• Wind and Structures
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• v.39 no.3
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• pp.175-190
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• 2024

Aerodynamic shape optimization is very useful for enhancing the performance of wind-sensitive structures. However, shape parameterization, as the first step in the pipeline of aerodynamic shape optimization, still heavily depends on empirical judgment. If not done properly, the resulting small design space may fail to cover many promising shapes, and hence hinder realizing the full potential of aerodynamic shape optimization. To this end, developing a novel shape parameterization scheme that can reflect real-world complexities while being simple enough for the subsequent optimization process is important. This study proposes a machine learning-based scheme that can automatically learn a low-dimensional latent representation of complex aerodynamic shapes for bluff-body wind-sensitive structures. The resulting latent representation (as design variables for aerodynamic shape optimization) is composed of both discrete and continuous variables, which are embedded in a hierarchy structure. In addition to being intuitive and interpretable, the mixed discrete and continuous variables with the hierarchy structure allow stakeholders to narrow the search space selectively based on their interests. As a proof-of-concept study, shape parameterization examples of tall building cross sections are used to demonstrate the promising features of the proposed scheme and guide future investigations on data-driven parameterization for aerodynamic shape optimization of wind-sensitive structures.

• Journal of computational fluids engineering
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• v.6 no.3
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• pp.10-18
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• 2001

Genetic Algorithm(GA) is applied to aerodynamic shape optimization and demonstrated its merits in global searching ability and the independency of differentiability. However, applications of GA are limited due to slow convergence rate, premature termination, and high computing costs. The present aerodynamic designs such as wing shape optimizations using GA have seldom been applied because of high computing costs. This paper has two objects; improvement of the efficiency of GA and application of GA into aerodynamic shape optimization for 2D and 3D wings. The study indicates that GA can be applied to aerodynamic design and its performance is comparable to traditional design methods.

• International Journal of Aeronautical and Space Sciences
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• v.4 no.1
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• pp.45-52
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• 2003

A three-dimensional aerodynamic shape optimization technique in inviscid compressible flows is developed by using a parallel continuous adjoint formulation on unstructured meshes. A new surface mesh modification method is proposed to overcome difficulties related to patch-level remeshing for unstructured meshes, and the effect of design sections on aerodynamic shape optimization is examined. Applications are made to three-dimensional wave drag minimization problems including an ONERA M6 wing and the EGLIN wing-pylon-store configuration. The results show that the present method is robust and highly efficient for the shape optimization of aerodynamic configurations, independent of the number of design variables used.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.130-133
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• 2008

In this paper the trust region method is studied and applied in aerodynamic shape optimization. The trust region method is a gradient-based optimization method, but it is not as popular as other methods in engineering computations. Its theory will be explained for unconstrained optimization problems and a trust region subproblem will be solved with the dogleg method. After verifying the trust region method with analytical test problems, it is applied to aerodynamic shape design optimization and the performance of airfoil is improved successfully.

• Wind and Structures
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• v.39 no.2
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• pp.101-110
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• 2024

Tall buildings are distinguished by their slenderness, making them sensitive to wind loads. A huge amount of resources is typically dedicated to controlling loads and vibrations caused by wind. Enhancing tall buildings' aerodynamic performance can save a large portion of these expenses. This enhancement can be achieved through aerodynamic optimization that can be tackled either by altering the outer shape of the building locally through modifying the corners (e.g., corner chamfering) or globally through changing the whole form of the building (e.g., twisting). In this paper, a newly developed aerodynamic optimization procedure (AOP) is adopted to enhance tall buildings' aerodynamic performance. This procedure is a combination of computational fluid dynamics (CFD), Artificial Neural Networks (ANN) and Genetic algorithm (GA). An ANN-based surrogate model is used to evaluate the aerodynamic parameters through the optimization procedure to reach a reliable aerodynamic shape. Helical twisting and corner modifications of the buildings are used to reduce the along-wind base moment.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.66-78
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• 2007

A multi-point aerodynamic shape optimization technique has been developed for helicopter rotor blades in hover based on a continuous adjoint method on unstructured meshes. The Euler flow solver and the continuous adjoint sensitivity analysis were formulated on the rotating frame of reference. The 'objective function and the sensitivity were obtained as a weighted sum of the values at each design point. The blade section contour was modified by using the Hicks-Henne shape functions. The mesh movement due to the blade geometry change was achieved by using a spring analogy. In order to handle the repeated evaluation of the design cycle efficiently, the flow and adjoint solvers were parallelized based on a domain decomposition strategy. A solution-adaptive mesh refinement technique was adopted for the accurate capturing of the wake. Applications were made to the aerodynamic shape optimization of the Caradonna-Tung rotor blades and the UH-60 rotor blades in hover.

• 한국전산유체공학회:학술대회논문집
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• 2005.04a
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• pp.191-196
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• 2005

For the improvement of aerodynamic performance of the turbine blade in a turbopump for the liquid rocket engine, the optimization of turbine profile shape has been studied. The turbine in a turbopump in this study is a partial admission of impulse type, which has twelve nozzles and supersonic inflow. Due to the separated nozzles and supersonic expansion, the flow field becomes complicates and shows oblique shocks and flow separation. To increase the blade power, redesign of the blade shape using CFD and optimization method was attempted. The turbine cascade shape was represented by four design parameters. For optimization, genetic algorithm based upon non-gradient search has been selected as a optimizer. As a result, the final blade has about 4 percent more blade power than the initial shape.

• Journal of computational fluids engineering
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• v.10 no.2
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• pp.54-59
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• 2005

For the improvement of aerodynamic performance of the turbine blade in a turbopump for the liquid rocket engine, the optimization of turbine profile shape has been studied. The turbine in a turbopump in this study is a partial admission of impulse type, which has twelve nozzles and supersonic inflow. Due to the separated nozzles and supersonic expansion, the flow field becomes complicate and shows oblique shocks and flow separation. To increase the blade power, redesign ol the blade shape using CFD and optimization methods was attempted. The turbine cascade shape was represented by four design parameters. For optimization, a genetic algorithm based upon non-gradient search hue been selected as an optimizer. As a result, the final blade has about 4 percent more blade power than the initial shape.

• Proceedings of the KSME Conference
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• 2001.06e
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• pp.373-379
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• 2001

When a train runs into a tunnel at high-speed, aerodynamic drag suddenly increases and the booming noise is generated at the exit of tunnel. The noise shape is very important to reduce the aerodynamic drag in tunnel as well as on open ground, and the micro-pressure wave that is a source of booming noise is dependent on nose shape, especially on area distribution. In this study, the nose shape has been optimized employing the response surface methodology and the axi-symmetric compressible Navier-Stokes equations. The optimal designs have been executed imposing various conditions of the aerodynamic drag and the micro-pressure wave on object functions. The results show that the multi-objective design was successful to decrease micro-pressure wave and aerodynamic drag of trains.

• Journal of computational fluids engineering
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• v.17 no.4
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• pp.56-68
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• 2012

Nowadays, Unmanned Combat Air Vehicle(UCAV) has become an important aircraft system for the national defense. For its efficiency and survivability, shape optimization of UCAV is an essential part of its design process. In this paper, shape optimization of UCAV was processed for aerodynamic performance improvement and Radar Cross Section(RCS) reduction using Multi Objective Genetic Algorithm(MOGA). Lift and induced drag, friction drag, RCS were calculated using panel method, boundary layer theory, Physical Optics(PO) approximation respectively. In particular, calculation applied Radar Absorbing Material(RAM) was performed for the additional RCS reduction. Results are indicated that shape optimization is performed well for improving aerodynamic performance, reducing RCS. Further study will be performed with higher fidelity tools and consider other design segments including structure.