GSA Connects 2021 in Portland, Oregon

Paper No. 220-11
Presentation Time: 9:00 AM-1:00 PM


LEE, Seong-Sun1, PARK, Inwoo1, JUN, Seong-Chun2, HA, Seung-Wook1, IM, Jin-Hui3, LEE, Sanghoon1 and LEE, Kang-Kun1, (1)SEES, Seoul National University, Gwanakro1 Gwanakgu, Seoul National University 25-1 505, Seoul, 08826, Korea, Republic of (South), (2)R&D Division, GeoGreen21 Co., Ltd.(Groundwater&Soil Environment Company), 1104 E&C Venture Dream Tower 2, 55 Digital-ro 33-gil, Guro-gu, Seoul, 08376, Korea, Republic of (South), (3)Soda system, Dongangu Beolmalro 123 Pyungchon, Smartbay A 1001, Anyang

The objective of our research is to develop an integrated pumping-injection operation system using graphical user interface on web-based service that includes an optimized remediation operating system, remediation strategies for preventing the spread of contaminated groundwater for each scenario, and optimized remediation design using simulation-optimization method based on numerical model. Among various studies, this study performs to suggest a cost-effective remediation strategy using a simulation-optimization model that takes into account the hydrogeological factors of the contaminated site when performing remediation by the pumping-injection method based on a hydraulic flow control at DNAPL contaminated site. In the process of finding an optimal method for the remediation design, Genetic Alogrithm(GA) method has been widely applied at contaminated sites to find the factors for optimal remediation operation such as location and rate of pumping and injection, the number of well, operating cost. However, one of problems of the existing Genetic Algorithm(GA) code are composed of C++ language, so there are many difficulties in changing the code except for developers. In this study, the GA code has been newly composed in python language with good compatibility with the user-interface environment within the integrated managing and operating system. The developed GA code is used for the development of the optimal remediation design algorithm for the pumping-injection system. The developed optimization algorithm was verified through the simplified numerical model simulation considering random contaminant sources. And then, it was applied to find the optimized pumping rate and well location that the concentration of contaminant in a single well appear to be minimum at the contaminated site. Also, simulation-optimization methods was applied to suggest the optimized operation condition that can prevent the spreading of contaminant plume with a hydraulic flow control concept in a short period.Acknowledgements: This work was supported by Korea Environment Industry & Technology Institute(KEITI) through "Activation of remediation technologies by application of multiple tracing techniques for remediation of groundwater in fractured rocks"(Grant number:20210024800002/1485017890)", "Hydraulic control and containment using pumping-injection system" (SEM projects2020002470001/1485017133), and the Demand Responsive Water Supply Service Program(RE20191097) funded by the Korea Ministry of Environment(MOE).