• Structural Engineering and Mechanics
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• v.74 no.2
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• pp.157-173
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• 2020

In the finite element modelling of long-span cable-stayed bridges, there are a lot of uncertainties brought about by the complex structural configuration, material behaviour, boundary conditions, structural connections, etc. In order to reduce the discrepancies between the theoretical finite element model and the actual static and dynamic behaviour, updating is indispensable after establishment of the finite element model to provide a reliable baseline version for further analysis. Traditional sensitivity-based updating methods cannot support updating based on static and dynamic measurement data at the same time. The finite element model is required in every optimization iteration which limits the efficiency greatly. A convenient but accurate Kriging surrogate model for updating of the finite element model of cable-stayed bridge is proposed. First, a simple cable-stayed bridge is used to verify the method and the updating results of Kriging model are compared with those using the response surface model. Results show that Kriging model has higher accuracy than the response surface model. Then the method is utilized to update the model of a long-span cable-stayed bridge in Hong Kong. The natural frequencies are extracted using various methods from the ambient data collected by the Wind and Structural Health Monitoring System installed on the bridge. The maximum deflection records at two specific locations in the load test form the updating objective function. Finally, the fatigue lives of the structure at two cross sections are calculated with the finite element models before and after updating considering the mean stress effect. Results are compared with those calculated from the strain gauge data for verification.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.6
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• pp.587-593
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• 2016

Reliability-based design optimization (RBDO) requires a high computational cost owing to its reliability analysis. A surrogate model is introduced to reduce the computational cost in RBDO. The accuracy of the reliability depends on the accuracy of the surrogate model of constraint boundaries in the surrogated-model-based RBDO. In earlier researches, constraint boundary sampling (CBS) was proposed to approximate accurately the boundaries of constraints by locating sample points on the boundaries of constraints. However, because CBS uses sample points on all constraint boundaries, it creates superfluous sample points. In this paper, efficient constraint boundary sampling (ECBS) is proposed to enhance the efficiency of CBS. ECBS uses the statistical information of a kriging surrogate model to locate sample points on or near the RBDO solution. The efficiency of ECBS is verified by mathematical examples.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.6
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• pp.653-663
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• 2000

A lot of hazardous wastes are discharged as by-products of working process by industrial development. Hazardous wastes is physical characteristics of difficult destruction at hight temperature. Numerical simulation and combustion experiment performed of dump incinerator for hazardous waste incineration. For the numerical simulation, the SIMPLEST algorithm was used to ensure rapid converge A K-$\varepsilon$ model was incorporate for the enclosure of turbulence flow. Combustion model was used by ESCRS (extended simple chemically reacting system) model available of CHEMKIN thermodynamic data for the source term of species conservation equation or energy equation. Radiation model is used by six flux model. A parametric screening studies was carried out through numerical simulation and experiment. Residence time and concentration in the incinerator was strongly dependent on the parameters of mixture velocity, mixture equilibrium ratio, surrogate velocity and surrogate equilibrium ratio.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1544-1550
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• 2014

In this paper, an adaptive optimization strategy utilizing Kriging model and genetic algorithm is proposed for the optimal design of electromagnetic devices. The ordinary Kriging assisted by the spherical covariance model is used to construct surrogate models. In order to improve the computational efficiency, the adaptive uniform sampling strategy is applied to generate sampling points in design space. Through several iterations and gradual refinement process, the global optimal point can be found by genetic algorithm. The proposed algorithm is validated by application to the optimal design of a switched reluctance motor, where the stator pole face and shape of pole shoe attached to the lateral face of the rotor pole are optimized to reduce the torque ripple.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.6
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• pp.653-663
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• 2012

The study considers the high maneuverability flight and path optimization is conducted to investigate the appropriate generation of the lift and thrust considering the angle of the stroke plane. The path optimization problem is defined according to the various purposes of the high maneuverability flight. The flying purposes are to maximize thrust force, lift force and both lift and thrust forces. The flapping motion of the airfoil is made by a combined sinusoidal plunging and pitching motion in each problem. The optimization process is carried out by using well-defined surrogate models. The surrogate model is determined by the results of two-dimensional computational fluid dynamics analysis. The Kriging method is used to make the surrogate model and a genetic algorithm is utilized to optimize the surrogate model. The optimization results show the flapping motions for the high maneuverable flight. The effects on the generation of lift and thrust forces are confirmed by analyzing the vortex.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.4
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• pp.369-374
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• 2015

In order to efficiently optimize the problem involving complex computer codes or computationally expensive simulation, surrogate models are widely used. Because their accuracy significantly depends on sample points, many experimental designs have been proposed. One approach is the sequential design of experiments that consider existing information of responses. In earlier research, the correlation coefficients of the kriging surrogate model are introduced as weight parameters to define the scaled distance between sample points. However, if existing information is incorrect or lacking, new sample points can be misleading. Thus, our goal in this paper is to propose a weight function derived from correlation coefficients to generate new points robustly. To verify the performance of the proposed method, several existing sequential design methods are compared for use as mathematical examples.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.817-823
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• 2017

In the past, research has been conducted on the development of an adaptive cruise control algorithm considering fuel efficiency, and an adaptive cruise control system considering fuel efficiency have been developed. However, research on optimizing vehicle and adaptive cruise control parameters in order to maximize performances is insufficient. In this study, the design optimization of vehicle and control parameters considering fuel efficiency, trackability, ride comfort and safe distance is performed. This paper proposes performance measures of vehicle behavior and develops an adaptive cruise control system. In addition, based on the screening of vehicle parameters that significantly influence performances, kriging surrogate models are constructed through a sequential design of experiment, and kriging surrogate model-based design optimization is performed to maximize fuel efficiency and satisfy target performances.

• Korean Journal of Poultry Science
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• v.41 no.2
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• pp.87-92
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• 2014

The avian embryos have been used as a good model to study embryonic development. Due to its unique development in the eggshell, avian embryos can be cultured and hatch in the surrogate eggshell system. In this study, we examined the viability, normal development and hatchability of Korean Oge (KO) chicken embryos in White Leghorn (WL) surrogate eggshells. Donor KO embryos at 3-day and 4-day-old were transferred into recipient WL eggshells, incubated for further 18 days at $37.5^{\circ}C$ with 70% of humidity until hatching. The viability of 3-day-old KO embryos at 7, 14 and 21 day in surrogate eggshell were 70.0%, 43.8% and 23.1%, respectively. In contrast, the viability of 4-day-old KO embryos at 7, 14 and 21 day in surrogate eggshells were 87.1%, 55.6% and 36.0%, respectively. The hatchability of KO embryos transferred into surrogate eggshells at 3-day-old was 23.1%, whereas embryos transferred at 4-day-old was 36.0%. Furthermore, the development of all viable embryos from 3-day group and 4-day group were normal. Our results suggested that culture of KO embryos in WL surrogate eggshells is highly possible, and transfer of donor embryos at 4-day-old may yield higher percentage of hatchability. This study may provide potential knowledge for the conservation of wild and endangered birds through surrogate system.

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.367-370
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• 2006

Performances of multiple surrogate models are evaluated in a turbomachinery blade shape optimization. The basic models, i.e., Response Surface Approximation, Kriging and Radial Basis Neural Network models as well as weighted average models are tested for shape optimization. Global data based errors for each surrogates are used to calculate the weights. These weights are multiplied with the respective surrogates to get the final weighted average models. The design points are selected using three level fractional factorial D-optimal designs. The present approach can help address the multi-objective design on a rational basis with quantifiable cost-benefit analysis.

• Journal of Magnetics
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• v.18 no.1
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• pp.74-79
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• 2013

This paper proposes a sampling-based optimization method for electromagnetic design problems, where design sensitivities are obtained from the elaborate surrogate models based on the universal Kriging method and a local window concept. After inserting additional sequential samples to satisfy the certain convergence criterion, the elaborate surrogate model for each true performance function is generated within a relatively small area, called a hyper-cubic local window, with the center of a nominal design. From Jacobian matrices of the local models, the accurate design sensitivity values at the design point of interest are extracted, and so they make it possible to use deterministic search algorithms for fast search of an optimum in design space. The proposed method is applied to a mathematical problem and a loudspeaker design with constraint functions and is compared with the sensitivity-based optimization adopting the finite difference method.