On Aerodynamic Optimization Under a Range of Operating Conditions

Zingg, David W.; Elias, Samy

doi:10.2514/6.2006-1053

Cited by 10 publications

(8 citation statements)

References 10 publications

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“…Off-design performance has not been considered here, as proof of the optimization method's capability is the primary aim of this paper, but future work will include multi-point optimization using either several objective functions or combining those at different cases, as in [47,48].…”

Section: Discussionmentioning

confidence: 99%

High‐fidelity aerodynamic shape optimization of modern transport wing using efficient hierarchical parameterization

Morris

Allen

Rendall

2009

Numerical Methods in Fluids

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SUMMARYAerodynamic shape optimization technology is presented, using an efficient domain element parameterization approach. This provides a method that allows geometries to be parameterized at various levels, ranging from gross three-dimensional planform alterations to detailed local surface changes. Design parameters control the domain element point locations and, through efficient global interpolation functions, deform both the surface geometry and corresponding computational fluid dynamics volume mesh, in a fast, high quality, and robust fashion. This results in total independence from the mesh type (structured or unstructured), and optimization independence from the flow-solver is achieved by obtaining gradient information for an advanced gradient-based optimizer by finite-differences. Hence, the optimization tool can be used in conjunction with any flow-solver and/or mesh generator. Results have been presented recently for two-dimensional aerofoil cases, and shown impressive results; drag reductions of up to 45% were demonstrated using only 22 active design parameters. This paper presents the extension of these methods to three dimensions, with results for highly constrained optimization of a modern aircraft wing in transonic cruise. The optimization uses combined global and local parameters, giving 388 design variables, and produces a shock-free geometry with an 18% reduction in drag, with the added advantage of significantly reduced root moments.

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Section: Discussionmentioning

confidence: 99%

High‐fidelity aerodynamic shape optimization of modern transport wing using efficient hierarchical parameterization

Morris

Allen

Rendall

2009

Numerical Methods in Fluids

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“…The first is that to apply it successfully requires careful selection of both the design points (although these are often known a priori ), and the weightings between the objectives at those design points. This issue can be eased by using automated weight selections, 24,25 or an integral approach. 26 The second common issue is the cost surrounding multipoint optimization.…”

Section: 22 23mentioning

confidence: 99%

Objective Function and Constraints for Robust Transonic Aerofoil Optimization

Poole

Allen

Rendall

2017

58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Construction of the aerodynamic optimization problem is considered within the context of robustness. The most common aerodynamic optimization problem considered is a liftconstrained drag minimization problem (also subject to geometric constraints), however, point-design at transonic flow conditions can produce shock-free solutions and therefore the result is highly localised, where the gains obtained at the design point are outweighed by the losses at off-design conditions. As such, a range optimization problem subject to a constraint on fixed non-dimensional lift with a varying design point is considered to mitigate this issue. It is shown, first from an analytical treatment of the problem, and second from inviscid optimizations, that more robust solutions are obtainable when considering range optimization against drag minimization. Furthermore, to effectively capture the trade-offs that exist in three-dimensional aircraft design between range, lift, drag and speed, it is shown that an induced drag factor is required and this is sufficient to produce optimal solutions exhibiting shocks.

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“…A problem with multipoint optimization noted by several researchers 5,14 is that the appropriate off-design weights are not known a priori. As implied by the findings of Zingg and Billing, a poor assignment of off-design weights will result in one of two outcomes:…”

Section: Introductionmentioning

confidence: 99%

Airfoil Optimization Using Practical Aerodynamic Design Requirements

Buckley

Zhou

Zingg

2010

Journal of Aircraft

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Practical aerodynamic design problems must balance the goal of performance optimization over a range of on-design operating conditions with the need to meet design constraints at various off-design operating conditions. Such design problems can be cast as multipoint optimization problems where the on-design and off-design operating conditions are represented as design points with corresponding objective/constraint functions. Two methods are presented for obtaining optimal airfoil designs that satisfy all design objectives and constraints. The first method uses an unconstrained optimization algorithm where the optimal design is achieved by minimizing a weighted sum of the objective functions at each of the operating conditions. To address the competing design objectives between on-design and off-design operating conditions, an automated procedure is used to efficiently weight the off-design objective functions so as to limit their influence on the overall optimization while satisfying the design constraints. The second method uses the constrained optimization algorithm SNOPT, which allows the aerodynamic constraints imposed at the off-design operating conditions to be treated explicitly. Both methods are applied to the design of an airfoil for a hypothetical aircraft where the problem is formulated as an 18-point multipoint optimization.

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On Aerodynamic Optimization Under a Range of Operating Conditions

Cited by 10 publications

References 10 publications

High‐fidelity aerodynamic shape optimization of modern transport wing using efficient hierarchical parameterization

High‐fidelity aerodynamic shape optimization of modern transport wing using efficient hierarchical parameterization

Objective Function and Constraints for Robust Transonic Aerofoil Optimization

Airfoil Optimization Using Practical Aerodynamic Design Requirements

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