Quantitative, SEM-based shape analysis of sediment particles in the Yellow River  被引量:3

Quantitative,SEM-based shape analysis of sediment particles in the Yellow River

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作  者:Daming Li Yangyang Li Zhichao Wang Xiao Wang Yanqing Li 

机构地区:[1]State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China [2]Civil Engineering, The University of Adelaide, Adelaide 5005, Austriia

出  处:《International Journal of Sediment Research》2016年第4期341-350,共10页国际泥沙研究(英文版)

基  金:supported in part by National Natural Science Foundation of China(Grant No.51079095);the Science Fund for Creative Research Groups of the National Natural Science Foundation of China(Grant No.51021004)

摘  要:The shape of a sediment particle can reveal part of the particle's transportation history and is a significant variable in sediment transport mechanics. Measuring sediment shapes is a difficult and time-consuming task. A whole sample sediment particle shape quantitative analysis method (WSQAM) was applied in this research for sediment statistical analysis. The shape parameter was found using sphericity and roundness descriptors: three samples were collected from the middle reach of the Yellow River at different depths. Scanning electron microscopy (SEM) was used to obtain sediment particles images. The sphericity and roundness descriptors were represented by the particle aspect ratio (AR) and the Fourier shape coeffi- cient (FSC). The Fourier series approximation matched the particle outlines. From the statistical results of the whole sediment particle sample, as counted by WSQAM based on digital image processing, fine sediment particles with smooth surfaces accounted for approximately 80% of all of the observed sediment particles. For the majority of sediment particles, AR was greater than 0.3 and FSC was less than 0.1. When AR was greater than 0.5, FSC exponentially decayed with AR. When AR was less than 0.5, the two parameters, AR and FSC, should be combined to describe the sediment particle shape. The combined use of these two parameters can provide a reference for future sediment-related calculations. The sediment particle shape analysis model, programmed in Fortran, was rapid and flexible. It proved efficient to use WSOAM for sediment statistical analysis, and the results were found to be accurate.The shape of a sediment particle can reveal part of the particle's transportation history and is a significant variable in sediment transport mechanics. Measuring sediment shapes is a difficult and time-consuming task. A whole sample sediment particle shape quantitative analysis method (WSQAM) was applied in this research for sediment statistical analysis. The shape parameter was found using sphericity and roundness descriptors: three samples were collected from the middle reach of the Yellow River at different depths. Scanning electron microscopy (SEM) was used to obtain sediment particles images. The sphericity and roundness descriptors were represented by the particle aspect ratio (AR) and the Fourier shape coeffi- cient (FSC). The Fourier series approximation matched the particle outlines. From the statistical results of the whole sediment particle sample, as counted by WSQAM based on digital image processing, fine sediment particles with smooth surfaces accounted for approximately 80% of all of the observed sediment particles. For the majority of sediment particles, AR was greater than 0.3 and FSC was less than 0.1. When AR was greater than 0.5, FSC exponentially decayed with AR. When AR was less than 0.5, the two parameters, AR and FSC, should be combined to describe the sediment particle shape. The combined use of these two parameters can provide a reference for future sediment-related calculations. The sediment particle shape analysis model, programmed in Fortran, was rapid and flexible. It proved efficient to use WSOAM for sediment statistical analysis, and the results were found to be accurate.

关 键 词:Hydraulics Sediment transport mechanics Sediment particle shape analysis SEM image Yellow River 

分 类 号:TP317.4[自动化与计算机技术—计算机软件与理论] X131.2[自动化与计算机技术—计算机科学与技术]

 

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