• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.341-351
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• 2022

During bolted flange assembly, the contact stiffness of some areas of the joint surface may be low due to the elastic interaction. In order to improve the contact stiffness at the lowest position of bolted flange, the correlation model between the initial bolt pre-tightening force and the contact stiffness of bolted flange is established in this paper. According to the stress distribution model of a single bolt, an assumption of uniform local contact stiffness of bolted flange is made. Moreover, the joint surface is divided into the compressive stress region and the elastic interaction region. Based on the fractal contact theory, the relationship model of contact stiffness and contact force of the joint surface is proposed. Considering the elastic interaction coefficient method, the correlation model of the initial bolt pre-tightening force and the contact stiffness of bolted flange is established. This model can be employed to reverse determine the tightening strategy of the bolt group according to working conditions. As a result, this provides a new idea for the digital design of tightening strategy of bolt group for contact stiffness of bolted flange. The tightening strategy of the bolted flange is optimized by using the correlation model of initial bolt pre-tightening force and the contact stiffness of bolted flange. After optimization, the average contact stiffness of the joint surface increased by 5%, and the minimum contact stiffness increased by 6%.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.401-411
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• 2022

To obtain the dynamic mechanical properties, fracture modes, energy and brittleness characteristics of Furong Baijiao coal rock, the dynamic impact compression tests under 0, 4, 8 and 12 MPa confining pressure were carried out using the split Hopkinson pressure bar. The results show that failure mode of coal rock in uniaxial state is axial splitting failure, while it is mainly compression-shear failure with tensile failure in triaxial state. With strain rate and confining pressure increasing, compressive strength and peak strain increase, average fragmentation increases and fractal dimension decreases. Based on energy dissipation theory, the dissipated energy density of coal rock increases gradually with growing confining pressure, but it has little correlation with strain rate. Considering progressive destruction process of coal rock, damage variable was defined as the ratio of dissipated energy density to total absorbed energy density. The maximum damage rate was obtained by deriving damage variable to reflect its maximum failure severity, then a brittleness index BD was established based on the maximum damage rate. BD value declined gradually as confining pressure and strain rate increase, indicating the decrease of brittleness and destruction degree. When confining pressure rises to 12 MPa, brittleness index and average fragmentation gradually stabilize, which shows confining pressure growing cannot cause continuous damage. Finally, integrating dynamic deformation and destruction process of coal rock and according to its final failure characteristics under different confining pressures, BD value is used to classify the brittleness into four grades.

• Composites Research
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• v.36 no.3
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• pp.141-153
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• 2023

This review paper presents an introduction of contact mechanics and rubber friction theory for sliding friction of elastomer composites in contact with rough surfaces. Particularly, Klüppel & Heinrich theory considers the self-affine (or fractal) characteristic for rough surfaces to predict adhesion and hysteresis frictions of elastomers based on the contact mechanics of Greenwood & Williamson. Due to dynamic excitation process of elastomer composites while sliding in contact with multiscale surface roughness (or asperity), viscoelastic properties in a wide frequency range becomes major contributor to friction behaviors. A brief description and examples are provided to construct a viscoelastic master curve considering nonlinear viscoelasticity of elastomer composites. Finally, application of rubber friction theory to tire tread compounds in traction with road surfaces is discussed with several experimental and theoretical results.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Geomechanics and Engineering
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• v.9 no.5
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• pp.619-629
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• 2015

Influenced by various mining activities, fractures in rock masses have different densities, set numbers and lengths, which induce different mechanical properties and failure modes of rock masses. Therefore, precisely expressing the failure criterion of the fractured rock influenced by coal mining is significant for the support design, safety assessment and disaster prevention of underground mining engineering subjected to multiple mining activities. By adopting PFC2D particle flow simulation software, this study investigated the propagation and fractal evolution laws of the micro cracks occurring in two typical kinds of rocks under uniaxial compressive condition. Furthermore, it calculated compressive strengths of the rocks with different confining pressures and box-counting dimensions. Moreover, the quantitative relation between the box-counting dimension of the rocks and the empirical parameters m and s in Hoek-Brown strength criterion was established. Results showed that with the increase of the strain, the box-counting dimension of the rocks first increased slowly at the beginning and then exhibited an exponential increase approximately. In the case of small strains of same value, the box-counting dimensions of hard rocks were smaller than those of weak rocks, while the former increased rapidly and were larger than the latter under large strain. The results also presented that there was a negative correlation between the parameters m and s in Hoek-Brown strength criterion and the box-counting dimension of the rocks suffering from variable mining activities. In other words, as the box-counting dimensions increased, the parameters m and s decreased linearly, and their relationship could be described using first order polynomial function.

• Journal of the Korean Geographical Society
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• v.40 no.3 s.108
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• pp.253-273
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• 2005

In recent years, there are strong social demands to characterize the spatial distribution of mountains in Korea. This study aims to develop a 'Sanjulgi-Jido(mountain ridge map)' that might be used not only to satisfy these social demands but also to effectively present the spatial distribution of mountains and drainage basins in the Korean Peninsular. The 'Sanjulgi-Jido' developed in this study is a map that presents the continuity of mountains based on the drainage divides that are delineated by a pre-defined drainage basin size and elevation. This study first validated the Bakdudaegan system through the analyses of a digital elevation model. The Bakdudaegan system has long been recognized as the Koreans traditional conceptual framework to characterize the spatial distribution of mountains. The analyses showed that the Bakdudaegan system has several problems to represent the mountain systems in Korea, which includes 1) the lack of the representativeness of drainage basins, 2) inaccuracy to depict the boundary of drainage basins, 3) the lack of representativeness of mountains, and 4) geo-polical issue that confines the spatial extent of mountain systems within the Korean Peninsular. In order to represent the mountains system in a more quantitative manner, we applied several terrain analysis techniques to understand the spatial distribution of mountains and drainage basins. Based on these analyses, we developed an hierarchical system to classify the continuity (If mountains, which are presented as the spatial distribution of drainage divides with a certain elevation. The first-order Sanjulgi is the drainage divides whose drainage basin are bigger than $5,000km^2$ and the point elevation is above 100m. The next order Sanjulgi is delineated as the size of drainage basin is successively divided by two. This kind of design is able to provide a logical framework to present the mountain systems at different details, depending on the purpose and scale of maps. We also provide several empirical functions to calculate various geomorphological indices for each order of Sanjulgi. The 'Sanjulgi Jido' is similar with the Bakdudaegan system, since it characterizes the continuity of mountains based on the spatial distribution of the drainage divide. It, however, has more scientific criteria to define the scale and continuity of mountains. It should be also noted that the 'Sanjulgi Jido' proposed has different logical and methodological background, compared with the mountain range map that explains the genesis of mountain systems in addition to the continuity of mountains.