• Journal of computational fluids engineering
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• v.17 no.4
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• pp.32-40
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• 2012

Efficient Global Optimization (EGO) method is a global optimization technique which can select the next sample point automatically by infill sampling criteria (ISC) and search for the global minimum with less samples than what the conventional global optimization method needs. ISC function consists of the predictor and mean square error (MSE) provided from the kriging model which is a stochastic metamodel. Also the constrained EGO method can minimize the objective function dealing with the constraints under EGO concept. In this study the constrained EGO method applied to the RAE2822 airfoil shape design formulated with the constraint. But the noisy CFD data caused the kriging model to fail to depict the true function. The distorted kriging model would make the EGO deviate from the correct search. This distortion of kriging model can be handled with the interpolation(p=free) kriging model. With the interpolation(p=free) kriging model, however, the search of EGO solution was stalled in the narrow feasible region without the chance to update the objective and constraint functions. Then the accuracy of EGO solution was not good enough. So the three-step search method was proposed to obtain the accurate global minimum as well as prevent from the distortion of kriging model for the noisy constrained CFD problem.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.268-270
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• 2006

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.6
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• pp.557-563
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• 2010

This paper addresses the issue of adaptive global optimization using Kriging metamodel known as EGO(Efficient Global Optimization). The algorithm adaptively chooses where to generate subsequent samples based on an explicit trade-off between reduction of global uncertainty and exploration of the region of the interest. A strategy that saves the computational cost by using expectations derived from probabilistic nature of approximate model is proposed. At every iteration, a candidate test point that seems to be feasible/inactive or has little possibility to improve for minimum is identified and excluded from updating approximate models. By doing that the computational cost is saved without loss of accuracy.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.6
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• pp.995-1006
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• 2015

Underwater glider, as a new kind of autonomous underwater vehicles, has many merits such as long-range, extended-duration and low costs. The shape of underwater glider is an important factor in determining the hydrodynamic efficiency. In this paper, a high lift to drag ratio configuration, the Blended-Wing-Body (BWB), is used to design a small civilian under water glider. In the parametric geometric model of the BWB underwater glider, the planform is defined with Bezier curve and linear line, and the section is defined with symmetrical airfoil NACA 0012. Computational investigations are carried out to study the hydrodynamic performance of the glider using the commercial Computational Fluid Dynamics (CFD) code Fluent. The Kriging-based genetic algorithm, called Efficient Global Optimization (EGO), is applied to hydrodynamic design optimization. The result demonstrates that the BWB underwater glider has excellent hydrodynamic performance, and the lift to drag ratio of initial design is increased by 7% in the EGO process.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.6
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• pp.693-704
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• 2017

Blended-Wing-Body Underwater Glider (BWBUG), which has excellent hydrodynamic performance, is a new kind of underwater glider in recent years. In the shape optimization of BWBUG, the lift to drag ratio is often used as the optimization target. However this results in lose of internal space. In this paper, the energy reserve is defined as the direct proportional function of the internal space of BWBUG. A motion model, which relates gliding range to steady gliding motion parameters as well as energy consumption, is established by analyzing the steady-state gliding motion. The maximum gliding range is used as the optimization target instead of the lift to drag ratio to optimizing the shape of BWBUG. The result of optimization shows that the maximum gliding range of initial design is increased by 32.1% though an Efficient Global Optimization (EGO) process.