CFD-based aeroelastic reduced-order modeling robust to structural parameter variations

Winter, Maximilian; Heckmeier, Florian M.; Breitsamter, Christian

doi:10.1016/j.ast.2017.03.030

Cited by 27 publications

(22 citation statements)

References 24 publications

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“…The applications range from the calculation of dynamic stability derivatives [10,11] to aero-servo-elastic investigations [12] to the generation of reduced order models [13]. However, in the context of this work the method is used for the CFD-based computation of the generalized aerodynamic forces for use in conventional linear flutter analysis.…”

Section: Introductionmentioning

confidence: 99%

CFD-Based Aeroelastic Sensitivity Study of a Low-Speed Flutter Demonstrator

et al. 2019

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The goal of developing aircraft that are greener, safer and cheaper can only be maintained through significant innovations in aircraft design. An integrated multidisciplinary design approach can lead to an increase in the performance of future derivative aircraft. Advanced aerodynamics and structural design technologies can be achieved by both passive and active suppression of aeroelastic instabilities. To demonstrate the potential of this approach, the EU-funded project Flutter Free Flight Envelope Expansion for Economical Performance Improvement is developing an unmanned aerial vehicle with a high-aspect-ratio-wing and clearly defined flutter characteristics. The aircraft is used as an experimental test platform. The scope of this work is the investigation of the aeroelastic behaviour of the aircraft and the determination of its flutter limits. The modeling of unsteady aerodynamics is performed by means of the small disturbance CFD approach that provides higher fidelity compared to conventional linear-potential-theory-based methods. The CFD-based and the linear-potential-theory-based results are compared and discussed. Furthermore, the sensitivity of the flutter behaviour to the geometric level of detail of the CFD model is evaluated.

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Section: Introductionmentioning

confidence: 99%

CFD-Based Aeroelastic Sensitivity Study of a Low-Speed Flutter Demonstrator

et al. 2019

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“…Zhang (Zhang et al, 2015) demonstrated a method to obtain a new ROM using existing CFD-based auto regressive with eXogenous input (ARX) ROM based on radial basis function (RBF) interpolation functions for local changes of the root boundary condition. Winter (Winter et al, 2017) presented two novel CFD based reduced-order modeling methodologies robust to variations in the structural modeshapes due to the additional lumped mass.…”

Section: Introductionmentioning

confidence: 99%

An efficient implementation of aeroelastic tailoring based on efficient computational fluid dynamics-based reduced order model

Gong

Ronch

et al. 2019

Journal of Fluids and Structures

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Current and future trends in the aerospace industry leverage on the potential benefits provided by lightweight materials that can be tailored to realize desired mechanical characteristics when loaded. For aircraft design, the deployment of aeroelastic tailoring is hindered by the need to re-compute, for any possible modification of the structure, the dependence of the aerodynamic field on the underlying structural properties. To make progress in this direction, the work presents a rapid computational fluid dynamics based aeroelastic tool which is built around a reduced order model for the aerodynamics that is updated for any modification of the structure by using the structural dynamics reanalysis method. The aeroelastic tailoring tool is demonstrated in transonic flow for the AGARD 445.6 wing, suitably modified with composite materials. It was found that the proposed method provides accurate engineering predictions for the aeroelastic response and stability when the structure is modified from the baseline model.

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“…Only one run of CFD process is required in structural optimization/UQ. Under the same framework, (Winter et al, 2017) proposed another ROM-AMS where Chebyshev polynomials are selected as basis mode shapes, which can capture the global features of physical mode shapes.…”

Section: Introductionmentioning

confidence: 99%

“…However, in (Winter et al, 2017;Zhang et al, 2015a), the number of required basis mode shapes is relatively large. Take ARX model as example, with same delay order, the number of parameters to be identified is square with the number of the basis modes.…”

Section: Introductionmentioning

confidence: 99%

A novel unsteady aerodynamic Reduced-Order Modeling method for transonic aeroelastic optimization

Wang

Zhang

et al. 2018

Journal of Fluids and Structures

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In aircraft design, structural optimization and uncertainty quantification concerning transonic aeroelastic issues are computationally impractical, because the iterative process requires great number of aeroelastic analysis. Emerging Reduced-Order Model (ROM) method is convenient for transonic aeroelastic analysis. However, current ROMs cannot be reused during iteration, thus time cost is still way too large. This study proposed an improved ROM suitable for Arbitrary Mode Shapes (ROM-AMS), which is reusable regardless the variation of design variables. By adopting Principal Component Analysis, ROM-AMS method can significantly reduce the number of basis mode shapes and improve the accuracy of flutter analysis. In an optimization case, the weight of cropped delta wing is reduced by 28.46%, and the efficiency is 900 times higher than traditional ROM method, which demonstrates the feasibility of this method in iterative design process.

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CFD-based aeroelastic reduced-order modeling robust to structural parameter variations

Cited by 27 publications

References 24 publications

CFD-Based Aeroelastic Sensitivity Study of a Low-Speed Flutter Demonstrator

CFD-Based Aeroelastic Sensitivity Study of a Low-Speed Flutter Demonstrator

An efficient implementation of aeroelastic tailoring based on efficient computational fluid dynamics-based reduced order model

A novel unsteady aerodynamic Reduced-Order Modeling method for transonic aeroelastic optimization

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