Digital Assistance for System Requirement Discovery and Analysis using Machine Learning Natural Language Processing Algorithm

Nipa Phojanamongkolkij; Braxton VanGundy; Ian Levitt; Heidi Glaudel

NASA NTRS · 20220013407

Digital Assistance for System Requirement Discovery and Analysis using Machine Learning Natural Language Processing Algorithm

Nipa Phojanamongkolkij·Braxton VanGundy·Ian Levitt·Heidi Glaudel

Abstract

NASA’s Air Traffic Management-Exploration (ATM-X) Urban Air Mobility (UAM) Airspace Subproject is conducting research that evolves UAM airspace towards a highly automated and operationally flexible system of the future (see https://www.nasa.gov/uam-overview/ for more information). The complexity of UAM airspace, and its evolution through a series of transformative epochs, requires a planning tool to effectively organize, integrate, and communicate the research that will guide the evolution of UAM operations in the National Airspace System (NAS). The planning tool, called the UAM airspace research roadmap (or just roadmap), is being developed as a new system engineering methodology leveraging model based system engineering (MBSE) and machine learning natural language processing (ML NLP, or just NLP) capabilities. This presentation gives an overview of the NLP application within this system engineering methodology and will describe how it is being used to meet the ATM-X UAM Airspace Subproject’s overarching research goals.

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ATM UAM MBSE ML NLP Digital Transformation systems engineering requirement analysis

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Nipa Phojanamongkolkij, Braxton VanGundy, Ian Levitt, Heidi Glaudel. Digital Assistance for System Requirement Discovery and Analysis using Machine Learning Natural Language Processing Algorithm. https://ntrs.nasa.gov/citations/20220013407

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