Requirements uncertainty propagation in conceptual design using bayesian networks
Date published
2024-09-09
Free to read from
2024-10-22
Supervisor/s
Journal Title
Journal ISSN
Volume Title
Publisher
International Council of the Aeronautical Sciences (ICAS)
Department
Course name
Type
Conference paper
ISSN
2958-4647
Format
Citation
Spinelli A, Sharma A, Kipouros T. (2024) Requirements uncertainty propagation in conceptual design using bayesian networks. 34th Congress of the International Council of the Aeronautical Sciences, 9 - 13 Sep 2024, Florence, Italy
Abstract
This paper presents the application of a Bayesian Network as a tool for propagating the uncertainty between the aircraft-level design and the component-level design. The framework is applied to an example case in UAV design for payload transport. By querying the model, we demonstrate its ability to capture the casual relationships of the design problem and propagating the effects of design decisions on other parameters and requirements.
Description
Software Description
Software Language
Github
Keywords
Requirements uncertainty, Machine learning, Bayesian networks, UAV Conceptual design
DOI
Rights
Attribution 4.0 International
Funder/s
This project has received funding from Innovate UK under Grant Agreement No 10003388.