NASA SBIR 2018-II Solicitation

Proposal Summary


PROPOSAL NUMBER:
 18-2- A1.01-6962
PHASE 1 CONTRACT NUMBER:
 80NSSC18P1879
SUBTOPIC TITLE:
 Structural Efficiency - Aeroelasticity and Aeroservoelastic Control
PROPOSAL TITLE:
 An Intelligent Framework to Develop Adaptive Parametric Reduced Order Model Database for Aerostructural Control
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
CFD Research Corporation
701 McMillian Way Northwest, Suite D
Huntsville, AL 35806
(256) 726-4800

PRINCIPAL INVESTIGATOR (Name, E-mail, Mail Address, City/State/Zip, Phone)
Kapil Pant
kapil.pant@cfdrc.com
701 McMillian Way Northwest, Suite D
Huntsville, AL 35806 - 2923
(256) 726-4871

BUSINESS OFFICIAL (Name, E-mail, Mail Address, City/State/Zip, Phone)
Silvia Harvey
proposals-contracts@cfdrc.com
701 McMillian Way Northwest, Suite D
Huntsville, AL 35806 - 2923
(256) 726-4858

Estimated Technology Readiness Level (TRL) :
Begin: 4
End: 6
Technical Abstract (Limit 2000 characters, approximately 200 words)

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. In Phase 1, the framework for both equation-based and data-driven PROMs was developed and feasibility to introduce “engineering intelligence” to AE/ASE ROMs was successfully established. Carefully selected ROMs and intelligence algorithms were developed to accomplish autonomous PROM construction. It was verified that ROMs built under the guidance of intelligent algorithms enable unprecedented state consistence and computational performance. For the first time, data-driven ROMs with state consistence were developed in a broad flight envelope. Equation-based ASE PROMs were developed, and demonstrated >12X reduction in model size for control synthesis. In Phase 2, software will be further refined for enhanced performance and functionality. Genetic Algorithm (GA)-guided ROM algorithms will be improved in terms of search space exploration, meta-optimization, and state consistence. Adaptive sampling will be extended to multi-dimensional flight parameter space. Methods to integrate PROMs from separate domains, and sensors and controllers will be optimized to meet various needs in NASA. A modular intelligent environment will be integrated into NASA workflow for technology transition. The software will be extensively validated and demonstrated for automated ROM development, certification, and control design using flexible vehicles of NASA interest.

Potential NASA Applications (Limit 1500 characters, approximately 150 words)

The developed technology will enable NASA to (1) determine critical flight conditions and guide CFD/ASE computation and flight testing; (2) enable real-time ASE simulation and flight control synthesis, and (3) develop advanced aerostructural control strategies. It will markedly reduce development costs and cycles of aerospace vehicles. NASA projects like High Speed ASE, MUTT, and MADCAT will benefit from the technology

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)

The non-NASA applications include aerospace, aircraft, and watercraft engineering for fluid-structural interaction and fatigue analysis, flow control and optimization, hardware-in-loop simulation, and others. The proposed development can be used for (1) fault diagnostics and optimized design; (3) design and planning of simulations and experiments;  (2) development of advanced control strategies.

Duration:

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