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ME597/AAE590: Introduction to Uncertainty Quantification

By Alina Alexeenko

Aeronautics and Astronautics, Purdue University, West Lafayette, IN

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Abstract The focus of the course is on the quantification of uncertainty in multiscale multiphsyics simulations for engineering analysis. Though engineering simulation has become the mainstay of academic and industrial analysis in recent years, there has been little emphasis in understanding and quantifying the source of uncertainty in predictions. These uncertainties may arise for a variety of reasons: lack of mesh-independence, inadequate physical models, uncertainties in geometry, operating conditions and material properties, among others. The course introduces the student to the concepts of verification and validation, sensitivity analysis, and uncertainty propagation using sampling methods, polynomial chaos and reliability based methods. An introduction to uncertainty quantification software is also given. Emerging topics in uncertainty quantification of microsystem simulations are presented. The course is taught as a set of lectures given by Purdue Faculty from the schools of Science and Engineering.
Contributor Joseph M. Cychosz
  • super-administrator
Sponsored by NNSA Center for Prediction of Reliability, Integrity and Survivability of Microsystems (PRISM)
Cite this work

Researchers should cite this work as follows:

  • Alina Alexeenko (2010), "ME597/AAE590: Introduction to Uncertainty Quantification," http://memshub.org/resources/40.

    BibTex | EndNote

Time Fall 2010
Location Birck Nanotechnology Center, Room 1001, Purdue University, West Lafayette, IN
Tags
  1. ME597/AAE590
  2. uncertainty quantification
  3. verification & validation
Lecture Number/Topic Online Lecture Video Lecture Notes Supplemental Material Suggested Exercises
Lecture 1: Introduction to Verification & Validation and Uncertainty Quantification
Intro to V&V and UQ; basic statistics.
View Flash View Notes
Lecture 2: Sensitivity Analysis
Linear sensitivity analysis; finite difference, sensitivity equation, code differentiation.
View Flash View Notes
Lecture 3: Uncertainty Propagation View Flash View Notes
Lecture 4: Generalized Polynomial Chaos for UQ, part 1 View Flash View Notes
Lecture 5: Generalized Polynomial Chaos for UQ, part 2 View Flash View Notes
Lecture 6: Using MEMOSA UQ Software View Notes
Lecture 7: UQ in Experiments View Flash View Notes
Lecture 8: V&V and UQ of Computational Models View Flash View Notes
Lecture 9: Dakota as a Solution Verification and Uncertainty Quantification Tool View Flash View Notes
Lecture 10: Bayesian Methods I View Flash View Notes
Lecture 11: Bayesian Methods II View Flash View Notes
Lecture 12: Uncertainty Propagation in a Multiscale Model of Nanocrystalline Plasticity View Flash View Notes
Lecture 13: Uncertainty Quantification Molecular Dynamics Simulations View Flash View