• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.53-58
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• 2001

Fractal dimension is the method to measure the roughness and the irregularity of something that cannot be defined obviously by Euclidean dimension. And the analysis method of this dimension don't need perfect, accurate boundary and color like analysis lot diameter, perimeter, aspect or reflectivity of wear particles or surface. If we arranged the morphological characteristic of various wear particle by using the characteristic of fractal dimension, it might be very efficient to the diagnosis of driving condition. In order to describe morphology of various wear particle, the wear test was carried out under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are boundary fractal dimension and surface fractal dimension.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.43-50
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• 2011

The fractal method has recently been applied to a model for determining soil grain size distribution. The objective of this study is to review the applicability of the fractal method for a analysis of submarine sedimentary environments by comparing fractal constants with grain size statistical analysis for the soil samples of Pohang (PH) and Namhae (NH). The y-interception of log (grain size)-log (passing) equation was also used because grain size distribution couldn't be expressed with fractal dimension only. The result of comparison between fractal constants (dimension, y-interception) and grain size statistical indices, the fractal dimension was directly proportional to the mean and the sorting. And the y-interception showed high correlation with the mean. The fractal dimension and y-interception didn't show significant correlation with the skewness and the kurtosis. Thus regression equations between fractal constants and two statistical indices (mean, sorting) were derived. All classifications of the mean and the sorting could be determined using the regression equation based on the fractal dimension and y-interception. Therefore, fractal constants could be used as an alternative index representing the sedimentary environments instead of the mean and sorting.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.10a
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• pp.115-123
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• 1998

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried out under different experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are shape fractal dimension and surface fractal dimension. The shape fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined by sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• Tribology and Lubricants
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• v.18 no.2
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• pp.147-152
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• 2002

The morphological analysis of wear particle is a very effective means fur machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried out under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing. These descriptors to analyze shape and surface of wear particle are shape fractal dimension and surface fractal dimension. The boundary fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined by sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal parameter.

• Journal of Fashion Business
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• v.22 no.1
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• pp.135-147
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• 2018

Since the 20th century, there has been a growing interest in the new concept of fractals, a combination of mathematics and art, and the attempt to study the creative spatial aspects of the concept is being made. The purpose of this research is to examine artistic characteristics of fractal dimension and then analyze the types of fractal dimensions expressed in the fashion. Previous literature on fractals and dimension, and visual data on art and fashion collected over the Internet were used for analysis. Fractal dimension refers to the spatial concept of structural dimension of geometrical self-similarity. An analysis of the types of fractals seen in fashion revealed spatial expansion, the repetition in continual figures, superposition accordant to different sizes, and shades of different shapes. The aesthetic characteristics of fractal dimension appearing in fashions were examined based on analyses of fractal dimension types; the inherent characteristics of self-similarity, superimposition, and atypicality were found. Results obtained from this study are expected to be used as basic materials for the application of the design of fractal dimension into various perspectives of fashion.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.06a
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• pp.30-35
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• 2001

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried oui under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are share fractal dimension and surface fractal dimension. The boundry fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined b)r sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• Architectural research
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• v.16 no.4
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• pp.175-183
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• 2014

Contemporary architecture tends to deconstruct modern architecture based on rationalization just like reductionism and functionalism and secedes from it. It means change from mechanical to organic and ecological view of the world. According to these changes, consideration of a compositive relationship presented variety and complexity in architecture. Thus, the modern speculation based on rationalism cannot provide an alternative interpretation about complicated architectural phenomena. At this point in time, the purpose of this study is to investigate the possibilities of the fractal as an alternative tool of analysis and design in contemporary architecture. In this study, two major aspects are discussed. First, the fractal concepts just like 'fractal dimension', 'box-counting dimension' and 'fractal rhythm' can be applied to analysis in architecture. Second, the fractal formative principles just like 'scaling', 'superimposition trace', 'distortion' and 'repetition' can be applied to design in architecture. Fractal geometry similar to nature's patterned order can provide endless possibilities for analysis and design in architecture. Therefore further study of fractal geometry should be conducted synthetically from now on.

• Wind and Structures
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• v.31 no.4
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• pp.363-371
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• 2020

Proper understanding of offshore wind speed variability is of essential importance in practice, which provides useful information to a wide range of coastal and marine activities. In this paper, long-term wind speed data recorded at various offshore stations are analyzed in the framework of fractal dimension analysis. Fractal analysis is a well-established data analysis tool, which is particularly suitable to determine the complexity in time series from a quantitative point of view. The fractal dimension is estimated using the conventional box-counting method. The results suggest that the wind speed data are generally fractals, which are likely to exhibit a persistent nature. The mean fractal dimension varies from 1.31 at an offshore weather station to 1.43 at an urban station, which is mainly associated with surface roughness condition. Monthly variability of fractal dimension at offshore stations is well-defined, which often possess larger values during hotter months and lower values during winter. This is partly attributed to the effect of thermal instability. In addition, with an increase in measurement interval, the mean and minimum fractal dimension decrease, whereas the maximum and coefficient of variation increase in parallel.

• Journal of Ocean Engineering and Technology
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• v.10 no.4
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• pp.84-91
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• 1996

A fractal analysis on fracture surface of aluminium-particulate SiC composites was attempted. As the volume fraction of SiC in composites increases, the fractal dimension tends to increase. However, no correlation between the fractal dimension and the fracture toughness in terms of critical energy release rate was observed. Since the fractal dimension represents the roughness of fracture surface, the fracture toughness would be a function of not only fracture surface roughness but also additional parameters. Thus the applicability of fractal analysis to the estimation of fracture toughness must depend on the proper choice and interpretation of additioal paramerters. In this paper, the size of characteristic strctural unit for fracture was considered as an additional parameter. As a result, the size appeared to be a function of only volume fraction of SiC. Finally, a master curve for fracture toughness of aluminium-particulate SiC composites was proposed as a function of fractal dimension and volume fraction of SiC.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.3
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• pp.67-72
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• 2006

There are many modelling methods using theoretical and experimental data. Recently, fractal interpolation methods have been widely used to estimate and analyze various data. Due to the chaotic nature of dynamic roundness profile data in roundness some desirable method must be used for the analysis which is natural to time series data. Fractal analysis used in this paper is within the scope of the fractal interpolation and fractal dimension. Also, two methods for computing the fractal dimension has been introduced which can obtain the dimension of typical dynamic roundness profile data according to the number of data points in which the fixed data are generally lower than 200 data points. This fractal analysis result shows a possible prediction of roundness profile that has some different roundness profile in round shape operation.