An Overview of a JMP® Decision Support System for Technology Assessment and Advanced Concepts Analysis for NASA’s Environmentally Responsible Aviation Project
Authors
John Salmon, PhD, Assistant Professor of Mechanical Engineering, Brigham Young University Jeff Schutte, PhD, Research Engineer, Aerospace Systems Design Laboratory, Georgia Tech
This paper will summarize the capabilities of a JMP-based decision support system (DSS) developed for the NASA Environmentally Responsible Aviation (ERA) research project currently underway at the Aerospace Systems Design Laboratory (ASDL). The ERA project analyzes system-level impacts for subsonic transport technologies integrated into advanced vehicle concepts that simultaneously meet the project metrics for noise, emissions and fuel burn. Interactive, parametric models become key enablers for e-review sessions to rapidly explore and analyze the design space of potential technologies across the multiple conflicting objectives. Various visualizations and use-cases from the DSS will be explored, including Pareto optimal technology packages, technology uncertainty analysis using probabilistics, MATLAB model integration, and noise contour evaluation at airports.
Published on 03-24-202509:02 AM by
Ryan_Gilmore| Updated on 03-27-202509:50 AM
Authors
John Salmon, PhD, Assistant Professor of Mechanical Engineering, Brigham Young University Jeff Schutte, PhD, Research Engineer, Aerospace Systems Design Laboratory, Georgia Tech
This paper will summarize the capabilities of a JMP-based decision support system (DSS) developed for the NASA Environmentally Responsible Aviation (ERA) research project currently underway at the Aerospace Systems Design Laboratory (ASDL). The ERA project analyzes system-level impacts for subsonic transport technologies integrated into advanced vehicle concepts that simultaneously meet the project metrics for noise, emissions and fuel burn. Interactive, parametric models become key enablers for e-review sessions to rapidly explore and analyze the design space of potential technologies across the multiple conflicting objectives. Various visualizations and use-cases from the DSS will be explored, including Pareto optimal technology packages, technology uncertainty analysis using probabilistics, MATLAB model integration, and noise contour evaluation at airports.
