ken powell and ryan mcclarren crash review, october 2010 crash students and courses
Post on 22-Dec-2015
213 views
TRANSCRIPT
About Our StudentsEach UM and TAMU student has a home department
Current students fromAtmospheric, Oceanic and Space Sciences (UM)Aerospace Engineering (UM)Applied Physics (UM)Computer Science (UM, TAMU)Mathematics (UM)Statistics (UM, TAMU)Nuclear Engineering (UM, TAMU)
Many CRASH students co-advised
About Our StudentsStudents 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 22 of the posters
Strong connections to NNSA labs Several students visited labs in 2010
Maginot (LANL), Pandya (LLNL), Stripling (LLNL), Zaide (LANL), Huntington (LLNL), Starinshak (LLNL)
Several possibilities for visits to the labs in 2011/12 Ongoing effort to encourage this and make connections
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 Reverse radiative shocks 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
CRASH CoursesPredictive Science course at TAMU
First offered Fall 2009Taught by Ryan McClarrenCovered verification, validation, sensitivity analysis and
UQ9 students
Uncertainty Quantification course at UMFirst offered Winter 2010Team-taught by James Holloway, Vijay Nair, Ken PowellFocused on input/output modeling, screening and
sensitivity analysis, UQ24 students
TAMU Predictive Science Course
Verification Numerical analysis preliminaries Verification with exact solutions Manufactured 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 / Calibration Dealing with epistemic
uncertainty
Structure of TAMU CourseThe course had students from nuclear
engineering, geophysics, and statistics.
Course was lectured-based with graded homework.
Final project covered a topic of the student’s choice.
In final project the students had to includeV&V of the code/model they were usingUncertain inputs A prediction with quantified uncertainty
Sample Final Projects – TAMU course
Several used polynomial chaos techniques toCompute the uncertainty in dose for a radiation
shielding calculation.Predict maximum temperature / flux in coupled
neutronics heat conduction simulation.
Compute sensitivity to coupling schemes in multiphysics problems.
Predict the spectral radius of a transport solve using a Kennedy-O’Hagan model
UM Uncertainty Quantification Course
Introduction Sources and types of
uncertainty Key probability concepts
used in UQ Overview of UQ process
Input/Output Modeling Emulators and response
surfaces Parametric regression Semi-parametric modeling
(MARS, MART) Gaussian process
modeling
Sampling the input space (Monte Carlo, Latin Hypercube, design of experiments)
Uncertainty quantification Estimating output
uncertainties Reducing input
uncertainties for a new prediction
Estimating model discrepancy function
Building a predictive model
Structure of UM courseLectures
Lab sessions Introduced background probability and statistics
information Introduced software (MATLAB, R)Worked examples related to lectures
Homeworks introduced key concepts, based on a simple simulation code written by each student (trajectory of a ball)
Final projects, based on their own research, presented in final weeks of class
Sample Final Projects – UM course
MARS/MART analysis of drag in a Mars Re-entry system
Gaussian process modeling and Markov-Chain Monte Carlo for turbulence model calibration
UQ analysis of a Fischer-Tropsch synthesis process
Constructing and sampling a response surface for radiative heat transfer in a scramjet
UQ in military ground vehicle blastworthiness simulations