinger WF, Farrauto RJ, Ribeiro FH, J. Catal., 217(1), 233, 2003
  10. Callaghan C, Fishtik I, Datta R, Carpenter M, Chmielewski M, Lugo A, Surf. Sci., 541, 21, 2003
  11. Levenspiel O, “Chemical Reaction Engineering,” 3rd ed. Chap, 11, 257, 1999
  12. Ingram GD, Cameron IT, Hangos KM, Chem. Eng. Sci., 59(11), 2171, 2004
  13. Chen Q, Zhai Z, Wang L, Chem. Eng. Sci., 62, 3580, 2007
  14. gPROMS, gPROMS User’ Guide, Process Systems Enterprise Ltd, 2006
  15. Fluent, Fluent 6.2 User’s Guide, Fluent Incorporated, 2006
  16. Versteeg HK, Malalasekera W, An introduction to Computational Fluid Dynamics, Prentice-Hall, 1995