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Educational Progress and Plans Ken Powell. Page 2 About Our Students Each UM and TAMU student has a home department Current students from –Atmospheric,

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Presentation on theme: "Educational Progress and Plans Ken Powell. Page 2 About Our Students Each UM and TAMU student has a home department Current students from –Atmospheric,"— Presentation transcript:

1 Educational Progress and Plans Ken Powell

2 Page 2 About Our Students Each UM and TAMU student has a home department Current students from –Atmospheric, Oceanic and Space Sciences (UM) –Aerospace Engineering (UM) –Applied Physics (UM) –Computer Science (TAMU) –Mathematics (UM) –Statistics (UM, TAMU) –Nuclear Engineering (UM, TAMU) Many CRASH students co-advised

3 Page 3 About Our Students Students funded from several sources –CRASH center funds –CRASH fellowship cost-sharing funds –Non-CRASH fellowship or RA funds Students engaged in CRASH community –Student involvement in 20 of the posters Strong connections to NNSA labs –Several senior students have already visited labs –Several newer students will visit the labs in 2010 –Ongoing effort to encourage this and make connections

4 Page 4 Selected Student Research Topics Modeling and Theory –Discontinous Galerkin methods for hydrodynamics –Coupling methods for rad-hydro –Radtran and turbulence effects in blast waves –Time discretization methods for radtran Experiments –Structure in radiative shocks –Radiative shock experiments at the OMEGA facility –Hydrodynamic shock experiments at the OMEGA facility UQ –Unsteady adjoints for error estimation and AMR –Bayesian and traditional regression methods for analysis of data from high-dimensional computational experiments

5 Page 5 UM Scientific Computing PhD Certificate Requirements are: –At least 24 credits in home department –At least 9 credits of numerical methods –At least 9 credits in computer science/applications –At least one doctoral prelim question related to scientific computing –Sample course requirements - Aerospace Eng + Scientific Computing/Predictive Science Compressible flow, viscous flow, turbulent flow Molecular gas dynamics, combustion Numerical linear algebra, CFD I, CFD II Software engineering, parallel computing, predictive science Several CRASH students pursuing this

6 Page 6 Curricular Developments Predictive Science course at TAMU –First offering Fall 2009 –Taught by Ryan McClarren –Covers verification, validation, sensitivity analysis and UQ Uncertainty Quantification course at UM –First offering Winter 2010 –Team-taught (James Holloway, Vijay Nair, Ken Powell) –Focused on input/output modeling, screening and sensitivity analysis, UQ The two groups will compare notes in the summer, work to improve both classes

7 Page 7

8 Page 8 TAMU Predictive Science Course Introduction Verification –Numerical analysis preliminaries –Verification with exact solutions –Designing a test suite –Analyzing the results Validation –Validation using experimental data –Model drill-down Uncertainty quantification and sensitivity analysis –Statistics preliminaries –Sensitivity analysis –Stochastic uncertainty quantification –Reliability methods –Polynomial chaos –Bayesian inference –Dealing with epistemic uncertainty

9 Page 9 UM Uncertainty Quantification Course Introduction Input/Output Modeling –Emulators and response surfaces –Parametric regression –Semi-parametric modeling –Gaussian process modeling –Prediction versus model identification –Screening and sensitivity analysis Uncertainty quantification –Estimating output uncertainties –Reducing input uncertainties for a new prediction –Estimating model discrepancy function –Building a predictive model


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