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Application of Transport Optimization Codes to Groundwater Pump-and-Treat Systems
Sponsored by: Environmental Security Technology Certification Program and U.S. EPA, Office of Superfund Remediation and Technology Innovation
Original Time/Date of Presentation:

September 24, 2003, 2:00 PM - 4:00 PM, EDT (18:00-20:00 GMT)

Presentation Overview:

The objective of presentation is to introduce transport optimization for groundwater pump-and-treat systems, the results of a recent ESTCP transport optimization demonstration project, the optimization formulation process for groundwater pump-and-treat systems, and recommendations on practical aspects of implementing the technology.

The recent ESTCP transport optimization demonstration project evaluated the benefits and utility of applying transport optimization algorithms coupled with groundwater flow and transport simulation models. Three Department of Defense (DoD) pump-and-treat systems were evaluated. Three mathematical formulations were developed for each site, consisting of an objective function to be minimized and a set of constraints to be satisfied. Two modeling groups applied transport optimization algorithms, and one group applied trial-and-error to serve as a control.

The results achieved by the two groups applying the optimization algorithms were generally similar for similarly-posed problems, and in all cases represented improved solutions versus the trial-and-error results. Typical improvement in objective function value was 20 percent relative to trial-and-error, but as much as 50 percent improvement was observed for one of the formulations. The optimization algorithms were able to evaluate far more alternatives, and also suggested alternatives that were not otherwise obvious.

The project illustrates that transport optimization techniques are practical for real-world problems. However, applying the techniques requires expertise. In some cases the transport optimization groups applied multiple mathematical algorithms and/or solved a series of modified sub-problems to reduce computational requirements. It was also determined that formulating the solving problems with multiple iterations (i.e., modifying the mathematical formulation based on initial results) is the most practical method to apply these techniques, although that approach was not possible in this demonstration study.

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