• Geomechanics and Engineering
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• v.27 no.6
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• pp.561-571
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• 2021

Cofferdams made of teel sheet piles are commonly utilized as support structures for excavation of sea-crossing bridge foundations. As cofferdams are often subject to tide variation, it is imperative to consider potential effects of tide on stability and serviceability of sheet piles, particularly, ultralong steel sheet piles (USSPs). In this study, a real USSP cofferdam constructed using new construction technology in Nanxi River was reported. The design of key parts of USSP cofferdam in the presence of tidal action was first introduced followed by the description of entire construction technology and associated monitoring results. Subsequently, a three-dimensional finite-element model corresponding to all construction steps was established to back-analyze measured deflection of USSPs. Finally, a series of parametric studies was carried out to investigate effects of tide level, soil parameters, support stiffness and construction sequence on lateral deflection of USSPs. Monitoring results indicate that the maximum deflection during construction occurred near the riverbed. In addition, measured stress of USSPs showed that stability of USSP cofferdam strengthened as construction stages proceeded. Moreover, the numerical back-analysis demonstrated that the USSP cofferdam fulfilled the safety requirements for construction under tidal action. The maximum deflection of USSPs subject to high tide was only 13.57 mm at a depth of -4 m. Sensitivity analyses results showed that the design of USSP cofferdam system must be further improved for construction in cohesionless soils. Furthermore, the 5th strut level before concreting played an indispensable role in controlling lateral deflection of USSPs. It was also observed that pumping out water before concreting base slab could greatly simplify and benefit construction program. On the other hand, the simplification in construction procedures could induce seepage inside the cofferdam, which additionally increased the deflection of USSPs by 10 mm on average.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.2
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• pp.154-161
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• 2005

In the machine tool industry, direct drive linear motor technology is an interesting means to achieve high acceleration, and to increase reliability. This paper analyzes and compares the characteristics of a tubular linear motor with Halbach and radial magnet array, respectively. First, the governing equations are established analytically in terms of the magnetic vector potential and two dimensional cylindrical coordinate systems. Then, we derive magnetic field solutions due to the PMs and the currents. Motor thrust, flux linkage and back emf are also derived. The results are shown to be in good conformity with those obtained from the commonly used finite element method. Finally, control parameters are obtained from analytical solutions.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.361-367
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• 2003

We propose an algorithm to detect the face region using a variable ellipsoidal mask and a neural network. Since outlines of human faces are similar to ellipsoid, the ellipsoidal mask that has the fixed ratio of major and minor axis can be used to detect the candidate area. The positions of eyes and lips are extracted in this candidate area, and then the morphological analysis is applied to make features which are consist of six parameters, such as the geometrical ratio of eyes and lips. A back-propagation neural network is used as a classifier to determine the most possible face region. The experimental result is conducted to verify its efficiency compared with those of previous works.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1089-1090
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• 2011

This paper presents a novel two-phase two-pole permanent magnet synchronous motor (PMSM) with asymmetric U-core stator structure. The construction and parameters of the novel two-phase U-core PMSM are compared with a conventional U-core single-phase PMSM (SPMSM). Then transient characteristics such as torque, back-emf, and power loss of the both PMSMs are analyzed by using 3-D Finite Element Method (FEM). Under the same condition of rated input current, synchronous speed, similar dimensions and volume, FE results show that the two-phase PMSM with U-core stator has significantly less torque ripple than single-phase U-core PMSM, with similar power loss and efficiency.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.4
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• pp.89-96
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• 2002

This paper aims to develop an intelligent model for predicting top-bead width for the robotic GMA(Gas Metal Arc) welding process using BP(Back-propagation) neural network and multiple regression analysis. Firstly, based on experimental data, the basic factors affecting top-bead width are identified. Then BP neural network model and multiple regression models of top-bead width are established. The modeling methods and procedure are explained. The developed models are then verified by data obtained from the additional experiment and the predictive behaviors of the two kind of models are compared and analysed. Finally the modeling methods, predictive behaviors md the advantages of each models are discussed.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.816_817
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• 2009

Optimization of geometry is one of the most important design process of the electrical motors. Tooth and yoke width are important variables that can maximize back emf and load torque among various design parameters. In this paper, in order to design the tooth and yoke width effectively, an equivalent magnetic circuit of one pole is constructed and an optimal value of tooth and yoke width resulting minimum reluctance are determined instead of a finite element analysis(FEA) that is time consuming.

• Korean Journal of Human Ecology
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• v.12 no.1
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• pp.63-73
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• 2003

The purpose of this study was to quantify the hands of fabrics for the Korean folk clothes using both a KES-FB and an artificial neural network. In order to select the proper input parameters, we calculated the correlation using step-wise regression between mechanical properties and the hand value of fabrics. For the classification, the primary hand values and total hand value, five neural networks with three-layered structure were constructed using the error back propagation algorithm and, in order to reduce errors and to speed up learning, the momentum method was selected. From the analysis of the primary and total hands using a self-constructed artificial intelligence system, the error rates of sleekness, stiffness, silkiness, and roughness compared with the judgement of expert panels were found to be 3.3%, 3.3%, 1.6%, and 4.9%, respectively, while that of the total hand was 9.83%.

• Proceedings of the KSRS Conference
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• v.1
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• pp.212-215
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• 2006

This paper describes several reliability models to estimate COMS ground segment availability and shows assessed availability according to GS function. Due to a back-up concept among three ground center, SOC will have all H/W and S/W module to be installed in MSC and KOSC site. Therefore, all configurations and availability parameters for H/W and S/W modules in MSC and KOSC are assumed as equal with those in SOC, if related modules have same function. Prior to access availability over COMS GS function, Availability related to fundamental configuration such as series, parallel, partial operation, and module combined H/W and S/W is described. Consequently, all functions are expected to operate with more than 99% of availability.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.835-844
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• 2003

A difficulty in spatial data analysis is to choose a suitable theoretical variogram. Generally mean squares error(MSE) is used as a criterion of selection. However researchers encounter the case that the values of MSE are almost the same whereas the estimates of parameters are different. In this case, the selection criterion based on MSE should take into account the parameter estimates. In this paper we study on the method of selecting a variogram using spatial correlation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1404-1407
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• 1996

A quality monitoring system in butt welding process is proposed to estimate weld pool sizes. The geometrical parameters of the weld pool such as the top bead width and the penetration depth plus half back width are utilized to prove the integrity of the weld quality. The monitoring variables used are the surface temperatures measured at three points on the top surface of the weldment. The temperature profile is assumed that it has a gaussian distribution in vertical direction of torch movement and verify this assumption through temperature analysis. A neural network estimator is designed to estimate weld pool size from temperature informations. The experimental results show that the proposed neural network estimator which used gaussian distribution as temperature information can estimate the weld pool sizes accurately than used three point temperatures as temperature information. Considering the change of gap size in butt welding, the experiment were performed on various gap size.