A Bayesian Technology Maturation Framework Applied to Structural Test Design
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Baker, Adam
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Abstract
The current technology development process is characterized by a holistic combination of modeling, expert judgment, and benchmark testing. Technologies are characterized through the assignment of an ordinal technology readiness level and then progress through pre-defined benchmark tests based on that assigned level. This is potentially problematic as the prescribed tests may or may not suitably address the underlying areas of uncertainty in the technology. Restricting the use of data from tests to deterministic passing or failing grades for benchmark performance levels is reductive and both fails to fully exploit the information that is generated by these tests and is potentially problematic as it falsely assumes the result will always be repeatable and reproducible.
The purpose of this research is to develop a framework that will reframe the technology development process to be defined based on the underlying uncertainty sources in a technology. This requires creating a baseline representation of uncertainty in a technology, identifying how these uncertainties impact the system of interest, and finally showing how these uncertainties can be addressed through Bayesian inference using test results. This inference can both leverage test data to reduce the uncertainty in phenomenological properties of the technology and challenge the input assumptions or computational models for the technology. The common thread of uncertainty throughout the technology development process creates traceability within the process and generates actionable data at every step. It is then demonstrated how this resulting framework enables the design of physical tests that can optimally address the underlying sources of uncertainty in a technology. This, in turn, enables enhanced decision-making for testing, as a efficacy of a given test for reducing uncertainty can be traded off against the cost of that test. The results demonstrate that a Bayesian framework has the capacity to adequately capture the various forms of information generated in the current technology maturation process and will create traceability that can enable the exploitation of test data and the design of physical tests for an individual technology.
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2025-04-23
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Dissertation