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1 to 10 of 42 Results
Jul 8, 2019 - SvePy code and documents
Hodges, Ben R.; Liu, Frank, 2019, "Algorithms in the SvePy solver for the unsteady Saint-Venant equations", https://doi.org/10.18738/T8/ETSJDJ, Texas Data Repository Dataverse, V1
The Saint-Venant Python (SvePy) code has been written to solve a single the Saint-Venant equations governing unsteady flow in a river reach with either rough or smooth geometry. The code was designed for prototype testing of finite-volume numerical algorithms. The primary descrip...
Center for Space Research Dataverse(University of Texas at Austin)
Jul 12, 2019University of Texas at Austin Dataverse
The UT Center for Space Research (CSR) is a leader and innovator in mission planning, design, and execution of spacecraft, aircraft, and ground-based campaigns. CSR expertise has led, supported and enhanced many missions that have improved our knowledge of complex processes rangi...
Jul 12, 2019 - Center for Space Research Dataverse
Save, Himanshu, 2019, "CSR GRACE RL06 Mascon Solutions", https://doi.org/10.18738/T8/UN91VR, Texas Data Repository Dataverse, V1
GRACE RL06 Monthly mascon solutions from the Center for Space Research
Dec 20, 2019 - Center for Space Research Dataverse
Save, Himanshu, 2019, "CSR RL05 GRACE Daily Swath Mass Anomaly Estimates over the Ocean", https://doi.org/10.18738/T8/95ITIK, Texas Data Repository Dataverse, V1
CSR GRACE Daily Swath Mass Anomaly Estimates over the Ocean
May 7, 2019 - Shahzad Gani Dataverse
Gani, Shahzad; Bhandari, Sahil; Seraj, Sarah; Wang, Dongy S.; Patel, Kanan; Soni, Prashant; Arub, Zainab; Habib, Gazala; Hildebrandt Ruiz, Lea; Apte, Joshua, 2019, "Data published in "Submicron aerosol composition in the world's most polluted megacity: The Delhi Aerosol Supersite campaign"", https://doi.org/10.18738/T8/9L33CI, Texas Data Repository Dataverse, V1
This dataset contains hourly data for PM1 species used in manuscript titled "Submicron aerosol composition in the world's most polluted megacity: The Delhi Aerosol Supersite campaign"
Nov 18, 2019 - Oil spill physics and modeling
Hodges, Ben, 2019, "Extending and improving Texas bay/estuary oil spill simulations", https://doi.org/10.18738/T8/DQWE9F, Texas Data Repository Dataverse, V1
The Hydrodynamic Oil Spill--Python (HyosPy) system is an integrated modeling system that combines the latest weather forecast with multiple hydrodynamic models and oil spill models that, in a conventional operating mode, can be used to provide predictions of oil spill particle tr...
Hodges Research Group Dataverse(University of Texas at Austin)
Jul 8, 2019University of Texas at Austin Dataverse
Research products associated with the research group of Prof. Ben R. Hodges and his students. Center for Water and the Environment, University of Texas at Austin
Huilin Gao Dataverse(Texas A and M University)
Jan 8, 2019Texas A&M University Dataverse
Intelligent Environments Laboratory(University of Texas at Austin)
May 23, 2019University of Texas at Austin Dataverse
Environmental measurements produced by the Intelligent Environments Laboratory
Oil spill physics and modeling(University of Texas at Austin)
Nov 18, 2019Hodges Research Group Dataverse
Research on oil spill physics and modeling conducted by Ben R. Hodges and collaborators
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