Author

Xiao Lin

Date of Award

Summer 2018

Document Type

Open Access Dissertation

Department

Computer Science and Engineering

First Advisor

Gabriel Terejanu

Abstract

Computational models play an important role in scientific discovery and engineering design. However, developing computational models is challenging, since the process always follows a path contaminated with errors and uncertainties. The uncertainties and errors inherent in computational models are the result of many factors, including experimental uncertainties, model structure inadequacies, uncertainties in model parameters and initial conditions, as well as errors due to numerical discretizations. To realize the full potential in applications it is critical to systematically and economically reduce the uncertainties inherent in all computational models.

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