Ph.D. Proposal
Tavish Pattanayak
(Advisor: Prof. Dimitri Mavris)
A Methodology for Optimizing Testing Strategies TowardsTechnology Maturation: An Uncertainty Quantification Approach
Friday, November 08
10:00 a.m.
Collaborative Visualization Environment (CoVE)
and
Abstract
The aviation industry faces a critical challenge in reducing its environmental impact while meeting the growing demand. Hybrid Electric Propulsion (HEP) presents a promising solution, aiming to lower emissions, noise, and operational costs. However, maturing HEP technologies to be useful for commercial aircraft poses significant challenges. For HEP to achieve commercial viability, numerous emerging technologies must advance to a certain level of feasibility. Currently, there exists considerable uncertainty at the component level, which is not well understood. To accelerate technology maturation, it is crucial to identify, characterize, propagate, and reduce these uncertainties.
Existing testing methodologies fall short in two key areas. First, they primarily focus on demonstrating functionality rather than quantifying uncertainty reduction. Second, they struggle to connect component-level insights to system-level performance. This work aims to address these gaps by developing a robust methodology that links testing to technology maturation. This will be achieved through a three-pronged research approach, the first of which is the quantification and the propagation of epistemic uncertainties from the component level to the system level. The second step is developing a multi-attribute decision-making framework to prioritize the components that need to be tested. The third and final step proposed in this thesis is the implementation of a data-driven, uncertainty-aware approach that will be used for planning and/or scheduling research activities. The expected outcome is a comprehensive methodology that will bridge the gap between testing and technology maturation. This will be achieved by leveraging uncertainty quantification techniques and establishing clear connections between component-level insights and the feasibility of the integrated HEP system.
This methodology is anticipated to yield several benefits. Firstly, it will enable more efficient resource allocation strategies, optimizing the use of time, manpower, and funding in research and development efforts. Secondly, it will accelerate the maturation of HEP technologies, bringing them closer to commercial readiness. Furthermore, the research will provide a deeper understanding of the uncertainties associated with hybrid-electric aircraft, facilitating swifter maturation and integration of HEP in aviation. Ultimately, this work aims to overcome the technological barriers currently impeding HEP's path to commercial viability. While focused on hybrid-electric propulsion in aviation, the developed methodology has broader applications. It can be adapted to a wide variety of emerging technologies across different fields, offering a systematic approach to uncertainty management and technology maturation.
Committee
- Prof. Dimitri Mavris – School of Aerospace Engineering (advisor)
- Prof. Daniel Schrage – School of Aerospace Engineering
- Prof. Graeme Kennedy – School of Aerospace Engineering
- Dr. Andrew Meade – NASA Ames
- Dr. Raphael Gautier – School of Aerospace Engineering