Materials Innovation Lecture Series

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Event Details
  • Date/Time:
    • Wednesday May 17, 2017 - Thursday May 18, 2017
      3:00 pm - 3:59 pm
  • Location: The George W. Woodruff School of Mechanical Engineering, MRDC Bldg., Room 4211, 801 Ferst Drive, NW Atlanta, GA 30332
  • Phone:
  • URL: https://goo.gl/maps/aA9Rkmowfs52
  • Email:
  • Fee(s):
    N/A
  • Extras:
    Free food
Contact
No contact information submitted.
Summaries

Summary Sentence: Join us as Laura Swiler presents a talk on the verification, validation, and uncertainty quantification (UQ) methods such as multi-fidelity, multi-physics, and multi-scale areas.

Full Summary: No summary paragraph submitted.

Media
  • Laura Swiler Laura Swiler
    (image/jpeg)

Uncertainty Quantification with Thoughts on Multiscale Materials Applications

Laura P. Swiler, Distinguished Member of Technical Staff

Optimization and Uncertainty Quantification Department 

Sandia National Laboratories

Abstract:

The talk will emphasize benefits, challenges, and appropriate use cases for various uncertianty quanification (UQ) approaches. Particular topics presented will include polynomial chaos expansions, dimension reduction and active subspace approaches, multi-level Monte Carlo methods, Bayesian calibration, and coupled methods as well as applications to materials problems and multi-scale materials applications. 

Biography:

Dr. Laura P. Swiler is a Distinguished Member of the Technical Staff in the Optimization and Uncertainty Quantification Department at Sandia National Laboratories.  She has twenty-two years of experience in reliability and risk assessment.   Laura started her career at Sandia working in reliability analysis, for weapons applications and nuclear waste repository assessment.  For the past fourteen years, Laura has focused on sensitivity analysis, model validation, and uncertainty quantification. Some of Laura’s research interests include:  sensitivity analysis for high-dimensional inputs, model validation incorporating both experimental and simulation uncertainty, use of surrogate or meta-models for optimization and extrapolation, calibration of model parameters in the presence of both experimental and model uncertainty, and use of non-probabilistic techniques to model epistemic uncertainty.   

Additional Information

In Campus Calendar
Yes
Groups

Georgia Tech Materials Institute

Invited Audience
Faculty/Staff, Public, Graduate students, Undergraduate students
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Keywords
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Status
  • Created By: Farlenthia Walker
  • Workflow Status: Published
  • Created On: Apr 17, 2017 - 12:55pm
  • Last Updated: Apr 17, 2017 - 4:36pm