Aeroelasticity & Structural Dynamics in a Fast Changing World
17 – 21 June 2024, The Hague, The Netherlands
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Gradient-based Optimization of the Common Research Model Wing Subject to CFD-based Gust and Flutter Constraints


Go-down ifasd2024 Tracking Number 69

Presentation:
Session: Aeroelastic optimisation 2
Room: Room 1.1
Session start: 11:00 Tue 18 Jun 2024

Andrew Thelen   andrew.s.thelen@nasa.gov
Affifliation: NASA Langley Research Center

Kevin Jacobson   kevin.e.jacobson@nasa.gov
Affifliation: NASA Langley Research Center

Bret Stanford   bret.k.stanford@nasa.gov
Affifliation: NASA Langley Research Center


Topics: - Steady/Unsteady Aerodynamics (High and low fidelity (un)coupled analysis methods:), - Computational Aeroelasticity (High and low fidelity (un)coupled analysis methods:), - Dynamic Loads (High and low fidelity (un)coupled analysis methods:), - Highly Flexible Aircraft Structures (High and low fidelity (un)coupled analysis methods:), - Aeroelasticity in Conceptual Aircraft Design (Vehicle analysis/design using model-based and data driven models)

Abstract:

The linearized frequency-domain method was recently implemented in the stabilized finite element solver in NASA’s FUN3D code. Previous work by the authors used this method for enforcing flutter constraints during gradient-based optimizations. More recently, the solver was expanded to account for continuous (also known as stochastic) gust responses. This paper expands on recent Common Research Model wing optimization work, which demonstrated gradient-based optimization with flutter and stochastic gust constraints, among others. While that work utilized FUN3D for static aeroelastic solutions but relied on doublet lattice aerodynamics for gust and flutter responses, the present work replaces these unsteady aerodynamic analyses with those of FUN3D’s linearized frequency-domain solver. With analytic derivatives available, gradient-based optimization is performed through the use of the OpenMDAO/MPhys libraries with over 700 shape, structural, and aerodynamic design variables and over 10 nonlinear constraints. Comparisons of analysis results and optimized designs are made between doublet lattice and linearized frequency-domain solutions.