• Structural Engineering and Mechanics
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• 제8권5호
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• pp.513-529
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• 1999

A concept of hierarchical modeling, the newest modeling technology, has been introduced in early 1990's. This new technology has a great potential to advance the capabilities of current computational mechanics. A first step to implement this concept is to construct hierarchical models, a family of mathematical models sequentially connected by a key parameter of the problem under consideration and have different levels in modeling accuracy, and to investigate characteristics in their numerical simulation aspects. Among representative model problems to explore this concept are elastic structures such as beam-, arch-, plate- and shell-like structures because the mechanical behavior through the thickness can be approximated with sequential accuracy by varying the order of thickness polynomials in the displacement or stress fields. But, in the numerical, analysis of hierarchical models, two kinds of errors prevail, the modeling error and the numerical approximation error. To ensure numerical simulation quality, an accurate estimation of these two errors is definitely essential. Here, a local a posteriori error estimator for elastic structures with thin domain such as plate- and shell-like structures is derived using the element residuals and the flux balancing technique. This method guarantees upper bounds for the global error, and also provides accurate local error indicators for two types of errors, in the energy norm. Compared to the classical error estimators using the flux averaging technique, this shows considerably reliable and accurate effectivity indices. To illustrate the theoretical results and to verify the validity of the proposed error estimator, representative numerical examples are provided.

• 대기
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• 제24권4호
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• pp.555-563
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• 2014

The impacts of dynamic and thermodynamic schemes used in the Community Ice CodE (CICE), the Los Alamos sea ice model, on sea ice concentration, extent and thickness over the Arctic and Antarctic regions are evaluated. Using the six dynamic and thermodynamic schemes such as sea ice strength scheme, conductivity scheme, albedo type, advection scheme, shortwave radiation method, and sea ice thickness distribution approximation, the sensitivity experiments are conducted. It is compared with a control experiment, which is based on the fixed atmospheric and oceanic forcing. For sea ice concentration and extent, it is found that there are remarkable differences between each sensitivity experiment and the control run over the Arctic and Antarctic especially in summer. In contrast, there are little seasonal variations between the experiments for sea ice thickness. In summer, the change of the albedo type has the biggest influence on the Arctic sea ice concentration, and the Antarctic sea ice concentration has a greater sensitivity to not only the albedo type but also advection scheme. The Arctic sea ice thickness is significantly affected by the albedo type and shortwave radiation method, while the Antarctic sea ice thickness is more sensitive to sea ice strength scheme and advection scheme.

• 대한기계학회논문집B
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• 제25권8호
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• pp.1087-1096
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• 2001

The dynamic structures of unsteady CH$_4$/Air jet diffusion flame with a flame-vortex interaction were numerically investigated. A timed-dependent, axisymmetric computational model and a low mach number approximation were employed in the present calculation. A two-step global reaction mechanism which considers 6 species, was used to calculate the reaction rates. The predicted results including the gravitational effect show that the large outer vortices and the small inner vortices can be well simulated without any additional disturbances near nozzle tip. It was found that the temperature and species concentrations have deviated values even for the same mixture fraction in the flame-vortex interaction region. It was also shown that the flame surface is not deformed by the inner vortex in upstream region, while in downstream region, the flame surface is compressed or stretched by the outer vortex roll-up. The present unsteady jet flame configuration accompanying a flame-vortex interaction is expected to give good implications for the unsteady structures of turbulent flames.

• 한국생산제조학회지
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• 제21권6호
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• pp.954-960
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• 2012

Nowadays, rapidly changing and unstable global economic environments request a lot of roles to engineers. In this situation, product should be designed to make more profit by cost down and to satisfy distinguished performance comparing to other competitive ones. In this research, the optimization design of the industrial robot casting will be done. The weight and deflection have to be reduced as objective functions and stress has to be constrained under some constant value. To reduce time cost, CCD (Central Composite Design) will be used to make experimental design. And RSM (Response Surface Methodology) will be taken to make regression model for objective functions and constraint function. Finally, optimization will be done with Genetic Algorithm. In this problem, the objective functions are multiple, so NSGA-II which is brilliant and efficient for such a problem will be used. For the solution quality check, the diversity between Pareto solutions will be also checked.

• International Journal of Aeronautical and Space Sciences
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• 제11권4호
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• Computers and Concrete
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• 제16권5호
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• pp.669-682
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• 2015

Degradation of reinforced concrete (RC) structures due to chloride penetration followed by reinforcement corrosion has been a serious problem in civil engineering for many years. The numerical simulation methods at present are mainly finite element method (FEM) and finite difference method (FDM), which are based on mesh. Mesh generation in engineering takes a long time. In the present article, the numerical solution of chloride transport in concrete is analyzed using radial point interpolation method (RPIM) and element-free Galerkin (EFG). They are all meshless methods. RPIM utilizes radial polynomial basis, whereas EFG uses the moving least-square approximation. A Galerkin weak form on global is used to attain the discrete equation, and four different numerical examples are presented. MQ function and appropriate parameters have been proposed in RPIM. Numerical simulation results are compared with those obtained from the finite element method (FEM) and analytical solutions. Two case of chloride transport in full saturated and unsaturated concrete are analyzed to test the practical applicability and performance of the RPIM and EFG. A good agreement is obtained among RPIM, EFG, and the experimental data. It indicates that RPIM and EFG are reliable meshless methods for prediction of chloride concentration in concrete structures.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.65-68
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• 2001

RBFN has some problem that because the basis function isnt orthogonal to each others the number of used basis function goes to big. In this reason, the Wavelet Neural Network which uses the orthogonal basis function in the hidden node appears. In this paper, we propose the composition method of the actual function in hidden layer with the scaling function which can represent the region by which the several wavelet can be represented. In this method, we can decrease the size of the network with the pure several wavelet function. In addition to, when we determine the parameters of the scaling function we can process rough approximation and then the network becomes more stable. The other wavelets can be determined by the global solutions which is suitable for the suggested problem using the genetic algorithm and also, we use the back-propagation algorithm in the learning of the weights. In this step, we approximate the target function with fine tuning level. The complex neural network suggested in this paper is a new structure and important simultaneously in the point of handling the determination problem in the wavelet initialization.

• 천문학회보
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• 제41권1호
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• pp.47.2-47.2
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• 2016

The protons and helium ions in the solar wind are observed to possess anisotropic temperature profiles. The anisotropy appears to be limited by various marginal instability conditions. One of the efficient methods to investigate the global dynamics and distribution of various temperature anisotropies in the large-scale solar wind models may be that based upon the macroscopic quasi-linear approach. The present paper investigates the proton and helium ion anisotropy instabilities on the basis of comparison between the quasi-linear theory versus particle-in-cell simulation. It is found that the overall dynamical development of the particle temperatures is quite accurately reproduced by the macroscopic quasi-linear scheme. The wave energy development in time, however, shows somewhat less restrictive comparisons, indicating that while the quasi-linear method is acceptable for the particle dynamics, the wave analysis probably requires higher-order physics, such as wave-wave coupling or nonlinear wave-particle interaction. We carried out comparative studies of proton firehose instability, aperiodic ordinary mode instability, and helium ion anisotropy instability. It was found that the agreement between QL theory and PIC simulation is rather good. It means that the quasilinear approximation enjoys only a limited range of validity, especially for the wave dynamics and for the relatively high-beta regime.

• 대한조선학회논문집
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• 제34권1호
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• pp.93-101
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• 1997

본 연구에서는 전통적인 비선형 최적화 기법의 문제점을 극복하기 위하여 유전자알고리즘과 지식베이스의 통합을 통한 새로운 개념의 최적화 기법을 개발하였다. 여기에서는 제한조건이 있는 비선형 최적화 문제를 해결하기 위해 사용되는 전통적인 순차적 선형화 방법과 새로운 유전자 알고리즘의 장단점을 서로 보완한 하이브리드형 최적화 기법을 개발하였다. 여기에 지식베이스를 통한 최적화 지원 기법 및 최적화 모델의 자동생성 모듈을 개발하여 최적화 모텔의 성능을 한층 개선할 수 있었다. 개발된 최적화 기법의 검증을 위하여 수학적 비선형 모델을 이용한 여러가지 기법의 비교 검토를 수행하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.685-686
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• 2007

This paper presents an application of power system fault diagnostic algorithm for the PEFP Proton Accelerator Research Center using neural network. Proposed fault diagnostic system is constructed by the radial basis function (RBF) neural network because it has the capabilities of the pattern classification and function approximation of any nonlinear function. Proposed system identifies faulted section in the power system based on information about the operation of protection devices such as relays and circuit breakers. In this paper, parameters of the RBF neural networks are tuned by the GA-TS algorithm, which has the global optimal solution searching capabilities. To show the validity of the proposed method, proposed algorithm has been tested with a practical power system in Proton Accelerator Research Center of PEFP.