DOE OSTI · 1034236
EMSL Pore Scale Modeling Challenge/Workshop
Abstract
The design and implementation of cost-effective remediation strategies for subsurface contamination not only relies on descriptive models of contaminant distribution but predictive models of contaminant fate and transport. The development of such predictive models is of great importance to many government agencies including the Department of Energy (DOE), Department of Defense, and the Environmental Protection Agency. Accurate prediction of the fate and transport of environmental contaminants in the subsurface has driven development of increasingly sophisticated subsurface flow and transport models. Even without considering spatial and temporal scalability, contaminant transport at the field scale is complex, and this almost inevitably results in an especially sophisticated model being developed for a specific field site. Unfortunately, these models are not easily generalizable to other field sites or and can only be used by the model authors to generate meaningful results. Over time, this results in the existence of numerous specialized models that are not readily comparable to each other and difficult to cross-validate. There is a lack of fundamental experimental observations at the pore scale that can be used to support model development and validation at the field scale.
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Hess, Nancy J., Oostrom, Martinus, Celia, Michael A., Hilpert, Markus, Kang, Qinjun, Pyrak-Nolte, Laura J., Scheibe, Timothy D., Tartakovsky, Alexandre M., Werth, Charles J., Wildenschild, Dorthe, Zhang, Changyong, Bialkowski, Stephen E., Ghezzehei, Teamrat A., Tang, Guoping, Doster, Florian, Kumar, Jitendra, Parashar, Rishi, Gerlach, Robin, Yoon, Hongkyu, Redden, George D., Zhang, Tianyu, Huang, Hai, Nogues, Juan, Deng, Wen, Resat, Haluk, Rod, Kenton A., Baer, Donald R., Kelly, Ryan T., Um, Wooyong, Wang, Guohui, Richmond, Marshall C., Rector, David R., Stewart, Mark L., Jung, Hun Bok, Plata, Charity. 2011-08-09. EMSL Pore Scale Modeling Challenge/Workshop. https://doi.org/10.2172/1034236
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