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CC BY V4.0, Open Access
Conference proceeding
A Regulatory Analysis and Process Improvement Decision Support Framework for Unmanned Aerial System (UAS) Noise Certification
Quet Drones (Manchester, England, 09/08/2024–09/11/2024)
09/2024
Appears in Aviation Sustainability Center (ASCENT)
Abstract
The rapidly growing Unmanned Aerial Systems (UAS) vehicle category with applications across various configurations and mission profiles introduces challenges in ensuring that applicable noise certification regulations are met. A framework is proposed for assessing regulatory compliance to noise standards and analyzing the process effectiveness and outcomes of noise testing campaigns for UAS. This framework is enabled by a Model-based Systems Engineering (MBSE) workflow for creating verification models that represent requirements derived by applicable regulations under the CFR Part 36 noise certification. As a digital thread-enabled approach, this environment allows for tracking and assessing adherence to noise regulatory practices through mapping noise data flows from test campaigns to metrics of interest as part of the verification of meeting regulatory noise requirements. Moreover, the environment allows for the assessment of the certification process eliminating unnecessary redundancies. The assessment of improvement strategies and selection of testing procedures is demonstrated through an integrated decision support dashboard for a small multi-rotor electric Vertical Takeoff and Landing (eVTOL) vehicle operated for a package delivery mission.
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Details
- Title
- A Regulatory Analysis and Process Improvement Decision Support Framework for Unmanned Aerial System (UAS) Noise Certification
- Creators
- Michael Balchanos (Author)Balaji Ravikanti (Author)Hussein Ali (Author)Hajar Mali (Author)Evan Harrison (Author)Dimitri N. Mavris (Author) - Georgia Institute of Technology
- Conference
- Quet Drones (Manchester, England, 09/08/2024–09/11/2024)
- Academic Unit
- Aviation Sustainability Center (ASCENT); Alternative Jet Fuel
- Grants
- 13-C-AJFE-GIT-066, Federal Aviation Administration (United States, Washington) - FAA
- Identifiers
- 99901177541401842
- Language
- English
- Resource Type
- Conference proceeding