프랙탈 차원을 이용한 해저 퇴적환경 분석 적용성 검토
A Review of the Applicability of The Fractal Dimension of Grain Size Distribution for a Analysis of Submarine Sedimentary Environments
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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.
Abstract
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.
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