涟漪
风洞
地质学
河床
夹带(生物音乐学)
粒子(生态学)
波纹标记
波峰
风积作用
纹理(宇宙学)
粒径
矿物学
地貌学
材料科学
机械
几何学
光学
物理
泥沙输移
古生物学
声学
海洋学
量子力学
电压
沉积物
人工智能
节奏
计算机科学
图像(数学)
数学
作者
Cheryl McKenna Neuman,ottO Bédard
摘要
Abstract This paper reports on a wind tunnel investigation of particle segregation, ripple formation and surface armouring within sand beds of systematically varied particle size distribution, from coarsely skewed to bimodal. By design, the system was closed with no external inputs of mass from an external particle feed. Particles too coarse to travel in saltation for the given range in wind speed were dyed red in order to distinguish them in optical images from finer sand particles, which could be entrained into the unidirectional airflow. A 3D laser scanner measured the changing bed topography at regular time intervals during 18 experiments involving varied combinations of wind speed and bed texture. Image classification techniques were used to investigate the coincident self‐organization of the two populations of particles, as distinguished by their colour. As soon as saltation commenced, some of the red particles segregated into thin discontinuous patches. Particle trapping and sheltering on these rough patches was strongly favoured, causing them to grow preferentially. During the earliest stages of formation, bedform growth coincided with: (i) rapid coarsening of the surface texture; and (ii) the merging of proto‐ripple ‘crests’ to generate larger rhythmic bedforms of lower frequency. Consistent with previous work, ripple size was observed to increase under stronger winds when not exceeding the threshold for entrainment of the coarse‐mode or red particles from the crest. With declining rates of mass transport and particle segregation as the bed surface armoured, and the consequent deceleration of ripple propagation through to the end of each experiment, all surfaces eventually attained a steady‐state morphometry. At saturation, the largest ripples developed on beds having the lowest initial concentration of red particles. Copyright © 2016 John Wiley & Sons, Ltd.
科研通智能强力驱动
Strongly Powered by AbleSci AI