A practical approach to MDO and its application to an HSCT aircraft (Multidisciplinary Design Optimization)

Baker, Myles L.; Giesing, Joe

doi:10.2514/6.1995-3885

Cited by 10 publications

(4 citation statements)

References 1 publication

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“…Notice that Eqs. (27) and (28) are directly proportional to the bending moments found by Prandtl in Eq. 7.…”

Section: B Hunsaker's Formulationmentioning

confidence: 85%

“…In place of FEA structural models, beam models [19][20][21][22] and weight equations derived statistically, 24 using response-surface methodology, 25 or other methods 21 have been used. Multi-fidelity aerostructural optimization routines have been successfully used for a wide variety of aircraft configurations, including subsonic configurations, [15][16][17][18] supersonic transports, [26][27][28] and rotorcraft. 29,30 Low-fidelity optimization routines are generally used for conceptual-level design.…”

Section: Introductionmentioning

confidence: 99%

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Numerical Algorithm for Wing-Structure Design

Taylor

Hunsaker

Joo

2018

2018 AIAA Aerospace Sciences Meeting

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“…Notice that Eqs. (27) and (28) are directly proportional to the bending moments found by Prandtl in Eq. 7.…”

Section: B Hunsaker's Formulationmentioning

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Numerical Algorithm for Wing-Structure Design

Taylor

Hunsaker

Joo

2018

2018 AIAA Aerospace Sciences Meeting

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“…The structural optimization of the HSCT wing box structure was performed using automated structural optimization system (ASTROS) code [6]. A jig-shape optimization of an HSCT wing was also performed by Baker and Giesing [7] using aeroelastic design optimization (ADOP) [8] and advanced integrated loads subsystem (AILS) [9] codes. In the study by Baker and Giesing, the takeoff gross weight of the baseline HSCT aircraft was decreased by adjusting the wing jig twist.…”

Section: Introductionmentioning

confidence: 99%

Jig-Shape Optimization of Low-Boom Supersonic Aircraft

Pak

2018

Journal of Aircraft

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A simple approach for optimizing the jig-shape is proposed in this study. This simple approach is based on an unconstrained optimization problem and applied to a low-boom supersonic aircraft. In this study, the jig-shape optimization is performed using the two-step approach. First, starting design variables are computed using the least-squares surface fitting technique. Next, the jig-shape is further tuned using a numerical optimization procedure based on an in-house object-oriented optimization tool. During the numerical optimization procedure, a design jig-shape is determined by the baseline jig-shape and basis functions. A total of 12 symmetric mode shapes of the cruise-weight configuration, rigid pitch shape, rigid left and right stabilator rotation shapes, and a residual shape are selected as sixteen basis functions. After three optimization runs, the trim shape error distribution is improved, and the maximum trim shape error of 0.9844 inches of the starting configuration becomes 0.00367 inch by the end of the third optimization run.

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“…Borland et al [9], Chattopadhyay and Pagaldipti [10] and Baker and Giesing [11] started using high-fidelity methods within the MDO problem, but were only able to afford a limited amount of design variables. In continuation, Manning [12] demonstrates large-scale design using industry-standard analyses and Barcelos and Maute [13] present the effects of viscous drag inclusion in high-fidelity aerodynamic analysis.…”

Section: Introduction and Problem Descriptionmentioning

confidence: 99%

Wing aerostructural optimization using the Individual Discipline Feasible Architecture

Hoogervorst

Elham

2017

Aerospace Science and Technology

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SUMMARYThis thesis presents an effort to contribute to the minimization of fuel use of aircraft. The intention is to achieve this efficiently by using the Individual Discipline Feasible architecture for solving a gradient-based, aerostructural Multidisciplinary Design Optimization problem for a static aeroelastic wing. This wing is then optimized for minimal fuel consumption during the cruise phase.The work in this paper is an effort continuing in the trend of using high-fidelity analyses for optimization of an aeroelastic wing. However this effort makes use of the Individual Discipline Feasible architecture, which decouples the aerodynamic and structural disciplines from each other. Using this approach the consistency of the system as a whole is maintained by the use of equality constraints on surrogate design variables. No coupled sensitivity information is required because of this decoupled system. This makes the system not only simpler, but also provides more freedom in software choice. Furthermore, the time to perform optimization is reduced with respect to the traditional Multidisciplinary Feasible architecture as the work of making the system consistent is removed from the computationally expensive individual disciplines and put it in the hands of the cheap optimization algorithm.The aerodynamic and the structural disciplines hence independently calculate both the intermediate states of the system and the partial derivatives of these states with respect to the design vector. The performance module is dependant on the aerodynamic discipline and is therefore included in it. This module calculates the fuel weight.SU2 is used within the aerodynamic discipline to deform the surface grid and the volume grid of the wing and its domain, calculate the flow properties and gain sensitivities of lift and drag with respect to surface perturbations of the wing. The software uses the 3D Free-Form Deformation parameterization technique to deform the surface grid. The code is originally meant to only deform the airfoil shapes of a wing, nevertheless it has been modified in order to also deform the wing according to the static aeroelastic deformation. The sensitivity analysis is performed by a continuous adjoint solver. It is shown however that the continuous adjoint method in SU2 does not capture the sensitivities of the trailing edge well due to assumptions of smoothness. This is why extra corrective factors are added to the false sensitivities. The results of the optimization verify the working of these corrective factors, except for the corrected sensitivities with respect to the planform design variables. The Euler model is used for the flow analysis, due to its speed advantages. However, because viscosity is neglected in the Euler model, the viscous drag component and its sensitivity derivatives are estimated by a separate module.For the structural discipline the FEMWET software is used, providing the static aeroelastic deformation and the aeroelastic axis of the wing. FEMWET uses equivalent panel thicknesses represe...

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A practical approach to MDO and its application to an HSCT aircraft (Multidisciplinary Design Optimization)

Cited by 10 publications

References 1 publication

Numerical Algorithm for Wing-Structure Design

Numerical Algorithm for Wing-Structure Design

Jig-Shape Optimization of Low-Boom Supersonic Aircraft

Wing aerostructural optimization using the Individual Discipline Feasible Architecture

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