Aerodynamic Shape Optimization Progress on ADODG Benchmark Problems Using the elsA Software

Dumont, Antoine; Méheut, Michaël; Baumgärtner, Daniel; Bletzinger, Kai‐Uwe

doi:10.2514/6.2017-4081

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…If shape optimization in computational aerodynamics has been mostly dedicated to wing design [3][4][5][6], several studies have also applied these methods to engine nacelles (including inlet, external cowls and nozzles). In the 90's, Bell et al [7] used an inverse optimization technique based on pressure distributions for the design of 2D and 3D nacelles with Euler flow computations.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic shape optimization of aircraft engine nozzles based on Computer-Aided Design

Bagy

Mohammadi²,

Méheut³

et al. 2020

AIAA Scitech 2020 Forum

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This study presents nozzle and cowl shape optimizations for turbofan separate-jet engines. The main objective of this work is to implement an optimization process including a detailed Computer-Aided Design (CAD) model and improve nozzles propulsive performance, taking into account the complete geometry of the aft-engine body. Integrating detailed CAD models in optimization workflows remains challenging, that is why an original approach is considered. This method uses expert knowledge to reduce dimensionality and enables to compute sensitivities with finite differences. The results illustrate the interest of this innovative industrial optimization approach for the design of turbofan nozzles.

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Section: Introductionmentioning

confidence: 99%

Aerodynamic shape optimization of aircraft engine nozzles based on Computer-Aided Design

Bagy

Mohammadi²,

Méheut³

et al. 2020

AIAA Scitech 2020 Forum

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show abstract

“…approaches adopted, particularly in the areas of adjoint methods, surface and volume mesh manipulation and quasi-Newton search methods. Much collaborative effort towards this has been in the AIAA Aerodynamic Design Optimization Discussion Group (ADODG * ) through which a set of benchmark cases [1][2][3] have been defined and tackled; here the current state-of-the-art sees much recent work surrounding the Common Research Model wing [4,5] and wing-body-tail [6,7] configurations. The cutting-edge in the field now sees the explicit inclusion of aerodynamic phenomena, such as buffet onset [8] and aeroelastic flutter [9], into the optimisation thereby further refining the design problem being posed.…”

Section: Introductionmentioning

confidence: 99%

Gradient-Limiting Shape Control for Efficient Aerodynamic Optimisation

Kedward

Allen

Rendall

2018

2018 Applied Aerodynamics Conference

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Local shape control methods, such as B-Spline surfaces, are well-conditioned such that they allow high-fidelity design optimisation, however this comes at the cost of degraded optimisation convergence rate as control fidelity is refined due to the resulting exponential increase in the size of the design space. Moreover, optimisations in higher-fidelity design spaces become illposed due to high frequency shape components being insufficiently bounded; this can lead to non-smooth and oscillatory geometries that are invalid both in physicality (shape) and discretisation (mesh). This issue is addressed here by developing a geometrically-meaningful constraint to reduce the effective degrees of freedom and improve the design space thereby improving optimisation convergence rate and final result. A new approach to shape control is presented using coordinate control (x, z) to recover shape-relevant displacements and surface gradient constraints to ensure smooth and valid iterates. The new formulation transforms constraints directly onto design variables, and these bound the out-of-plane variations to ensure smooth shapes as well as the in-plane variations for mesh validity. Shape gradient constraints approximating a C 2 continuity condition are derived and demonstrated on a challenging test case: inviscid transonic drag minimisation of a symmetric NACA0012 aerofoil. Significantly the regularised shape problem is shown to have an optimisation convergence rate independent of both shape control fidelity and numerical mesh resolution, while still making use of increased control fidelity to achieve improved results. Consequently, a value of 1.6 drag counts is achieved on the test case, the lowest value achieved by any method.

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“…Aerodynamic shape optimization has reached a good level of maturity, as well as variety, among the tools and approaches adopted, particularly in the areas of adjoint methods, surface and volume mesh manipulation, and quasi-Newton search methods. Much collaborative effort toward this has been in the AIAA Aerodynamic Design Optimization Discussion Group (ADODG § ), through which a set of benchmark cases [1][2][3] have been defined and tackled; here the current state-of-the-art sees much recent work surrounding the Common Research Model wing [4,5] and wing-body-tail [6,7] configurations. The cutting edge in the field now sees the explicit inclusion of aerodynamic phenomena, such as buffet onset [8] and aeroelastic flutter [9], into the optimization, thereby further refining the design problem being posed.…”

mentioning

confidence: 99%

Gradient-Limiting Shape Control for Efficient Aerodynamic Optimization

2020

View full text Add to dashboard Cite

Local shape control methods, such as B-spline surfaces, are well-conditioned such that they allow high-fidelity design optimization; however, this comes at the cost of degraded optimization convergence rate as control fidelity is refined due to the resulting exponential increase in the size of the design space. Moreover, optimizations in higherfidelity design spaces become ill-posed due to high-frequency shape components being insufficiently bounded; this can lead to nonsmooth and oscillatory geometries that are invalid in both physicality (shape) and discretization (mesh). This issue is addressed here by developing a geometrically meaningful constraint to reduce the effective degrees of freedom and improve the design space, thereby improving optimization convergence rate and final result. A new approach to shape control is presented using coordinate control (x;z) to recover shape-relevant displacements and surface gradient constraints to ensure smooth and valid iterates. The new formulation transforms constraints directly onto design variables, and these bound the out-of-plane variations to ensure smooth shapes as well as the in-plane variations for mesh validity. Shape gradient constraints approximating a C 2 continuity condition are derived and demonstrated on a challenging test case: inviscid transonic drag minimization of a symmetric NACA0012 airfoil. Significantly, the regularized shape problem is shown to have an optimization convergence rate independent of both shape control fidelity and numerical mesh resolution, while still making use of increased control fidelity to achieve improved results. Consequently, a value of 1.6 drag counts is achieved on the test case, the lowest value achieved by any method.

show abstract

Aerodynamic Shape Optimization Progress on ADODG Benchmark Problems Using the elsA Software

Cited by 3 publications

References 11 publications

Aerodynamic shape optimization of aircraft engine nozzles based on Computer-Aided Design

Aerodynamic shape optimization of aircraft engine nozzles based on Computer-Aided Design

Gradient-Limiting Shape Control for Efficient Aerodynamic Optimisation

Gradient-Limiting Shape Control for Efficient Aerodynamic Optimization

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