Efe Yamac Yarbasi
(Advisor: Prof. Dimitri Mavris]

will propose a doctoral thesis entitled,

A Methodology for Identifying Experiments for Uncertainty Mitigation in Complex Multi-Disciplinary Design

On

Monday, February 21 at 1:30 p.m.
Collaborative Design Environment (CoDE)
Weber Space Science and Technology Building (SST II)

https://bluejeans.com/265188272/8505

Abstract
Development of a flight vehicle is a long, costly process that take many years. Thanks to increase in computational capabilities, designers usually rely on computer models to make predictions about the performance of an aircraft under corresponding operational conditions. However, due to uncertainties in physics phenomena, modeling, and abstractions in product details; the results obtained from computational tools are never exact. Therefore, minimizing uncertainty in design is a common objective for everyone in the aerospace industry. The objective of this thesis is to develop a methodology to identify and mitigate the sources uncertainty in aircraft design.

An aircraft is a complex system which consists of other highly complex subsystems. These subsystems are modeled using computational tools under a set of assumptions and model abstractions. Uncertainties in subsystem simulations propagate to the system level, reducing the confidence in the performance predictions of the aircraft. The first research area of this thesis is to develop a systematic method to create a fit-for-purpose modeling and simulation environment that enables uncertainty identification and characterization, while following established systems engineering principles. The second research area addresses issues faced in identifying these uncertainties. The impact of subjectivity on simulation inputs and top-down uncertainty allocation have been identified as potential improvement areas for this work. After the critical uncertainties are identified, computational and/or physical experiments can be designed to create new information, so that any uncertainty due to a lack of knowledge can be reduced. The third research area of this work aims to leverage computational experiments to design sub-scale physical experiments to better represent the full-scale while accounting for external constraints such as test facility dimensions.

Committee

• Prof. Dimitri Mavris – School of Aerospace Engineering (advisor)
• Prof. Daniel Schrage – School of Aerospace Engineering
• Prof. Graeme Kennedy – School of Aerospace Engineering
• Dr. Burak Bagdatli – School of Aerospace Engineering