An Intelligent Framework to Develop Adaptive Parametric Reduced Order Model Database for Aerostructural Control, Phase I

The goal of the project is to develop an intelligent framework to construct adaptive parametric reduced order model (PROM) database for aeroservoelastic (ASE) analysis and aerostructural control. Leveraging on significant advancements by the proposing team in prior research, this Phase I effort will initiate a new frontier of ‘engineering intelligence’ to further ASE ROM development, including several emerging techniques: genetic algorithm optimization-guided ROMs, data-driven ROM for nonlinear aeroelasticity and gust response analysis, online determination of critical flight conditions and in-situ PROM database development while modeling, CFD computation, and ROM are in progress. A modular software framework will be established for automated PROM generation and optimization, consistent state enforcement, adaptive parameter space sampling, and database population. The feasibility of the proposed technology will be demonstrated for ASE problems of NASA interest (e.g., High-speed ASE, X-56A MUTT, etc.). The Phase II effort will focus on: (1) PROM engine optimization in terms of execution efficiency, robustness, and autonomy; and (2) direct integration of the ‘intelligent’ environment into NASA workflow; and process automation of modeling, simulation, and control synthesis for technology insertion and transition; and (3) extensive software validation and demonstration for ASE and flight control analysis of realistic aircrafts of current NASA interest

Data and Resources

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identifier TECHPORT_94493
issued 2019-01-01
landingPage https://techport.nasa.gov/view/94493
modified 2020-01-29
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metadata_created 2025-11-19T22:19:46.004481
metadata_modified 2025-11-19T22:19:46.004485
notes <p>The goal of the project is to develop an intelligent framework to construct adaptive parametric reduced order model (PROM) database for aeroservoelastic (ASE) analysis and aerostructural control. Leveraging on significant advancements by the proposing team in prior research, this Phase I effort will initiate a new frontier of &lsquo;engineering intelligence&rsquo; to further ASE ROM development, including several emerging techniques: genetic algorithm optimization-guided ROMs, data-driven ROM for nonlinear aeroelasticity and gust response analysis, online determination of critical flight conditions and <em>in-situ</em> PROM database development while modeling, CFD computation, and ROM are in progress. A modular software framework will be established for automated PROM generation and optimization, consistent state enforcement, adaptive parameter space sampling, and database population. The feasibility of the proposed technology will be demonstrated for ASE problems of NASA interest (e.g., High-speed ASE, X-56A MUTT, etc.). The Phase II effort will focus on: (1) PROM engine optimization in terms of execution efficiency, robustness, and autonomy; and (2) direct integration of the &lsquo;intelligent&rsquo; environment into NASA workflow; and process automation of modeling, simulation, and control synthesis for technology insertion and transition; and (3) extensive software validation and demonstration for ASE and flight control analysis of realistic aircrafts of current NASA interest</p>
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title An Intelligent Framework to Develop Adaptive Parametric Reduced Order Model Database for Aerostructural Control, Phase I