MS Defense by Ian Marks
[Advisor: Prof. Dimitri Mavris]
will defend a Masters thesis entitled,
ASSESSING AN AEROSPACE APPLICATION OF DIGITAL TWINS FOR MULTI AGENT DYNAMIC DECISION MAKING
Friday, November 4th at 11:00 a.m.
Teams: Click here to join the meeting
Dynamic Decision Making (DDM) requires a series of interdependent decisions to achieve some overall goal while adapting to the results of previous decisions alongside environmental changes. Examples of DDM in application vary from individual predictive maintenance to activity tasking. When making dynamic decisions in a multi-agent scenario, the goal is to minimize uncertainty for future actions by predicting consequences for both the individual and the multi-agent group. Recent developments in Digital Twins show the potential to improve the dynamic decision-making process by providing unique agent state information and predictions to the decision maker. With AIAA’s definition of a digital twin being a virtual representation of a connected physical system, the aspects of computational and physical requirements impact the overall capability (fidelity) and utility (runtime, proximity, latency) of their infusion. The research performed develops a method of evaluating the infusion of Digital Twins in a multi agent DDM architecture with their inherent challenges compares the performance to historically deterministic processes for a relevant aerospace scenario.
- Prof. Dimitri Mavris – School of Aerospace Engineering (advisor)
- Dr. Olivia Pinon Fischer - School of Aerospace Engineering
- Mr. Noah Fehrenbacher – Lockheed Martin (Digital Twin Chief Engineer)
- Workflow Status: Published
- Created By: Tatianna Richardson
- Created: 11/03/2022
- Modified By: Tatianna Richardson
- Modified: 11/03/2022