A Workshop on Applying Optimization Algorithms and Contaminant Transport Models to Reduce Costs and Speed Remediation at Pump and Treat Sites
Dave Becker, U.S. Army Corps of Engineers, Hazardous, Toxic, and Radioactive Waste Center of Expertise
Robert Greenwald, Geotrans, Inc.
Karla Harre, US Navy, Naval Facilities Engineering Service Center
Barbara Minsker, Ph.D., University of Illinois
Kathleen Yager, US EPA, Office of Superfund Remediation and Technology Innovation (OSRTI)
This workshop provides an overview of the process of using optimization algorithms in conjunction with ground water flow and transport models (“simulation optimization”) to help identify the optimal combinations of well locations and extraction/injection rates to accomplish ground water remediation with the least cost or in the least time subject to site-specific constraints. The two-hour workshop is intended for site managers, regulators, and technical staff who desire an understanding of the benefits of this type of optimization, the general process, and what tools are publicly available to perform such simulation optimization. The workshop attendees will learn what simulation optimization is, what the potential benefits of applying the approach at their sites are, what the general process entails, and what the typical costs and expertise requirements are for application of the technology.
The workshop: 1) defines “transport optimization” as the use of optimization algorithms with ground water contaminant-transport models to find the optimal combination of well locations and flow rates (subject to certain constraints) that minimizes some measure of performance such as cost or time to cleanup, 2) identifies the potential benefits relative to more traditional “trial and error” approaches for groundwater extraction design, 3) describes the optimization process as one that includes the development of an objective function to be minimized or maximized (e.g., total cost, total pumping rate, contaminant mass remaining, etc.) and identification of constraints that must be satisfied (e.g., maximum flow from each well), followed by the application of software that uses optimization algorithms. This software repeatedly runs the flow and transport model (e.g., MODFLOW/MT3DMS) with different well locations and flow rates until a “better answer,” as measured by the objective function, can not be found by the optimization algorithm. 4) briefly presents the general capabilities of two publicly available optimization algorithm packages, MGO (University of Alabama) and SOMOS (Utah State University). 5)presents the results of a multi-site demonstration project where the optimal solution determined with MGO and SOMOS are compared to the results of the best efforts of experienced modelers using a traditional “trial and error” approach to solve the same optimization problem.
The development and presentation of the workshop and demonstration project were funded through the Department of Defense’s Environmental Security Technology Certification Program (ESTCP) and the EPA Office of Superfund Remediation and Technology Innovation.