• Geomechanics and Engineering
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• 제30권5호
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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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• 제36권3호
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• pp.141-153
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• 2023

본 리뷰 논문에서는 일반 접촉 역학 이론과 더불어 유기탄성체 마찰에 관한 이론 및 배경을 소개한다. 특히 Greenwood & Williamson 접촉 역학 이론을 확장하여 거친 표면을 자기-아핀(self-affine) 특성으로 고려한 접촉 역학 및 마찰의 수학적 모델을 제시한 Klüppel & Heinrich 이론을 중심으로 유기탄성체 복합재료의 마찰 거동에 대해 살펴본다. 자기-아핀 특성에 의한 노면의 멀티스케일 거칠기로 인해 미끄러짐 마찰 시 유기탄성체 복합재료는 다양한 주파수에 따른 동적 변형이 가해지며 이때 재료가 나타내는 점탄성이 마찰 거동에 주요한 영향을 미친다. 따라서 유기탄성체 복합재료의 비선형 점탄성을 고려하여 광범위한 주파수 영역에서의 점탄성 거동인 마스터커브를 구축하는 원리 및 방법을 제시하였다. 마지막으로 유기탄성체 복합재료 마찰 이론을 타이어 트레드 컴파운드와 노면 간의 마찰에 응용한 실험적 결과와 그 물리적 의미를 이론과 접목하여 설명하였다.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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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.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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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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• 제9권5호
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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.

• 대한지리학회지
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• 제40권3호
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• pp.253-273
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• 2005

최근 한국 사회에는 산지의 공간적 연속성을 파악하고자 하는 사회적인 요구가 높다. 이 연구는 이러한 사회적 요구를 수용하면서 한반도의 산지와 유역분수계의 공간적 특징을 효율적으로 표현할 수 있는 '산줄기 지로'의 개념을 제시하는 것이 목적이다. '산줄기 지도'란 지표면에서 일정한 고도를 가지면서 산으로 인식될 수 있는 지점들을 연결한 선을 표시한 지도이다. 이 연구에서는 먼저 우리 사회에서 전통적인 산지 인식체계로 알려져 있는 백두대간 체계가 한반도의 산지특성과 유역분수계를 얼마나 정확하게 설명하고 있는지 에 대한 검증을 실시하였다 백두대간 체계는 유역분수계의 특성을 파악하거나 산지의 연속성을 명확하게 제시하는 목적에 사용되기에는, 1)유역분수계 구분의 대표성 결여, 2)유역분수계 표현의 부정확성, 3) 산지 표현의 대표성 결여, 그리고 4) 지정학적 측면에서의 문제점 등을 안고 있다. 이러한 문제점들을 극복하기 위해 한반도의 산지와 유역분수계의 공간적 분포 특성을 정량적으로 분석하였다. 그 결과를 토대로 한반도의 산지 분포를 유역분수계의 관점 에서 계층화하여 산줄기 지도를 제시하였다. 제시된 산줄기 지도에서는 한반도에서 유역 면적이 $5,000km^2$ 이상 되는 유역분지의 분수계 중에서, 고도가 100m 이상이 되는 지점들을 연결한 선을 1차 산줄기로 규정하였다. 그 다음 차수의 산줄기들은 기준 유역면적을 매 차수마다 반분하여 산줄기를 그릴 수 있도록 설계하였다. 이 과정에서 각 차수의 산줄기 가 표현할 수 있는 각종 지형학적 특성을 제시하는 경험공식들을 개발하였다. 이러한 과정을 통해 한반도 전체 산줄기 의 분포와 특성을 필요한 목적과 표현하려는 지도의 축적에 따라 계층적으로 표현할 수 있는 토대를 마련하였다. 이 지도는 유역분수계에 근거했다는 점에서 산경표의 산줄기 체계와 유사성을 지니고 있으나, 근대 지형학의 관점에서 산지의 규모와 연속성을 보다 체계적으로 해석한 것이다. 제시된 산줄기 체계는 산지의 형성작용과 그 과정을 설명하는 교육적인 모형인 산맥체계와 뚜렷이 구별된다는 점을 유념할 필요가 있다.