Application of Jetstream to a Suite of Aerodynamic Shape Optimization Problems

Telidetzki, Karla; Osusky, Lana; Zingg, David W.

doi:10.2514/6.2014-0571

Cited by 30 publications

(19 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Thus, we need a set of benchmark cases for aerodynamic design optimization, following a model similar to that of the Drag Prediction Workshop [19][20][21]. Four papers, including this one, were presented on this test case at the 2014 AIAA Science and Technology Forum and Exposition in a special session organized by the ADODG [22][23][24][25]. These problems range from the optimization of a two-dimensional airfoil using the Euler equations to threedimensional shape optimization using the RANS equations.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic Shape Optimization Investigations of the Common Research Model Wing Benchmark

2015

View full text Add to dashboard Cite

Despite considerable research on aerodynamic shape optimization, there is no standard benchmark problem allowing researchers to compare results. This work addresses this issue by solving a series of aerodynamic shape optimization problems based on the Common Research Model wing benchmark case defined by the Aerodynamic Design Optimization Discussion Group. The aerodynamic model solves the Reynolds-averaged Navier-Stokes equations with a Spalart-Allmaras turbulence model. A gradient-based optimization algorithm is used in conjunction with an adjoint method that computes the required derivatives. The drag coefficient is minimized subject to lift, pitching moment, and geometric constraints. A multilevel technique is used to reduce the computational cost of the optimization. A single-point optimization is solved with 720 shape variables using a 28.8-million-cell mesh, reducing the drag by 8.5%. A more realistic design is achieved through a multipoint optimization. Multiple local minima are found when starting from multiple randomly generated geometries, but the minimum drag values are within 0.1 drag counts of each other, and the geometries differ by only 0.4% of the mean aerodynamic chord. The effect of varying the number of shape design variables is examined. The Common Research Model wing benchmark problem proved to be useful for evaluating our design optimization framework, and the geometries and meshes for both the baseline and optimized wings are available as supplemental materials in this paper.

show abstract

Section: Introductionmentioning

confidence: 99%

Aerodynamic Shape Optimization Investigations of the Common Research Model Wing Benchmark

2015

View full text Add to dashboard Cite

show abstract

“…The CRM configuration is a useful benchmark for drag prediction, having served as the geometry of interest for both the 4 th and 5 th Drag Prediction Workshops b [3]. More recently, a modified the CRM wing has been used as a benchmark case for the for for the Aerodynamic Design Optimization Discussion Group (ADODG) [6,7,8,9].…”

Section: Jig Shape and Wingbox Designmentioning

confidence: 99%

Aerostructural optimization of the Common Research Model configuration

Kenway

Kennedy

Martins

2014

15th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference

View full text Add to dashboard Cite

The NASA Common Research Model (CRM) has become a standard test case for verification and validation of Reynolds averaged Navier-Stokes computational fluid dynamics codes. In this paper we evaluate the suitability of the CRM for aerostructural and aeroelastic optimization studies. Since the CRM was originally intended for aerodynamic studies only, the undeformed geometry is not available. To address this issue, we designed a jig shape and the corresponding wingbox structure for the CRM using an inverse design procedure. The results are verified by computing the drag coefficient of the aerostructural solution with the jig shape at the nominal CRM operating conditions. The drag differs by less than one drag count relative to the CRM original shape. Using the CRM jig geometry, a sample high-fidelity aerostructural optimization is performed to determine the potential decrease in fuel burn for a long-range design mission when varying wing planform and airfoil shapes. The optimization increases the aspect ratio of the wing from 9.0 to 12.6 and reduces the fuel burn by 8.8%. We also perform a series of gust load analysis on both the initial and optimized designs and determine that the optimized structure is critical under gust loads. The aerostructural optimization produces a high aspect ratio wing with effective passive aeroelastic tailoring, but additional load cases with cruise-like lift distributions are required to produce a more realistic wing design.

show abstract

“…This case has previously been investigated with a variety of different parameterisation methods: Bèzier Curves [1,2]; B-Splines [3,4,5,6,7]; NURBS [8]; Class/Shape Transformations (CSTs) [9]; Hicks-Henne bump functions [10]; Bèzier Surface FFD [11]; PARSEC [12]; Radial basis function domain element (RBF-DE) deformation [13,14] and Singular Value Decompositions (SVD) [14,15]. Due to the large range of factors influencing the results it is difficult to isolate contribution of the parameterisation method from these previous studies.…”

Section: Introductionmentioning

confidence: 99%

Impact of Shape Parameterisation on Aerodynamic Optimisation of Benchmark Problem

Masters

Poole

Taylor

et al. 2016

54th AIAA Aerospace Sciences Meeting

View full text Add to dashboard Cite

General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Department of Aerospace Engineering, University of BristolThis paper presents an investigation into the influence of shape parameterisation and dimensionality on the optimisation of a benchmark case described by the AIAA Aerodynamic Design Optimisation Discussion Group. This problem specifies the drag minimisation of a NACA0012 under inviscid flow conditions at M = 0.85 and α = 0 subject to the constraint that local thickness must only increase. The work presented here applies six different shape parameterisation schemes to this optimisation problem with between 4 and 40 design variables. The parameterisation methods used are: Bèzier Surface FFD; B-Splines; CSTs; Hicks-Henne bump functions; a Radial Basis Function domain element method (RBF-DE) and a Singular Value Decomposition (SVD) method. The optimisation framework used consists of a gradient based SQP optimiser coupled with the SU 2 adjoint Euler solver which enables the efficient calculation of the design variable gradients. Results for the all the parameterisation methods are presented with the best results for each method ranging between 25 and 56 drag counts from an initial value of 469. The optimal result was achieved with the B-Spline method with 16 design variables. A further validation of the results is then presented and the presence of hysteresis is explored.

show abstract

Application of Jetstream to a Suite of Aerodynamic Shape Optimization Problems

Cited by 30 publications

References 11 publications

Aerodynamic Shape Optimization Investigations of the Common Research Model Wing Benchmark

Aerodynamic Shape Optimization Investigations of the Common Research Model Wing Benchmark

Aerostructural optimization of the Common Research Model configuration

Impact of Shape Parameterisation on Aerodynamic Optimisation of Benchmark Problem

Contact Info

Product

Resources

About