Natural Resources, School of

 

First Advisor

Dr. Nam-Ho Kim

Second Advisor

Dr. Raphael Haftka

Date of this Version

2016

Citation

Price, N. B. (2016). Optimizing the Safety Margins Governing a Deterministic Design Process while Considering the Effects of a Future Test and Redesign on Epistemic Model Uncertainty (University of Florida). Retrieved from http://ufdc.ufl.edu/UFE0050354/00001

Comments

RS-3667

Abstract

At the initial design stage, engineers often rely on low-fidelity models that have high uncertainty. Model uncertainty is reducible and is classified as epistemic uncertainty; uncertainty due to variability is irreducible and classified as aleatory uncertainty. In a deterministic safety-margin-based design approach, uncertainty is implicitly compensated for by using fixed conservative values in place of aleatory variables and ensuring the design satisfies a safety-margin with respect to design constraints. After an initial design is selected, testing (e.g. physical experiment or high-fidelity simulation) is performed to reduce epistemic uncertainty and ensure the design achieves the targeted levels of safety. Testing is used to calibrate low-fidelity models and prescribe redesign when tests are not passed. After calibration, reduced epistemic model uncertainty can be leveraged through redesign to restore safety or improve design performance; however, redesign may be associated with substantial costs or delays. In this work, the possible effects of a future test and redesign are considered while the initial design is optimized using only a low-fidelity model. The goal is to develop a general method for the integrated optimization of the design, testing, and redesign process that allows for the tradeoff between the risk of future redesign and the associated performance and reliability benefits. This is accomplished by formulating the design, testing, and redesign process in terms of safety-margins and optimizing these margins based on expected performance, expected probability of failure, and probability of redesign. The first objective of this study is to determine how the degree of conservativeness in the initial design relates to the expected design performance after a test and possible redesign. The second objective is to develop a general method for modeling epistemic model uncertainty and calibration when simulating a possible future test and redesign. The third objective is to apply the method of simulating a future test and redesign to a sounding rocket design example.

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