Ken Powell and Ryan McClarrenCRASH Review, October 2010

CRASH Students and Courses

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

Blastworthiness Project

Concluding Remarks

Both classes drew a diverse student group – there is real interest in the topic among grad students

The combination of simpler homework sets to teach the concepts and final projects driven by the students’ research worked well