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CLASS:PUBLIC
CREATED:20260911T170707Z
DESCRIPTION:Subsurface characterization with an application to coastal aquifer characterization\n\nJonghyun Harry Lee, Assistant Professor in Civil and Environmental Engineering and WRRC, University of Hawaiʻi at Mānoa.\n\nAbstract\n\nRecent advances in computational resources and sensor technology allow multi-physics simulation of subsurface properties and open up a new opportunity to characterize unknown subsurface parameters at small scale. However, identification of unknown parameters such as subsurface permeability becomes more computationally challenging than ever with expensive high-fidelity simulations and big environmental data assimilation. In this talk, I will introduce numerical tools that can accelerate the estimation process without much loss of accuracy. Then, I will present a coastal aquifer permeability estimation application and report that integration with coupled flow and transport models can improve characterization results significantly even with sparse noisy pressure observations. Compared to typical aquifer characterization necessarily with joint flow and transport data sets for better results, pressure or concentration data alone in coupled system might be enough to obtain reliable subsurface images, which help design an optimal sampling network for coastal aquifer characterization.\n\nBio\n\nJonghyun Harry Lee is an assistant professor in Civil and Environmental Engineering and WRRC at the university of Hawaii at Manoa. Prior to the appointment, he was a postdoc scholar in Civil and Environmental Engineering at Stanford University. He received his B.S. in Civil, Urban and Geosystem Engineering from Seoul National University in 2007, his M.S. in Civil and Environmental Engineering from Colorado State University in 2009, and his PhD in Civil and Environmental Engineering from Stanford University in 2014. His research focuses on the development of integrated computational tools to perform large-scale predictive simulation in high-performance computing environment, fast and scalable parameter estimation with uncertainty quantification using big environmental data, and cost optimization with data-worth analysis for civil and environmental engineering projects such as managed aquifer recharge and recovery, contaminant remediation and real-time near-shore bathymetry identification.
DTEND;TZID=Pacific/Honolulu:20171019T020000Z
DTSTAMP:20260911T170707Z
DTSTART;TZID=Pacific/Honolulu:20171019T010000Z
LAST-MODIFIED:20260911T170707Z
LOCATION:POST 723
PRIORITY:5
SEQUENCE:0
SUMMARY;LANGUAGE=en-us:WRRC Water Seminar
TRANSP:OPAQUE
UID:178918242732033web-support-l@lists.hawaii.edu
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