• Water for future
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• v.29 no.4
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• pp.109-118
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• 1996

The neural network is a mathematical model of theorized brain activity which attempts to exploit the parallel local processing and distributed storage properties. The neural metwork is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. A multi-layer neural network is constructed to predict rainfall. The network learns continuourvalued input and output data. Application of neural network to 1-hour real data in Seoul metropolitan area and the Soyang River basin shows slightly good predictions. Therefore, when good data is available, the neural network is expected to predict the complicated rainfall successfully.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.224-233
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• 1999

The quality of injection molded parts is affected by the variables such as materials, design variables of part and mold, molding machine, and processing conditions. It is difficult to consider all the variables at the same time to predict the quality. In this paper neural network was applied to analyze the relationship between processing conditions and volumetric shrinkage of part. Engineering plastic gear was used for the study, and the learning data was extracted by the simulation software like Moldflow. Results of neural network was good agreement with simulation results. Nonlinear regression model was formulated using the test data of 3,125 obtained from neural network, Optimal processing conditions were calculated to minimize the volumetric shrinkage of molded part by the application of RQP(Recursive Quadratic Programming) algorithm.

• Structural Engineering and Mechanics
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• v.10 no.2
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• pp.165-180
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• 2000

An analytical model with tension softening for the prediction of the capacity of prestressed concrete beams under pure torsion and under torsion combined with shear and flexure is introduced. The proposed approach employs bilinear stress-strain relationship with post cracking tension softening branch for the concrete in tension and special failure criteria for biaxial stress states. Further, for the solution of the governing equations a special numerical scheme is adopted which can be applied to elements with practically any cross-section since it utilizes a numerical mapping. The proposed method is mainly applied to plain prestressed concrete elements, but is also applicable to prestressed concrete beams with light transverse reinforcement. The aim of the present work is twofold; first, the validation of the approach by comparison between experimental results and analytical predictions and second, a parametrical study of the influence of concentric and eccentric prestressing on the torsional capacity of concrete elements and the interaction between torsion and shear for various levels of prestressing. The results of this investigation presented in the form of interaction curves, are compared to experimental results and code provisions.

• Structural Engineering and Mechanics
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• v.22 no.1
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• pp.17-32
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• 2006

The application of cellular materials in load-carrying and security-relevant structures requires the exact prediction of their mechanical behavior, which necessitates the development of robust simulation models and techniques based on appropriate experimental procedures. The determination of the yield surface requires experiments under multi-axial stress states because the yield behavior is sensitive to the hydrostatic stress and simple uniaxial tests aim only to determine one single point of the yield surface. Therefore, an experimental technique based on a uniaxial strain test for the description of the influence of the hydrostatic stress on the yield condition in the elastic-plastic transition zone at small strains is proposed and numerically investigated. Furthermore, this experimental technique enables the determination of a second elastic constant, e.g., Poisson's ratio.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.5 s.143
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• pp.466-471
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• 2005

The out-of-plane deformation in thin plate structure has been a serious qualify problem. It has been known that the out-of-plane deformation is caused by the angular deformation of welded joint. However, experimental results show that the conventional theory based on angular deformation is not appropriate for prediction of the out-of-plane deformation in thin plate structure. In this study, large deformation plate theory is introduced to clarify the effect of residual stress on the out-of-plane deformation. A simple equation is proposed to predict the out-of-plane deformation. The results by the proposed method show good agreement with the experimental results.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.3
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• pp.610-625
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• 2015

In this paper the wave run-up around a circular column in regular waves is numerically calculated to investigate the applicability of the Modified Marker-Density (MMD) method to prediction of wave run-up around an offshore platform. The MMD method is one of the methods to define the highly nonlinear free surface. The governing equations are the Navier-Stokes equations and the continuity equation which are computed in Cartesian grid system. To validate incident waves generated by numerical simulation, those are compared with the solutions of the Stokes $5^{th}$ order wave theory. The wave run-up simulations are performed varying the steepness and period of incident waves as referred experimental data. The numerical results are compared to the experimental data and the results show good agreements.

• Journal of Magnetics
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• v.18 no.1
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• pp.57-64
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• 2013

Flux linkage of phase windings is a key parameter in determining the behavior of a switched reluctance motor (SRM) [1-8]. Therefore, the accurate prediction of flux linkage at aligned and unaligned rotor positions makes a significant contribution to the design of an SRM and its analytical approach is not straightforward due to nonlinear saturation in flux. Although several different approaches using a finite element analysis (FEA) or a curve-fitting tool have been employed to compute phase flux linkage [2-5], they are not suitable for a simple design procedure because the FEA necessitates a large amount of time in both modeling and solving with complexity for every motor design, and the curve-fitting requires the data of flux linkage from either an experimental test or an FEA simulation. In this paper, phase flux linkage at aligned and unaligned rotor positions is estimated by means of a reluctance network, and the proposed approach is analytically verified in terms of accuracy compared to FEA.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.110-115
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• 2022

Accurate current-voltage modeling of solar cell systems plays an important role in power prediction. Solar cells have nonlinear characteristics that are sensitive to environmental conditions such as temperature and irradiance. In this paper, the output characteristics of photovoltaic module are accurately predicted by combining the artificial neural network and physical model. In order to estimate the performance of PV module under varying environments, the artificial neural network model is trained with randomly generated temperature and irradiance data. With the use of proposed model, the current-voltage and power-voltage characteristics under real environments can be predicted with high accuracy.

• Coupled systems mechanics
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• v.11 no.2
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• pp.133-149
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• 2022

The accurate prediction of elastoplasticity under prescribed workloads is essential in the optimization of engineering structures. Mechanical experiments are carried out with the goal of obtaining reliable sets of material parameters for a chosen constitutive law via inverse identification. In this work, two sample geometries made of high strength steel plates were evaluated to determine the optimal configuration for the identification of Ludwik's nonlinear isotropic hardening law. Finite element model updating(FEMU) was used to calibrate the material parameters. FEMU computes the parameter changes based on the Hessian matrix, and the sensitivity fields that report changes of computed fields with respect to material parameter changes. A sensitivity analysis was performed to determine the influence of the sample geometry on parameter identifiability. It was concluded that the sample with thinned gauge region with a large curvature radius provided more reliable material parameters.

• Nonlinear Functional Analysis and Applications
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• v.28 no.1
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• pp.175-203
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• 2023

In this paper, we study an iterative algorithm that is based on inertial proximal and contraction methods embellished with relaxation technique, for finding common solution of monotone variational inclusion, and fixed point problems of pseudocontractive mapping in real Hilbert spaces. We establish a strong convergence result of the proposed iterative method based on prediction stepsize conditions, and under some standard assumptions on the algorithm parameters. Finally, some special cases of general problem are given as applications. Our results improve and generalized some well-known and related results in literature.