Clint N. Dawson
Affiliations: | Institute for Computational Engineering and Sciences | University of Texas at Austin, Austin, Texas, U.S.A. |
Area:
Mathematics, Fluid and Plasma PhysicsWebsite:
https://www.ae.utexas.edu/people/faculty/faculty-directory/dawsonGoogle:
"Clint N. Dawson"Bio:
Dawson, Clint. Error estimates for Godunov mixed methods for nonlinear parabolic equations.
(1988) Diss., Rice University. https://hdl.handle.net/1911/16131.
Parents
Sign in to add mentor| Mary Fanett Wheeler | grad student | 1988 | Rice University (MathTree) | |
| (Error estimates for Godunov mixed methods for nonlinear parabolic equations) | ||||
Children
Sign in to add trainee| Jennifer K. Proft | grad student | 2002 | UT Austin |
| Vadym Aizinger | grad student | 2004 | UT Austin |
| Ruijie Liu | grad student | 2004 | UT Austin |
| Hyung T. Ahn | grad student | 2005 | UT Austin |
| Mauricio Santillana | grad student | 2008 | UT Austin |
| Amin Kiaghadi | post-doc | UT Austin (Meteorology Tree) |
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Publications
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| Kiaghadi A, Rifai HS, Dawson CN. (2021) The presence of Superfund sites as a determinant of life expectancy in the United States. Nature Communications. 12: 1947 |
| Valseth E, Dawson C. (2020) An unconditionally stable space–time FE method for the Korteweg–de Vries equation Computer Methods in Applied Mechanics and Engineering. 371: 113297 |
| Sochala P, Chen C, Dawson C, et al. (2020) A polynomial chaos framework for probabilistic predictions of storm surge events Computational Geosciences. 24: 109-128 |
| Siripatana A, Maitre OL, Knio O, et al. (2020) Bayesian inference of spatially varying Manning’s n coefficients in an idealized coastal ocean model using a generalized Karhunen-Loève expansion and polynomial chaos Ocean Dynamics. 70: 1103-1127 |
| Li W, Kiaghadi A, Dawson C. (2020) Exploring the best sequence LSTM modeling architecture for flood prediction Neural Computing and Applications. 1-10 |
| Samii A, Kazhyken K, Michoski C, et al. (2019) A Comparison of the Explicit and Implicit Hybridizable Discontinuous Galerkin Methods for Nonlinear Shallow Water Equations Journal of Scientific Computing. 80: 1936-1956 |
| Bremer MH, Kazhyken K, Kaiser H, et al. (2019) Performance Comparison of HPX Versus Traditional Parallelization Strategies for the Discontinuous Galerkin Method Journal of Scientific Computing. 80: 878-902 |
| Jain PK, Mandli K, Hoteit I, et al. (2018) Dynamically adaptive data-driven simulation of extreme hydrological flows Ocean Modelling. 122: 85-103 |
| Bass B, Torres JM, Irza JN, et al. (2018) Surge dynamics across a complex bay coastline, Galveston Bay, TX Coastal Engineering. 138: 165-183 |
| Samii A, Dawson C. (2018) An explicit hybridized discontinuous Galerkin method for Serre-Green-Naghdi wave model Computer Methods in Applied Mechanics and Engineering. 330: 447-470 |