• Steel and Composite Structures
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• v.8 no.6
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• pp.441-455
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• 2008

This paper presents an effective hysteretic model for the prediction and evaluation of steel reinforced concrete member seismic performance. This model adopts the load-deformation relationship acquired from monotonic load tests and incorporates the double-pivot behavior of composite members subjected to cyclic loads. Deterioration in member stiffness was accounted in the analytical model. The composite member performance assessment control parameters were calibrated from the test results. Comparisons between the cyclic load test results and analytical model validated the proposed method's effectiveness.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.561-566
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• 2003

In this study, to predict the behavior of RC beam strengthened with Carbon fiber reinforced polymer(CFRP) plate, analytical program considering material non-linearity is developed. Strain compatibility and force equilibrium are applied and internal forces of constitutive material are calculated using nonlinear stress-strain relationship. Also, to certainty the reliability of analytical program, deflection, strain of CFRP plate, change of neutral axis on cross section and crack distribution at failure are compared with those of experiment, and each results are almost coincident.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.495-502
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• 1999

Typical analytical tools in noise level estimation are using BEM and Ray Acoustics for acoustic field.0 this paper, application of both approaches have been examined for the prediction on the exterior surface of railway vehicles. Advantages and disadvantages of the tool have been also evaluated. The result shows that sound understanding of the analytical tools for noise evaluation is necessary.

• The Journal of Korean Society for Radiation Therapy
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• v.35
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• pp.15-21
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• 2023

Purpose: The purpose of this study is to compare the performance of the anisotropic analytical algorithm (AAA) and portal dose image prediction (PDIP) for patient-specific quality assurance based on electronic portal imaging device, and to evaluate the clinical feasibility of portal dosimetry using AAA. Subjects and methods: We retrospectively selected a total of 32 patients, including 15 lung cancer patients and 17 liver cancer patients. Verification plans were generated using PDIP and AAA. We obtained gamma passing rates by comparing the calculated distribution with the measured distribution and obtained MLC positional difference values. Results: The mean gamma passing rate for lung cancer patients was 99.5% ± 1.1% for 3%/3 mm using PDIP and 90.6% ± 5.8% for 1%/1 mm. Using AAA, the mean gamma passing rate was 98.9% ± 1.7% for 3%/3 mm and 87.8% ± 5.2% for 1%/1 mm. The mean gamma passing rate for liver cancer patients was 99.9% ± 0.3% for 3%/3 mm using PDIP and 96.6% ± 4.6% for 1%/1 mm. Using AAA, the mean gamma passing rate was 99.6% ± 0.5% for 3%/3 mm and 89.5% ± 6.4% for 1%/1 mm. The MLC positional difference was small at 0.013 mm ± 0.002 mm and showed no correlation with the gamma passing rate. Conclusion: The AAA algorithm can be clinically used as a portal dosimetry calculation algorithm for patientspecific quality assurance based on electronic portal imaging device.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.13-17
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• 1993

Analytical models for the prediction of the size of hardened zone in laser surface hardening are presented. The models are based on the solutions to the problem of three-dimensional heat flow in plates with infinite thickness. The validity of the model was tested on medium carbon steel for Gaaussian mode of beam. Then the model for rectangular beam was used for the prediction of the size of harened zone on various hardening process parameters. From the calculation results it appeared that the size and shape of the hardened zone are strongly dependent on process parameters suchas beam mode, beam size, and traverse speed.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.292-295
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• 2002

In this paper, an analytical model for the prediction of the elastic properties of multi-axial warp knit fabric (MWK) composites is proposed. The geometric limitation, effect of stitching fibers and design parameters of MWK composites are considered in the model. The elastic behavior of MWK composites was conducted by using an averaging method. The predicted elastic properties are in reasonably good agreement with experimental values. Finally the effect of stitching in the MWK composites are discussed.

• Journal of the korean Society of Automotive Engineers
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• v.14 no.2
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• pp.65-75
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• 1992

An analytical scheme for predicting the crack aspect pattern of materials which contain twin surface cracks was developed. Fatigue tests were performed on twin surface cracked PMMA plate specimens to obtain the interaction factor accounting for the interference effect of adjacent cracks. Here, the interaction factor is defined as the ratio of the stress intensity factor for twin surface cracks to that for a single surface crack. From the analysis of the fatigue test result, the interaction factor was presented as the ninth-order polynomial expression having a function of dimensionless crack spacing ratio. Then the polynomial expression was incorporated into the prediction program of the crack aspect pattern for twin surface cracked materials. And, the interaction effect and the coalescence condition of adjacent cracks were simplified in the newly developed prediction scheme of the crack aspect pattern. The predicted crack growth pattern using the prediction scheme was compared with test data from PMMA specimen. The predicted pattern agreed well with the test data.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.1
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• pp.58-67
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• 2020

A big data processing method to predict solar power generation using systems engineering approach is developed in this work. For developing analytical method, linear model (LM), support vector machine (SVN), and artificial neural network (ANN) technique are chosen. As evaluation indices, the cross-correlation and the mean square root of prediction error (RMSEP) are used. From multi-variable comparison test, it was found that ANN methodology provides the highest correlation and the lowest RMSEP.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.2
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• pp.77-86
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• 2018

This study develops an empirical prediction equation of spectral acceleration responses of earthquakes which can induce structural damages. Ground motion records representing hazards of low-to-moderate seismic regions were selected and organized with several influential factors affecting the response spectra. The empirical equation and estimator coefficients for acceleration response spectra were then proposed using a robust nonlinear optimization coupled with a regression analysis. For analytical verification of the prediction equation, response spectra used for low-to-moderate seismic regions were estimated and the predicted results were comparatively evaluated with measured response spectra. As a result, the predicted shapes of response spectra can simulate the graphical shapes of measured data with high accuracy and most of predicted results are distributed inside range of correlation of variation (COV) of 30% from perfectly correlated lines.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1009-1012
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• 1999

An analytical performance model that can predict the performance of a superscalar processor employing multiple branch prediction is introduced. The model is based on the conditional independence probability and the basic block size of instructions, with the degree of multiple branch prediction, the fetch rate, and the window size of a superscalar architecture. Trace driven simulation is performed for the subset of SPEC integer benchmarks, and the measured IPCs are compared with the results derived from the model. As the result, our analytic model could predict the performance of the superscalar processor using multiple branch prediction within 6.6 percent on the average.