• Title/Summary/Keyword: box counting method

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Fatigue life prediction of horizontally curved thin walled box girder steel bridges

  • Nallasivam, K.;Talukdar, Sudip;Dutta, Anjan
    • Structural Engineering and Mechanics
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    • v.28 no.4
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    • pp.387-410
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    • 2008
  • The fatigue damage accumulation rates of horizontally curved thin walled box-girder bridge have been estimated from vehicle-induced dynamic stress history using rain flow cycle counting method in the time domain approach. The curved box-girder bridge has been numerically modeled using computationally efficient thin walled box-beam finite elements, which take into account the important structural actions like torsional warping, distortion and distortional warping in addition to the conventional displacement and rotational degrees of freedom. Vehicle model includes heave-pitch-roll degrees of freedom with longitudinal and transverse input to the wheels. The bridge deck unevenness, which is taken as inputs to the vehicle wheels, has been assumed to be a realization of homogeneous random process specified by a power spectral density (PSD) function. The linear damage accumulation theory has been applied to calculate fatigue life. The fatigue life estimated by cycle counting method in time domain has been compared with those found by estimating the PSD of response in frequency domain. The frequency domain method uses an analytical expression involving spectral moment characteristics of stress process. The effects of some of the important parameters on fatigue life of the curved box bridge have been studied.

Enhancement of the Box-Counting Algorithm for Fractal Dimension Estimation (프랙탈 차원 추정을 위한 박스 계수법의 개선)

  • So, Hye-Rim;So, Gun-Baek;Jin, Gang-Gyoo
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.9
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    • pp.710-715
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    • 2016
  • Due to its simplicity and high reliability, the box-counting(BC) method is one of the most frequently used techniques to estimate the fractal dimensions of a binary image with a self-similarity property. The fractal calculation requires data sampling that determines the size of boxes to be sampled from the given image and directly affects the accuracy of the fractal dimension estimation. There are three non-overlapping regular grid methods: geometric-step method, arithmetic-step method and divisor-step method. These methods have some drawbacks when the image size M becomes large. This paper presents a BC algorithm for enhancing the accuracy of the fractal dimension estimation based on a new sampling method. Instead of using the geometric-step method, the new sampling method, called the coverage ratio-step method, selects the number of steps according to the coverage ratio. A set of experiments using well-known fractal images showed that the proposed method outperforms the existing BC method and the triangular BC method.

A Study on the Design of Fatigue Strength using Fractal Character of Surface Micro-crack (표면미소균열의 프랙탈 특성을 이용한 피로강도설계에 관한 연구)

  • Cho, Seok-Swoo;Joo, Won-Sik
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.12
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    • pp.143-151
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    • 1999
  • The shape of surface micro-crack is very irregular due to nonhomogeneous microstructure but is very important in respect to qualitative estimation of fatigue life. Fractal geomety can quantify the shape of surface mciro-crack. Fractal dimension is measured for surface micro-cracks with coast line and box counting method and estimates cycle ration in Al 2024-T3. The average fractal dimension $D_{favg}$ of surface micro-cracks has 3-parameter weibull distribution and location parameter is nearly constant but shape parameter decreases as cycle ration increases. The fractal dimension by coast line method is measured for individual surface micro-crack but the fractal dimension by box countin method is measured for all the surface micro-cracks under sampling area. Therefore, This paper shows fractal dimension $D_{fb}$ can predict cycle ratio $N/N_f$ more convenient than fractal dimension $D_{favg}$.

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Simulation on Surface Tracking Pattern using the Dielectric Breakdown Model

  • Kim, Jun-Won;Roh, Young-Su
    • Journal of Electrical Engineering and Technology
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    • v.6 no.3
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    • pp.391-396
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    • 2011
  • The tracking pattern formed on the dielectric surface due to a surface electrical discharge exhibits fractal structure. In order to quantitatively investigate the fractal characteristics of the surface tracking pattern, the dielectric breakdown model has been employed to numerically generate the surface tracking pattern. In dielectric breakdown model, the pattern growth is determined stochastically by a probability function depending on the local electric potential difference. For the computation of the electric potential for all points of the lattice, a two-dimensional discrete Laplace equation is solved by mean of the successive over-relaxation method combined to the Gauss-Seidel method. The box counting method has been used to calculate the fractal dimensions of the simulated patterns with various exponent $\eta$ and breakdown voltage $\phi_b$. As a result of the simulation, it is found that the fractal nature of the surface tracking pattern depends strongly on $\eta$ and $\phi_b$.

Application of Fractal Geometry on the Static Growing Crack of STS316 CT Specimen with a Side Groove (측면 홈을 가지는 STS316 CT시험편의 정적 성장균열에 대한 프랙탈 기하학의 응용)

  • Yun, Yu-Seong;Kwon, Oh-Heon
    • Journal of the Korean Society of Safety
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    • v.17 no.4
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    • pp.38-44
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    • 2002
  • The application of fractal concept provides an useful method in the study for the quantitative analysis of irregular variations like the fracture surfaces and crack profiles. Fractal curves have characteristics that represents a self-similarity based on the fractal dimension. The fractal dimensions were obtained by the box counting method. In this report, we obtained the nearly stable fractal dimensions of fracture crack profiles for STS316 with CT specimen as the crack advances and the relationships between crack length and fractal dimension. Moreover fractal fracture parameter that corresponds to J-R curve is shown by the relationships between fractal dimension and crack extension. From the results, we concluded that crack extension of high toughness material also shows the fractal characteristics, which can be used in order to evaluate the crack life precisely.

A Fundamental Study of Fractal Characteristics for a Crack Growth Profile (성장균열 형상에 대한 기초적 프랙탈 특성연구)

  • 권오헌
    • Journal of Advanced Marine Engineering and Technology
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    • v.22 no.4
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    • pp.522-528
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    • 1998
  • This paper presents a fundamental fractal characteristics of the growing crack that has an irregularity producing a zigzag crack contour. This irregularity is analysed by a fractal geometry in a box counting method that is a very simple technique. First the fractal dimensions and actual fractal extensive crack length are obtained. Also a fractal fracture energy relation with a fractal dimension is found so as to get fractal crack behaviors. Thus it can be shown that the fractal dimension has a possibility as a fracture parameter in a real crack growth length meaning.

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Quad-tree Segmentation using Fractal Dimension based on Accurate Estimation of Noise and Its Application (잡음의 정확한 추정 기반 프랙탈 차원 쿼드트리 영역분할과 응용)

  • Koh, Sung-Shik;Kim, Chung-Hwa
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.39 no.3
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    • pp.35-41
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    • 2002
  • There are many image segmentation methods having been published as the results of research so far, but it is difficult to be partitioned to each similar range that should be extracted into the accurate parameters of image information on the images with noises. Also if it is used to fractal coding, according to amount of noise in image, the image segmentation leads to decreasing of the compression ratio. In this paper, we propose the new quad-tree image segmentation using the box-counting dimension which can estimate the effective image information parameters against the noise properties and apply this method to fractal image coding. As the result of simulation, we confirm that the image segmentation is improved to 31.10% for parameter detection of image information and compression ratio is enhanced to 38.93% for fractal image coding when tested on 10% Gaussian white noise image by the proposed quad-tree method compared with method using existing quad-tree. 

FRACTAL ANALYSIS OF TIDAL CHANNEL USING HIGH RESOLUTION SATELLITE IMAGES

  • Eom, Jin-Ah;Lee, Yoon-Kyung;Ryu, Joo-Hyung;Won, Joong-Sun
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.29-32
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    • 2007
  • Tidal channel development is influenced by sediment type, grain size, composition and tidal current. Tidal channels are usually characterized by channel development, density and shape. Quantitative analysis of tidal channels using remotely sensed data have rarely been studied. The objective of this study is to quantify tidal channels in terms of fractal dimension and compare different inter-tidal channel patterns. For the fractal analysis, we used Box counting method which had been successfully applied to streams, coastlines and others linear features. For a study, the southern part of Ganghwado tidal flats was selected where is famous for high dynamics of tidal currents and vast tidal flats. This area has different widths and lengths of tidal channels. IKONOS and Komsat-2 MSC images were used for extracting tidal channels, and the Box counting method was applied to obtain fractal dimensions (D) for each tidal channel. Yeochari area possesses channels with linear pattern and less dense development and accordingly show low D values ranging from 1.037 to 1.038. On other hands, area (near Donggumdo and Yeongjongdo ) of dendrites channel pattern and dense development resulted in high D values from 1.2057 to 1.2667. Also, area possesses channels with linear pattern had low density about $18{\sim}24%$. Area of dendritic channel pattern had high density about $34{\sim}69%$. The difference of fractal dimensions about 0.2 according to channel development in tidal flats is relatively large enough to use as an index for tidal channel classification. Also, area where channels showed linear pattern had low density about $18{\sim}24%$. Area of dendritic channel pattern had high density about $34{\sim}69%$. Using fractal dimension and density, it would be possible to quantify the tidal channel development in association with surface characteristics.

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Fractal Analysis of Tidal Channel using High Resolution Satellite Image (고해상도 위성 영상을 이용한 조류로의 프랙털 분석)

  • Eom, Jin-Ah;Lee, Yoon-Kyung;Ryu, Joo-Hyung;Won, Joong-Sun
    • Korean Journal of Remote Sensing
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    • v.23 no.6
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    • pp.567-573
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    • 2007
  • Tidal channel development is influenced by sediment type, grain size, composition and tidal current. Tidal channels are usually characterized by channel formation, density and shape. Quantitative analysis of tidal channels using remotely sensed data have rarely been studied. The objective of this study is to quantify tidal channels in terms of fractal dimension and compare different inter-tidal channel patterns and compare with DEM (Digital Elevation Model). For the fractal analysis, we used box counting method which had been successfully applied to streams, coastlines and others linear features. For a study, the southern part of Ganghwado tidal flats was selected which know for high dynamics of tidal currents and vast tidal flats. This area has different widths and lengths of tidal channels. IKONOS was used for extracting tidal channels, and the box counting method was applied to obtain fractal dimensions (D) for each tidal channel. Yeochari area where channels showed less dense development and low DEM had low fractal dimenwion near $1.00{\sim}1.20$. Area (near Donggumdo and Yeongjongdo) of dendritic channel pattern and high DEM resulted in high fractal dimension near $1.20{\sim}1.35$. The difference of fractal dimensions according to channel development in tidal flats is relatively large enough to use as an index for tidal channel classification. Therefore we could conclude that fractal dimension, channel development and DEM in tidal channel has high correlation. Using fractal dimension, channel development and DEM, it would be possible to quantify the tidal channel development in association with surface characteristics.