• Journal of Korean Society on Water Environment
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• v.33 no.6
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• pp.650-660
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• 2017

In this study, pollutant emission characteristics by water damage period analyzed 11 items (water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and flow) with load duration curve, time series load curve and factor analysis for three years (2014-2016). Load duration curve is applied to judge the level of impaired waterbody and estimate impaired level by pollutants such as BOD and T-P in this study depending on variation of stream flow. Water quality standard exceeded the flow of mid-range and low-range by flow condition evaluation using load duration curve. This watershed was influenced by point source more than non-point source. Cumulative excess rate of BOD and T-P kept water quality standard for all seasons (spring, summer, autumn and winter) except BOD 59% in spring. Water quality changes were influenced by pollutants of basic environmental treatment facilities and agricultural areas during spring and summer. Results of factor analysis were classified commonly first factor (BOD, COD, and TOC) and second factor (flow, water temperature and SS). Therefore, effects of artificial pollutants and maintenance water must be controlled seasonally and reduced relative to water damage caused by point pollution sources with effluent standard strengthened in the target watershed.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.578-580
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• 1995

In this paper, a method for the daily maximum load forecasting which uses a chaotic time series in power system and artificial neural network. We find the characteristics of chaos in power load curve and then determine a optimal embedding dimension and delay time, For the load forecast of one day ahead daily maximum power, we use the time series load data obtained in previous year. By using of embedding dimension and delay time, we construct a strange attractor in pseudo phase plane and the artificial neural network model trained with the attractor font mentioned above. The one day ahead forecast errors are about 1.4% of absolute percentage average error.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.835-837
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• 1996

In this paper, a method for the daily maximum load forecasting which uses a chaotic time series in power system and artificial neural network(Back-propagation) is proposed. We find the characteristics of chaos in power load curve and then determine a optimal embedding dimension and delay time. For the load forecast of one day ahead daily maximum power, we use the time series load data obtained in previous year. By using of embedding dimension and delay time, we construct a strange attractor in pseudo phase plane and the artificial neural network model trained with the attractor mentioned above. The one day ahead forecast errors are about 1.4% for absolute percentage average error.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1144-1148
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• 1997

In this paper, a method for the daily maximum load forecasting which uses a chaotic time series in power system and artificial neural network. We find the characteristics of chaos in power load curve and then determine a optimal embedding dimension and delay time. For the load forecast of one day ahead daily maximum power, we use the time series load data obtained in previous year. By using of embedding dimension and delay time, we construct a strange attractor in pseudo phase plane and the artificial neural network model trained with the attractor mentioned above. The one day ahead forecast errors are about 1.4% for absolute percentage average error.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.26-32
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• 2007

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform(WFT or STFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform(WT) is used to decompose the acoustic emission(AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.342-348
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• 2005

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform (WFT or SIFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform (WT) is used to decompose the acoustic emission (AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.4
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• pp.1051-1061
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• 1995

In order perform leak-before-break design of nuclear piping systems and integrity evaluation of reactor vessels, full stress-strain (.sigma. - .epsilon.) curves and fracture resistance (J-R) curves are required. However it is time-consuming and expensive to obtain J-R curves experimentally. The objective of this paper is to develop two methods for J-R curve prediction. In the first method, elastic-plastic finite element analyses for a series of crack length / specimen width ratio were performed. Accordingly the load versus load line displacement (P .delta.) curve corresponding to the fracture strain is obtained and the J-R curve based on the generalized locus method is obtained. In the second method, the correlation between .sigma.-.epsilon. curves and J-R curves was statistically analyzed and an empirical equation to predict the J-R curve from the .sigma.-.epsilon. test result is proposed. A good correlation between the predicted results based on the proposed methods and the experimental ones is obtained.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.669-673
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• 2001

The objective of this paper is to predict and evaluate the sealing performance of the thermoplastic rubber component in the proto-design stage. The large strain and large deformation properties of rubber are modeled by strain energy function and the related material constants are calculated from the test data. The viscoelastic property of the rubber is also considered using the coefficients in a Prony series representation of a viscoelastic modulus ken the compression stress relaxation test. The results show that the current design of cap mount system has 2-different stiffness caused by the cap-mount contact and the viscoelastic property of rubber plays an important role in time dependent deformation.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.692-699
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• 2005

In order to evaluate that factors such as span length, member type and train loading affect on fatigue of steel railway bridges, in this paper, a series field tests were carried out for some plate girder bridges. From the result estimated by rainflow counting method to analyses real strain-time curve obtained from the field test, it was known that the fatigue effect is more significant in the bridge having short span length and the secondary members regardless of train load types.

• Journal of Korean Society on Water Environment
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• v.37 no.4
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• pp.249-262
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• 2021

This study investigated the pollution characteristics of the main pollution zone in the Hwangguji watershed and the influence of the tributary on the main stream. The characteristics of the main pollution zone, including, the water quality index (WQI), stream rating, load duration curve (LDC), delivery load density (DLD), and contribution of the tributary to the mainstream, were evaluated by time-series visual heatmap. The WQI of the mainstream of Hwangguji was lowered to the poor (IV) level from the inflow point of Suwon stream (SW) and the LDC excess rate in the T-P was higher than that of BOD₅, especially for the wet season, suggesting that management of non-point source with T-P is preferred. The contribution (%) of the tributaries in the upstream section of Hwangguji watershed were BOD₅ 14.54%, TOC 15.67%, T-N 5.43%, and T-P 6.97%. In particular, the Suwon sewage treatment plant located in the mainstream showed a high contribution of BOD₅ (64.40%) and T-P (53.54%), respectively, due to the high discharge rate (6.019 m³/sec). Meanwhile, Sammi and Gal stream have a large impact on the mainstream with high DLD and poor WQI. Thus, both streams were considered as pollution hot spots. These results provide useful basic data for preparing more effective water quality improvement and management plans in the watershed.