• 연구논문집
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• s.32
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• pp.111-120
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• 2002

In this paper, the design of a decatizing cylinder with uniformly distributed pressure in a decatizing system is investigated by using the Finite Element Method. Particularly, since deflection of a cylinder will not perform to iron the fabrics, the cylinder design insuring uniform pressure is very important. In this paper proposed two improved cylinder model obtained by changing the support type of the bean and the support location. And perform optimization with two improved cylinder model.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.45-50
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• 1999

The object of this study is structure analysis of vehicle air compressor. Structure analysis is compose to nodal solution and element solution using ANSYS code. Then analysis is partition to head part, cylinder and piston part of vehicle air compressor. Stress and strain results are satisfy to Von Mises yield criterion.

• Composites Research
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• v.35 no.5
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• pp.317-321
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• 2022

In this study, the PIC design method with machine learning that automatically assigning different stacking sequences according to loading types was applied bumper beam. The input value and labels of the training data for applying machine learning were defined as coordinates and loading types of reference elements that are part of the total elements, respectively. In order to compare the 2D and 3D implementation method, which are methods of representing coordinate value, training data were generated, and machine learning models were trained with each method. The 2D implementation method is divided FE model into each face and generating learning data and training machine learning models accordingly. The 3D implementation method is training one machine learning model by generating training data from the entire finite element model. The hyperparameter were tuned to optimal values through the Bayesian algorithm, and the k-NN classification method showed the highest prediction rate and AUC-ROC among the tuned models. The 3D implementation method revealed higher performance than the 2D implementation method. The loading type data predicted through the machine learning model were mapped to the finite element model and comparatively verified through FE analysis. It was found that 3D implementation PIC bumper beam was superior to 2D implementation and uni-stacking sequence composite bumper.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.4
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• pp.243-248
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• 2022

Weight optimization was performed for a rotorcraft shaft system using one-dimensional Euler-Bernoulli beam elements. Torsion, shaft support stiffness such as bearings, flange mass are all considered. To guarantee structural dynamic stability, eigenvalue analysis was performed to avoid critical speed and tooth mesh excitation form the gearbox. The weight optimization was performed by adjusting the thickness and radius while the length of the shaft was fixed, and the optimization process was divided into two stages. In the first, the weight is optimized with the torsional strength constraint. In the second, the difference between the primary mode of shaft and the critical speed is maximized so that the primary mode of the shaft can avoid the critical speed while the constraint on the torsional strength of the shaft is satisfied according to the standard for shaft system stability (AMC P 706-201, 1974). The proposed method was verified by comparing the results of the optimal design using the given one-dimensional beam elements with the stress results of the 3D finite element and the actual manufactured shaft.

• Steel and Composite Structures
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• v.25 no.6
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• pp.663-670
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• 2017

The problem of layup optimization of the composite laminates involves a very complex multidimensional solution space which is usually non-exhaustively explored using different heuristic computational methods such as genetic algorithms (GA). To ensure the convergence to the global optimum of the applied heuristic during the optimization process it is necessary to evaluate a lot of layup configurations. As a consequence the analysis of an individual layup configuration should be fast enough to maintain the convergence time range to an acceptable level. On the other hand the mechanical behavior analysis of composite laminates for any geometry and boundary condition is very convoluted and is performed by computational expensive numerical tools such as finite element analysis (FEA). In this respect some studies propose very fast FEA models used in layup optimization. However, the lower bound of the execution time of FEA models is determined by the global linear system solving which in some complex applications can be unacceptable. Moreover, in some situation it may be highly preferred to decrease the optimization time with the cost of a small reduction in the analysis accuracy. In this paper we explore some machine learning techniques in order to estimate the failure of a layup configuration. The estimated response can be qualitative (the configuration fails or not) or quantitative (the value of the failure factor). The procedure consists of generating a population of random observations (configurations) spread across solution space and evaluating using a FEA model. The machine learning method is then trained using this population and the trained model is then used to estimate failure in the optimization process. The results obtained are very promising as illustrated with an example where the misclassification rate of the qualitative response is smaller than 2%.

• The Journal of Bigdata
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• v.3 no.2
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• pp.11-18
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• 2018

This study is a study on domain automatic classification for domain - based quality diagnosis which is a key element of big data quality diagnosis. With the increase of the value and utilization of Big Data and the rise of the Fourth Industrial Revolution, the world is making efforts to create new value by utilizing big data in various fields converged with IT such as law, medical, and finance. However, analysis based on low-reliability data results in critical problems in both the process and the result, and it is also difficult to believe that judgments based on the analysis results. Although the need of highly reliable data has also increased, research on the quality of data and its results have been insufficient. The purpose of this study is to shorten the work time to automizing the domain classification work which was performed from manually to using machine learning in the domain - based quality diagnosis, which is a key element of diagnostic evaluation for improving data quality. Extracts information about the characteristics of the data that is stored in the database and identifies the domain, and then featurize it, and automizes the domain classification using machine learning. We will use it for big data quality diagnosis and contribute to quality improvement.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1411-1421
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• 1995

A rigid visco-plastic finite element method has been developed for modeling superplastic forming processes. The optimum pressure-time relationship for a target strain rate and thickness distributions was predicted using two-node line element based on membrane approximation for plane strain and axisymmetric condition. Analysis of superplastic forming was carried out using the developed program and the numerical results were compared to the values available in the literature for plane strain problems. For description of the contact between the dies and sheet, the direct projection method was applied to the complicated problem and the validity of the scheme was tested. Experiments for the various geometries such as hemisphere and cone were performed with the developed forming machine using the calculated optimum pressure-time curves. Comparison between analysis and experiments showed good agreement.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3
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• pp.380-387
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• 2013

In this study, two finite element (FE) models were developed to evaluate the thermal characteristics of a feeding axis of a CNC lathe. One was used for analysis of heat transfer to identify the temperature distribution of the feeding axis and then, the other was used for analysis of thermal deformation to evaluate its structural behavior based on the temperature distribution. The FE models were based on the test standard for the axial thermal displacement. The feeding velocity was composed of three steps: the ascending, constant, and descending velocities. Therefore, the heat generation and convection coefficient were calculated for each velocity and applied to the thermal FE model. The convection coefficient for the ball screw rotation was based on an experimental equation. The result of the analytical thermal displacement was compared with that of the experimental displacement to verify the finite element models.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.6 s.183
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• pp.128-135
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• 2006

Rational dynamic modeling and analysis method f3r complex structures are studied with special attention to slide way joints. For modeling of slide way joints, a general modeling technique is used by using the influence coefficients method which is applied to the conversion of detailed finite element model to the equivalent reduced joint model. The theoretical part of this method is illustrated and the method is applied to the structure with slide way joint. In this method, the non-linearity of the contact surfaces is considered within a proper range and the boundary effect of the joint model could be eliminated. The proposed method was applied to finite element modal analysis of a clamp jointed cantilever beam and slide way joints of the vertical type lathe. The method can also be used to other kinds of joint modeling. The results of these analysis were compared with those of Yoshimura models and rigid joint models, which demonstrated the practical applicability of the proposed method.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.1
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• pp.16-22
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• 2001

In this study for reduction degree of freedom of dynamic model, a mixed method to combined finite element method and transfer matrix method is presented. This offers the advantages of an automatic reduction in the size of the eigenvalues problem and of a straightforward means of dynamic substructuring. The analytical procedure in this method for dynamic analysis of 3-dimensional cantilevered box beam are described. the result of numerical example is shown to demonstate the efficiency and accuracy of this method. The result form this example agree well those obtained by ANSYS, By using this technique, the number of nodes required in the regular finite element method is reduced and therefore a smaller com-puter can be used.