Abstract

Submarine channel slope stability is a key factor in marine traffic safety. Channel slope instability and collapse may change the geometry of a channel, block ports, and lead to marine traffic accidents. In this study, fractal and multifractal analyses are performed on sub-bottom profile images obtained before, during and after episodes of slope instability and collapse in sediments obtained from a muddy submarine channel. Results show that sub-bottom profiles exhibit distinctive fractal properties, and that changes in sub-bottom profiles are reflected by changes in fractal dimensions. For example, fractal dimensions are highest during slope collapse. During episodes of slope instability and collapse, fractal dimensions of temporal domain sub-bottom profile images exhibit distinct variations at different depths along the slope. Meanwhile, the fractal dimensions of vertical spatial domain sub-bottom profile images reveal that the slope experiences multiple fluctuating changes during collapse. Multifractal spectrum parameters highlight image non-uniformity. For example, spectrum width temporarily increases during slope instability and collapse. Results of this study suggest that the fractal dimensions and multifractal parameters of sub-bottom profiles are sensitive to channel slope instability and collapse, thereby providing useful indicators with high potential for use in slope collapse prediction and early warning systems.

摘要

海底航道边坡稳定性是海上交通安全的关键因素。航道边坡不稳定和坍塌可能会改变航道的几何形状，阻塞港口，并导致海上交通事故。在这项研究中，分形和多重分形分析是在从泥泞的海底通道获得的沉积物斜坡失稳和塌陷之前、期间和之后获得的亚底剖面图像上进行的。结果表明，亚底剖面表现出独特的分形特性，亚底剖面的变化反映在分形维数的变化上。例如，分形维数在斜坡崩塌期间最高。在边坡不稳定和塌陷期间，时域亚底剖面图像的分形维数在沿边坡的不同深度表现出明显的变化。同时，垂直空间域亚底剖面图像的分形维数揭示了斜坡在坍塌过程中经历了多次波动变化。多重分形光谱参数突出了图像的不均匀性。例如，在斜坡不稳定和塌陷期间，谱宽会暂时增加。本研究结果表明，亚底剖面的分形维数和多重分形参数对河道边坡失稳和崩塌敏感，从而为边坡崩塌预测和预警系统提供了极具潜力的有用指标。在边坡不稳定和塌陷过程中谱宽会暂时增加。本研究结果表明，亚底剖面的分形维数和多重分形参数对河道边坡失稳和崩塌敏感，从而为边坡崩塌预测和预警系统提供了极具潜力的有用指标。在边坡不稳定和塌陷过程中谱宽会暂时增加。本研究结果表明，亚底剖面的分形维数和多重分形参数对河道边坡失稳和崩塌敏感，从而为边坡崩塌预测和预警系统提供了极具潜力的有用指标。