Parameter estimation for reactive transport by a Monte-Carlo approach
The chemical parameters used in reactive transport models are not known accurately due to the complexity and the heterogeneous conditions of a real domain. The development of an efficient algorithm in order to estimate the chemical parameters using Monte‐Carlo method is presented. By fitting the res...
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Published in | AIChE journal Vol. 52; no. 6; pp. 2281 - 2289 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Hoboken
Wiley Subscription Services, Inc., A Wiley Company
01.06.2006
Wiley Subscription Services American Institute of Chemical Engineers |
Subjects | |
Online Access | Get full text |
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Summary: | The chemical parameters used in reactive transport models are not known accurately due to the complexity and the heterogeneous conditions of a real domain. The development of an efficient algorithm in order to estimate the chemical parameters using Monte‐Carlo method is presented. By fitting the results obtained from the model with the experimental curves obtained with various experimental conditions, the problem of parameters estimation is converted into a minimization problem. Monte‐Carlo methods are very robust for the optimization of the highly nonlinear mathematical model describing reactive transport. It involves generating random values of parameters and finding the best set. The focus is to develop an optimization algorithm which uses less number of realizations so as to reduce the CPU time. Reactive transport of TBT through natural quartz sand at seven different pHs is taken as the test case. Our algorithm will be used to estimate the chemical parameters of the sorption of TBT onto the natural quartz sand. © 2006 American Institute of Chemical Engineers AIChE J, 2006 |
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Bibliography: | ArticleID:AIC10813 EGIDE ark:/67375/WNG-P6X837XB-6 istex:240C05CC1926FB6FFE74DEFE8CDEED9C5EA73171 ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 0001-1541 1547-5905 |
DOI: | 10.1002/aic.10813 |