IFASD2024 Paper Submission & Registration
17 – 21 June 2024, The Hague, The Netherlands

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11:00   Aeroelastic optimisation 2
Chair: Andrea Da Ronch
30 mins
Including Gradient-based Transient Gust Optimization in ASTROS
Joshua Deslich, Doug Neill, Kevin McHugh, Raymond Kolonay
Abstract: Recent advancements in conceptual and preliminary air vehicle design seek to inject higher-fidelity analyses into early design processes to capture physics-based aircraft performance as soon as possible in the design cycle. This philosophy is often realized in the form of high-fidelity coupled aeroelastic or aeroservoelastic design via analysis including quasisteady maneuver behavior or flutter. However, there are relatively few efforts to include transient aeroelastic solutions in design, and those cases are limited in the context of a conceptual design process. This work seeks to leverage an existing aeroelastic solver, ASTROS, and enhance the design capability to include analytical stress gradients for designing a high aspect ratio wing under transient gust stress constraints. Previous development of ASTROS has excluded transient gusts from optimization due to computational cost and was primarily used for checking final designs. Including gust analysis in the early stages of aeroelastic conceptual design could mitigate late-stage redesigns to account for gust loads certification.
30 mins
Gradient-based Optimization of the Common Research Model Wing Subject to CFD-based Gust and Flutter Constraints
Andrew Thelen, Kevin Jacobson, Bret Stanford
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.
30 mins
Maneuver and gust loads alleviation using simultaneous layout and size optimization
Hammad Rahman
Abstract: The aviation industry is striving to create high-performance aircraft that consume less fuel. This involves using composite materials to reduce weight and implementing methods to alleviate aeroelastic loads. The stiffness of the wing, determined by the layout and sizing of its internal structure, is crucial. While traditional manufacturing constraints have limited layout configurations, recent advancements have enabled more complex layouts. To fully utilize the synergies between layout and sizing design variables, simultaneous optimization is essential. However, previous optimization studies often use gradient-free methods, which are easier to implement but restrict the design space due to a limited number of design variables. This limits the potential improvement that optimization can bring. This paper presents an innovative design strategy that simultaneously optimizes layout and size design variables using a gradient-based method. It employs a CAD modelling tool to parameterize the geometry. This CAD-based parameterization offers two advantages. First, it implicitly applies geometric constraints to ensure the perturbed wingbox layout conforms to the wing’s OML, eliminating the need for additional constraints on the grid point coordinates. Second, a link with the CAD model is maintained throughout the optimization process, as the same design variables are controlled by the optimizer. This eliminates the need for an additional step of converting the optimal design back to the CAD model. Instead of mesh morphing, a re-meshing strategy is employed. The sensitivities of the response with respect to both layout and size design variables are achieved through a semi-analytical method, which is a faster approach for calculating gradients compared to finite difference schemes. The CRM wing under aeroelastic constraints has been used as a design model. The design variables include the thickness of the design regions, as well as the individual rib and stiffener location and orientation. Gust loads are included using the Equivalent Static Load Method. The primary focus is to investigate the potential benefits of simultaneous layout and size optimization in alleviating the static and dynamic loads on the wing. These investigations are expected to provide valuable insights and additional ways to locally tailor the structure.

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