• Journal of the Korean Society for Precision Engineering
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• v.18 no.6
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• pp.93-101
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• 2001

This paper presents modeling of an inductive micro position sensing system and its analysis. The parameters affected the system response are excitation frequency, turn ratio, input position, air-gap size, load resistance, and geometric dimensions. To analyze the system, we try to establish a modeling based on an equivalent magnetic circuit with permeances. The model is verified by the experimental results from 1 kHz to 20 kHz. The magnetic circuit model is well fitted to the experimental data except a little error due to LC resonance in the large turn-ratio system. Modeling enables us to theoretically approach the response characteristics. Based on the magnetic circuit model, system parameters can be selected in such a way to obtain the required characteristics such as high sensitivity, good linearity, or small size.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.10
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• pp.1062-1069
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• 2012

This paper suggests a computational modeling to reflect static/dynamic characteristics of LM bearings. A theoretical study for modeling LM bearings is elucidated by using the Hertz contact theory, the Lagrange's equation of motion, normal mode analysis and a calculation of equivalent moment center. The complex geometry of LM bearings is replaced by a simplified model with eight springs only. The suggested model reflects static and dynamic characteristics of LM bearings without any consideration for the shape of the bed or stages on the LM bearings. The modal experimental results are compared to the simulation results with the suggested computational modeling. The difference between the experiments and simulation is calculated less than 8%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1343-1351
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• 2000

Thermally induced errors have been significant factors affecting the machine tool accuracy. In this paper, the spindle thermal error has been focused, where the 5 degree of freedom thermal error components are considered. An effective measurement system has been devised for the 5 DOF thermal errors, consisting of gap sensors and thermocouples around the micro-computer interfaced environment. Several thermal error modeling techniques are also implemented for the thermal error prediction: multiple linear regression, neural network and system identification methods, etc. The performance of the thermal error modeling techniques is evaluated and compared, giving the system identification method as the optimum model having the least deviation. The developed system for the thermal error measurement and modeling was practically applied to a CNC machining center, and the spindle thermal errors were effectively compensated around the micro computer-machine tool interfaced networks. The machine tool accuracy was improved about 4-5 times typically.

• Journal of Mechanical Science and Technology
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• v.16 no.9
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• pp.1093-1101
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• 2002

Continuous fiber ceramic composites (CFCCs) have advantages over monolithic ceramics : Silicon Nitride composites are not well used for application because of their low fracture toughness and fracture strength, but CFCCs exhibit increased toughness for damage tolerance, and relatively high stiffness in spite of low specific weight. Thus it is important to characterize the fracture resistance and properties of new CFCCs materials. Tensile and flexural tests were carried out for mechanical properties and the fracture resistance behavior of a SCS6 fiber reinforced Si$_3$N$_4$ matrix CFCC was evaluated. The results indicated that CFCC composite exhibit a rising R curve behavior in flexural test. The fracture toughness was about 4.8 MPa$.$m$\^$1/2 , which resulted in a higher value of the fracture toughness because of fiber bridging. Mechanical properties as like the elastic modulus, proportional limit and the ultimate strength in a flexural test are greater than those in a tensile test. Also a numerical modeling of failure process was accomplished for a flexural test. This numerical results provided a good simulation of the cumulative fracture process of the fiber and matrix in CFCCs.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.74-84
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• 2015

The core activities of a bicycle manufacturer are design, engineering analysis, and manufacturing. Therefore, it is important to develop a configuration design system for bicycles in order to automate the design process and facilitate the use of design data in engineering analysis and manufacturing. In this paper, we present a method to develop a bicycle configuration design system based on the part-shape information model. The proposed method enables the construction of a CAD library using modeling functions with equations and parameters that are common to most 3D mechanical CAD systems. Furthermore, the part-shape information model ensures the independence between the configuration design system and the library, making it possible to extend the CAD library flexibly without changing the system architecture.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.305-311
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• 2005

This research presents a three-dimensional modeling technique for a flexible sheet. A relative coordinate formulation is used to represent the kinematics of the sheet. The three-dimensional flexible sheet is modeled by multi-rigid bodies interconnected by out-of-plane joints and plate force elements. A parent node is designated as a master body and is connected to the ground by a floating joint to cover the rigid motion of the flexible sheet in space. Since the in-plane deformation of a sheet such as a paper and a film is relatively small, compared to out-of-plane deformation, only the out-of-plane deformation is accounted for in this research. The recursive formulation has been adopted to solve the equations of motion efficiently. An example is presented to show the validity of the proposed method.

• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.859-869
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• 2016

Component-scale modeling of boiling is predominantly based on the Eulerian-Eulerian two-fluid approach. Within this framework, wall boiling is accounted for via the Rensselaer Polytechnic Institute (RPI) model and, within this model, the bubble is characterized using three main parameters: departure diameter (D), nucleation site density (N), and departure frequency (f). Typically, the magnitudes of these three parameters are obtained from empirical correlations. However, in recent years, efforts have been directed toward mechanistic modeling of the boiling process. Of the three parameters mentioned above, the departure diameter (D) is least affected by the intrinsic uncertainties of the nucleate boiling process. This feature, along with its prominence within the RPI boiling model, has made it the primary candidate for mechanistic modeling ventures. Mechanistic modeling of D is mostly carried out through solving of force balance equations on the bubble. Forces incorporated in these equations are formulated as functions of the radius of the bubble and have been developed for, and applied to, low-pressure conditions only. Conversely, for high-pressure conditions, no mechanistic information is available regarding the growth rates of bubbles and the forces acting on them. In this study, we use direct numerical simulation coupled with an interface tracking method to simulate bubble growth under high (up to 45 bar) pressure, to obtain the kind of mechanistic information required for an RPI-type approach. In this study, we compare the resulting bubble growth rate curves with predictions made with existing experimental data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2603-2609
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• 2014

Reliability analysis of mechanical systems requires statistical modeling of input random variables such as distribution function types and statistical parameters that affect the performance of the mechanical systems. Some random variables are correlated, but considered as independent variables or wrong assumptions on input random variables have been used. In this paper, joint distributions were modeled using copulas and Bayesian method from limited number of data. To verify the proposed method, statistical simulation tests were carried out for various number of samples and correlation coefficients. As a result, the Bayesian method selected the most probable copula types among candidate copulas even though the candidate copula shapes are similar for low correlations or the number of data is limited. The most probable copulas also yielded similar reliabilities with the true reliability obtained from a true copula, so that it can be concluded that the Bayesian method provides accurate statistical modeling for the reliability analysis.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.2
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• pp.131-136
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• 2023

Nanocomposites have been considered innovative composite materials that have multi-functionality and high performance. Because the incorporation of nanoscale fillers may significantly improve the electrical, mechanical, and thermal properties of composites, numerous extensive studies on the characterization of nanocomposites with nanoscale fillers have been performed. In particular, the development of nanocomposites using carbon-based nanoscale fillers (e.g., carbon nanotubes, carbon black, graphene nanoplates) have attracted much interest in the composite field. This paper provides a review of recent advances in the electrical/mechanical characteristics of nanocomposites, which are essential for their practical applications. Furthermore, this paper revisits the recent research on multi-scale modeling, which is a promising approach for predicting the characteristics of nanocomposites. The current challenges and future development potentials for multi-scale modeling are also discussed.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.218-219
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• 2003