*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Mayank Bendarkar
(Advisor: Prof. Dimitri Mavris)
will defend a doctoral thesis entitled,
An Integrated Framework to Evaluate Off-Nominal Requirements and Reliability of Novel Aircraft Architectures in Early Design
Friday, April 9th at 2:00 pm
Meeting Link: https://bluejeans.com/114374164
Abstract
One of the barriers to the development of novel aircraft architectures and technologies is the uncertainty related to their reliability and the safety risk they pose. In the conceptual and preliminary design stages, traditional system safety techniques rely on heuristics, experience, and historical data to assess these requirements. The limitations and off-nominal operational considerations generally postulated during traditional safety analysis may not be complete or correct for new concepts. Additionally, dearth of available reliability data results in poor treatments of epistemic and aleatory uncertainty for novel aircraft architectures.
Two performance-based methods are demonstrated to solve the problem of improving the identification and characterization of safety related off-nominal requirements in early design. The problem of allocating requirements to the unit level is solved using a network-based bottom-up analysis algorithm combined with the Critical Flow Method. A Bayesian probability approach is utilized to better deal with epistemic and aleatory uncertainty while assessing unit level failure rates. When combined with a Bayesian decision theoretic approach, it provides a mathematically backed framework for compliance finding under uncertainty. To estimate multi-state reliability of complex systems, this dissertation contributes a modified Monte-Carlo algorithm that uses the Bayesian failure rate posteriors previously generated. Finally, multi-state importance measures are introduced to determine the sensitivity of different hazard severity to unit reliability.
The developed tools, techniques, and methods of this dissertation are combined into an integrated framework with the capability to perform trade-studies informed by safety and reliability considerations for novel aircraft architectures in early preliminary design. A test distributed electric propulsion (T-DEP) aircraft inspired by the X-57 is utilized as a test problem to demonstrate this framework.
Committee
