Gradient-free aerodynamic shape optimization using Large Eddy Simulation

Karbasian, Hamid R.; Vermeire, Brian C.

doi:10.1016/j.compfluid.2021.105185

Cited by 14 publications

(6 citation statements)

References 32 publications

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“…MADS has previously been used for optimization using LES of the SD7003 airfoil at low Reynolds numbers by Karbasian and Vermeire [53]. MADS has also been used successfully with RANS simulations to design hydraulic turbine runner blades by Bahrami [54] and Bahrami et al [55].…”

Section: Gradient-free Methodsmentioning

confidence: 99%

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High-fidelity gradient-free optimization of low-pressure turbine cascades

Aubry¹,

Karbasian²,

Vermeire³

2022

Computers & Fluids

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Section: Gradient-free Methodsmentioning

confidence: 99%

“…where I, w and n s are the identity matrix, a normalized random vector and the number of design parameters respectively [53]. To create a poll set, H k is normalized to the range of the design values by…”

Section: Madsmentioning

confidence: 99%

High-fidelity gradient-free optimization of low-pressure turbine cascades

Aubry¹,

Karbasian²,

Vermeire³

2022

Computers & Fluids

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“…The selection or definition of design variables directly affects the optimization of the optimization problem, or it produces different optimization problems [1]. According to whether the gradient method is used, the optimization problem is divided into gradient and non-gradient optimization methods [2][3][4][5]. The definition of design variables in these two methods is the same.…”

Section: Introductionmentioning

confidence: 99%

Influence of parameterization method and optimization algorithm on airfoil optimization

Zhou,

Jia,

et al. 2023

J. Phys.: Conf. Ser.

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In this study, the impact of parameterization methods and optimization algorithms on the optimization results of the RAE2822 airfoil is examined. Specifically, how variations in the number of design variables, spacing of control points, the scaling scale of the objective function, and line search step of different FFD parameterization methods affect the resistance convergence process are investigated. The results indicate that the number of design variables and the spacing of control points play a significant role in the speed and minimum value of resistance convergence. In contrast, the scaling scale of the objective function and the line search step has a relatively minor impact on resistance optimization.

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“…Recently, there have been few studies regarding small/largescale optimization problems using different approaches such as gradient-free and gradient-based methods [13,14]. For instance, the Mesh Adaptive Direct Searches (MADS) algorithm can be implemented for derivative-free optimization, which uses a number of variable-size meshes to search the space until convergence is achieved.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic optimization of eVTOL rotor profiles

Yeganehdoust,

Karbasian,

Vermeire

2023

Progress in Canadian Mechanical Engineering. Volume 6

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Electric Vertical Take-Off and Landing (eVTOL) aircraft are currently being developed to fill a gap in the air transportation sector and, simultaneously, provide zero-emissions alternatives to current generation carbon-intensive short-haul aircraft. However, unlike conventional fixed-wing or rotary aircraft, eVTOL rotors operate in both hover and forward flight configurations. This significantly increases the range of operating conditions experienced by the rotor, introducing multiple aerodynamic design challenges. Additionally, the efficiency of these rotors is particularly important, since it has a direct impact on power draw and aircraft range. In this presentation, a classical airfoil, the ClarkY, is used as a baseline configuration for an eVTOL rotor section. A gradient-based optimization framework using an adjoint solver in Discrete Adjoint with OpenFOAM (DAFoam) with the Reynolds Averaged Navier-Stokes (RANS) approach is then used. In this study, a control point-based free form deformation (FFD) method is used in the framework in order to change the aerodynamic shape. The objective function for this optimization is the lift-to-drag ratio, with additional target lift and geometric constraints. The baseline design is first validated against experimental data, and then the optimization is completed for several target lift coefficient values. Results demonstrate that the lift-to-drag ratio can be increased significantly while maintaining the desired target lift coefficient. Preliminary results for complete rotor optimization using RANS will then be presented, followed by preliminary airfoil optimization using Large Eddy Simulation (LES).

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Gradient-free aerodynamic shape optimization using Large Eddy Simulation

Cited by 14 publications

References 32 publications

High-fidelity gradient-free optimization of low-pressure turbine cascades

High-fidelity gradient-free optimization of low-pressure turbine cascades

Influence of parameterization method and optimization algorithm on airfoil optimization

Aerodynamic optimization of eVTOL rotor profiles

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