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Reliability-based shape optimization of structures undergoing fluid–structure interaction phenomena
Affiliation:1. Strand 7, Sydney 2000, Australia;2. National Technical University of Athens, Institute of Structural Analysis & Seismic Research, 9 Iroon Polytechneio, Zografou Campus, 157 80 Athens, Greece;1. Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA;2. The Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA;3. Department of Structural Engineering, University of California, San Diego, La Jolla, CA 92093, USA;4. Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA;5. Departments of Pediatrics and Bioengineering, Stanford University, Stanford, CA 94305, USA
Abstract:Fluid–structure interaction phenomena are often roughly approximated when the stochastic nature of a system is considered in the design optimization process, leading to potentially significant epistemic uncertainty. In this paper, after reviewing the state-of-the-art methods in robust and reliability-based design optimization of problems undergoing fluid–structure interaction phenomena, a computational framework is presented that integrates a high-fidelity aeroelastic model into reliability-based design optimization. The design optimization problem is formulated pursuant to the reliability index and performance measure approaches. The system reliability is evaluated by a first-order reliability analysis method. The steady-state aeroelastic problem is described by a three-field formulation and solved by a staggered procedure, coupling a potentially detailed structural finite element model and a finite volume discretization of the Euler flow. The design and imperfection sensitivities are computed by evaluating the analytically derived direct and adjoint coupled aeroelastic sensitivity equations. The computational framework is verified by the optimization of three-dimensional wing structures. The lift-to-drag ratio is maximized, subject to stress constraints, by varying shape, thickness, and material properties. Uncertainties in structural parameters, including design parameters, operating conditions, and modeling uncertainties are considered. The results demonstrate the need for reliability-based optimization methods, for the design of structures undergoing fluid–structure interaction phenomena, and the applicability of the proposed framework to realistic design problems. Comparing the optimization results for different levels of uncertainty shows the importance of accounting for uncertainties in a quantitative manner.
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