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.
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Researchers should cite this work as follows:
Birck Nanotechnology Center, Purdue University, West Lafayette, IN
|Lecture Number/Topic||Online Lecture||Video||Lecture Notes||Supplemental Material||Suggested Exercises|
|ME 597A Lecture 5: Generalized Polynomial Chaos for UQ II - The Collocation Approach||View HTML
|ME 597A Lecture 7: Uncertainty Quantification in Experiments||View Flash||View||Notes|
Guest Lecture Arvind Raman.
|ME 597A Lecture 12: Uncertainty Propagation in a Multiscale Model of Nanocrystalline Plasticity||View Flash||View||Notes|
Guest lecturer: Marisol Koslowski.
|ME 597A Lecture 13: Uncertainty Quantification of Molecular Dynamics Simulations||View Flash||View||Notes|
Guest lecturer: Alejandro Strachan.