Assessing a Response Surface-Based Optimization Approach for Soil Vapor Extraction System Design
Publication: Journal of Water Resources Planning and Management
Volume 135, Issue 3
Abstract
This paper presents a study on a response surface-based optimization approach for soil vapor extraction system (SVES) design. The SVES design involves extraction rate determination for a number of wells at fixed locations. Two optimization problems were investigated in this study, including: (1) minimizing total cost while achieving the required cleanup goal; and (2) maximizing percentage of contaminant mass removal under the constraint of total extraction rate. The response surface-based optimization approach integrates a multiphase flow and transport simulator, a genetic algorithm and a response surface method that employs regression analysis for constructing an approximation function of mass removal percentage in terms of extraction rate. A symmetric Latin hypercube design (SLHD) or factorial design plan is employed to obtain a moderate number of design points for different optimization problems. Besides, an iterative optimization procedure is implemented in the approach to enhance the accuracy of the approximated response function by gradually adding more design points to the design space. Results show that the response surface-based optimization approach is superior to a simulation/optimization approach in terms of optimal solution and computation time.
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Acknowledgments
This work was funded by the National Science Council in Taiwan. The writers would like to thank Professor L. M. Abriola, Dr. K. M. Rathfelder, and Mr. J. R. Lang for providing the MISER code, and Professor D. L. Carroll for the GA code. The National High-Speed Computer Institute in Taiwan providing the parallel computing equipment is also acknowledged.
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Published In
Journal of Water Resources Planning and Management
Volume 135 • Issue 3 • May 2009
Pages: 198 - 207
Copyright
© 2009 ASCE.
History
Received: Feb 8, 2008
Accepted: Jun 4, 2008
Published online: May 1, 2009
Published in print: May 2009
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