Name: image-based lagrangian particle tracking in bed-load experiments
Uploaded: 2017-07-20T15:00:00.000+00:00
Duration: 10 min 32 s
Description: Watch this Scientific Journal Video about Image-based Lagrangian Particle Tracking in Bed-load Experiments at JoVE.com

这项工作得到了研究执行机构的支持，通过欧盟第七个框架计划，支持研究人员的培训和职业发展（Marie Curie-FP7-PEOPLE-2012-ITN），资助了初步培训网络（ITN） HYTECH"生态关键异质接口中的流体动力学运输"（编号316546）。它还得到了米兰政治学院的Polo Territoriale di Lecco的支持。实验是在SS访问米兰政治学院期间进行的，作为访问科学家。作者感谢Tarcisio Fazzini，Stefania Gherbi，Francesco Mottini（米兰政治学院的学生）和Seyed Abbas Hosseini-Sadabadi（HYTECH项目的研究员和Milano Politecnico di博士生），以支持实验活动和数据分析。作者非常感谢Roger Nokes教授（新西兰基督城坎特伯雷大学）提供Streams软件和不断的建议。最后，作者感谢JoVE的总编辑和三位匿名评论家的发言人的意见和建议，感谢手稿可以大大改进。

注意:沉积物运输实验在位于米兰政治学院的莱科校区的山体液力实验室的水槽中进行。水槽被完全构造透明的丙烯酸材料制成，并且是5.2×0.3×0.45米3。通道由两个钢梁支撑，由于铰链和螺丝千斤顶，可以在不同的斜坡上操作。一系列盖子使得水槽能够充当封闭导管，这是覆盖流动配置，以及这项工作中使用的通道。 1.测量和设置水槽坡度<ol><li>密封水槽的出口并用静止水填充。 注意:密封方法将取决于通道特征。在这里提到的情况下，通道的端子部分配有联轴器法兰，因此通过在它们之间用橡胶垫圈将塑料塞螺栓连接到法兰上来获得密封。 </li><li>操作螺丝孔to设置任意通道斜率。 </li><li>等待至少30分钟让水达到静止。为了检查振荡衰减和达到静水条件，在水槽壁上放置一个测点，并反复测量自由表面的高度。 </li><li>将点测量仪放置在多个位置的通道壁上，并读取自由表面的高度。 注意:当水面为水平时，水槽倾斜，读数会相互不同。 </li><li>根据点量规对读数的线性插值计算斜率值。 </li><li>用激光距离传感器进行测量，激光距离传感器连接到支撑通道的一个光束并指向地面。 注意:这里，激光传感器永久地连接到通道，因此在其设置的协议中不需要任何操作。 </li><li>对于各种坡度条件，重复步骤1.2到1.6。 </li><li>适合线性方程到笛卡尔平面中的实验点，激光测量在水平轴上，通道斜率测量在垂直轴上。确定从激光测量到通道斜率的传递函数（反之亦然）。 </li></ol> 2.设置工作配置<ol><li>准备一套总厚度与通道底部尺寸相等的钢板（2 mm厚）。 注意:在这里，四个板块的尺寸为1.3×0.3米2被使用。 </li><li>通过将沉淀物颗粒粘在板上来创建固定的粗糙床。为此，用双组分聚酯树脂涂漆板，然后在其上铺上一层沉积物（1-1.5厘米）。 注意:这里使用的沉淀颗粒是聚对苯二甲酸丁二醇酯（PBT），白色制成，尺寸为3毫米。通过上述步骤，粘合到板上的沉淀物的厚度类似于粒度。 </li><li> w ^请至少24小时以使树脂干燥，然后通过倾斜板块并使沉淀物滑落而除去多余的沉淀物。用防水喷漆将黑色沉积物表面涂上。等待至少10小时以使油漆干燥。 </li><li>将沉积物涂层板（参见步骤2.1-2.3）放入水槽和聚氯乙烯（PVC）支撑件上，以形成工作部分的底部。注意连续板的放置，以确保床的连续性。 注意:使用PVC支架是可选的。在这种情况下，最初设计了水槽（0.3m宽，0.45m高，对应于低于1的宽度与深度比）的横截面，以便沉积物运输实验与一层松散的沉积物进行运输。该手稿中提出的实验是用固定床运行，导致宽度与深度之间的不寻常的，太低的值。因此，为了实现大的PVC使用PVC支架这个比率的r值。 </li><li>将一系列透明的丙烯酸盖（覆盖整个通道长度）放在通道壁上，以创建一个覆盖的工作部分。 注意:在这里描述的水槽中，盖子是高度为20厘米的内部盒子，只是放置在水槽壁上。因此，在实验过程中，一些水存在于盖子侧面，但不会明显地改变水槽内的流动。下面实验中使用的工作部分大小为0.3 mx 0.105 m 2 。 </li></ol> 3.建立稳定的流量条件<ol><li>打开泵，用水填充通道，并使用调节阀设定流量。 注意:在这项工作中，流量通过沿输送管放置的电磁流量计来测量。 </li><li>使用尾水调节器将压头的高程设置为高于通道盖，确保有一个覆盖的流动但避免在盖子上有显着的浮力。 注意:在此处提供的通道中，尾水调节通过位于水槽末端的一系列棒来实现。 </li><li>重复测量流量和压头以检查流量条件的稳定性。 </li></ol> 4.表征流量分布<ol><li> 测量各种位置的流速分量的垂直剖面。 <ol><li>使用适当的探头支架将超声波速度轮廓仪（UVP）的探头放在水槽盖上方。将探头放置在选定的倾斜位置，尾部朝向通道入口。在探针尖端和盖子之间的空间内应用适当的超声波耦合凝胶，以避免超声波通过空气。将探头连接到其采集模块。 注意:在目前情况下，探头支架由PVC制成，并由倾斜的底座组成指引附。在选择探头角后构建该支撑。 </li><li>采样几个瞬时速度曲线。 注意:使用本实验中使用的仪器，此步骤需要手动设置发射的超声波的频率，脉冲重复频率，分辨率和所需的瞬时曲线数。当达到所需数量时，配置文件不断获取并保存。 </li><li>重复步骤4.1.1和4.1.2，除了将探头与尾部朝向通道出口。 </li><li>评估信号解尖峰24通过流明智速度的获取的时间演变的视觉检查的需要。如有必要，在数据处理过程中执行去尖峰。 </li><li>计算UVP的每个测量位置（门）的平均速度值，以从两次测量中获得探针方向速度分量的时间平均分布（探头的尾部朝向通道入口和出口）。 </li><li>使用在任何高程处测量的两个探测速度的三角组合来获得流和垂直速度分量。 <ol><li>用v 向上和v 向下如步骤4.1.2和4.1.3测量分别，时间平均的速度，确定该流明智（u）和垂直速度（v）组件为: <img alt="公式1" src="/files/ftp_upload/55874/55874eq1.jpg" /> <img alt="公式2" src="/files/ftp_upload/55874/55874eq2.jpg" /> 其中，α是探头相对于通道的倾斜度。 </li></ol></li><li>调整轮廓中测量位置的距离值，以确定声束行进的不同介质（凝胶，丙烯酸和水） 25 。 </li><li>对于所有测量位置重复4.1.1至4.1.7的步骤。 </li></ol></li><li&gt; 从流速分量的垂直剖面测量剪切速度。 <ol><li>确定一系列高程，其中流速分量的轮廓表示半对数图中的线性趋势（ 见图2 ）。 </li><li>通过拟合如下对数方程式来估算剪切速度u s : <img alt="公式3" src="/files/ftp_upload/55874/55874eq3.jpg" /> 其中u （ z ）是在床的某个仰角z处的时间平均流速， κ是等于0.4的卡曼常数， z 0是流体动力学粗糙度长度。 </li><li>量化剪切速度26的估计中的不确定性为: <img alt="公式4" src="/files/ftp_upload/55874/55874eq4.jpg" /> 其中N是用于c的值的数量请求拟合， j是从1到N的计数器。 </li></ol></li></ol> 5.进行泥沙运输实验<ol><li> 设置所需的相机参数（分辨率，频率）。使用相机制造商的支持，将两个动作相机连接到面向通道底部的两个流动位置的盖子的侧壁上。确保两个摄像机的对焦区域重叠。 <ol><li>通过反复试验调整相机的位置和方向。如果两个对焦区域不重叠或摄像机视图与水槽不完全对准，请从每个摄像机捕获短视频，观看视频并更改摄像机的位置或方向。 注意:在本工作中，相机以30 fps的速度运行，分辨率为1,920×1080像素。 </li></ol></li><li>建立稳定的流动条件，如步骤3.1至3.3所述。喂白色颗粒（与那些t相同）帽子在步骤2.2和2.3中胶合并涂黑色）进入水槽入口处的流中。选择少量颗粒并释放它们（每隔几秒钟一个颗粒），在黑色的床上保持低浓度的白色颗粒。在实验的整个持续时间内保持喂养。 注:低颗粒浓度简化17的追踪处理相比，情况具有更高的浓度18。事实上，在与随后的图像中的相同粒子某一图像一个颗粒之间的匹配是基于周围的粒子19，27的原来位置的搜索窗口;更高的浓度增加了在搜索窗口中检测多于一个粒子的可能性，从而导致不匹配。 </li><li>如果房间灯熄灭，则需要将其打开，因为需要同步摄像机。触发相机开始拍摄与适当的控制。确保两台摄像机都开始拍摄后，请关闭房间灯。 注意:以这种方式，从图像中的像素强度的历史可以清楚地识别光被关闭的时间，从而使得（以小于一帧的精度）使得两个获取的电影之间的时间偏移待定可视化当然不能在黑暗中进行。在现在的工作中，实验只使用自然采光（由于房间的侧壁是玻璃制成的）。如果在实验过程中照明条件发生显着变化，则应重复运行，因为照明影响下面描述的粒子识别和跟踪。 </li><li>继续拍摄所需的时间（这里是15分钟），然后停止相机。 注意:代表性的结果如下所示，持续时间为100秒。 </li><li>对于任何其他所需的水力动力条件，重复步骤5.2至5.7例如，不同的流量）。 注意:在这里描述的实验中，拍摄后一些被捕获的颗粒存在于床上。在进行另一个配置测试之前，应该先拆下盖子，用刷子去除颗粒，更换盖子。 </li></ol> 6.预处理图像<ol><li>通过对像素坐标进行径向变换并重新映射图像来校正由于受限的透镜长度造成的图像失真。通过试验调整应用转换所需的校准因子。 注意:给定r作为从任何像素到图像中心的距离，转换的距离可以计算为: <img alt="公式5" src="/files/ftp_upload/55874/55874eq5.jpg" /> 其中k是需要通过试验28调整的校准因子，其基于在图像中应该显示为直线的水槽底侧的目视检查秒。 </li><li>使用放置在已知距离处和位于海拔高度的位于水槽侧壁上的目标，确定从像素到实际距离的线性图像转换。 注意:这可以在编程语言（参见材料表 ）中使用命令imread来打开图像文件，命令ginput来点击目标并获得像素中的坐标，并找到一个比例所确定的像素坐标和真实像素坐标。 </li></ol>识别和跟踪粒子注意:对于两台摄像机分别收集的图像，必须执行以下所有操作。使用Streams 29进行颗粒的识别和跟踪。该软件可以免费提供给开发人员查询。作者在几个实验室中已经使用了流二维泥沙运输在不同条件下3，16，17，18，28，30。 <ol><li>通过单击图像→创建图像序列导入框。输入两帧之间的时间步长和图像校准因子。选择要包含在序列中的图像文件。点击确定 。 注意:在当前情况下，时间间隔为1/30秒（对应于步骤5.1中提到的帧速率），图像校准系数为0.5 mm /像素。 </li><li> 识别粒子 <ol><li>为一些随机选择的图像生成强度图，以便找到对应于白色粒子的像素的典型强度值（从0到255的比例）。 <ol><li>右键单击创建的图像序列 ，然后选择Open图像视图。按住Shift键 ，在图像上绘制任何矩形。右键单击矩形并选择ShowIntensityMatrix 。选择合适的阈值。 注意:在本例中，阈值设置为80。 </li></ol></li><li>基于二值图像中的白点的强度值和预期大小来阈值图像。 <ol><li>右键单击创建的图像序列 ，然后选择打开进程视图 。单击新建 ，选择过滤器图像管道 ，然后单击确定 。给进程一个名称，提供序列名称，然后单击确定 。双击过滤器管道 ，单击新建 ，选择删除背景 ，然后单击确定 。 </li><li>在" 流程"窗口中，单击" 新建" ，选择" 识别粒子" ，然后单击" 确定" 。选择单阈值 ，然后单击确定 。在算法中 </em&gt;页面，输入阈值强度和限制光斑直径，然后单击确定 。选择创建的进程，单击添加到管道 ，然后单击执行 。 注意:这里的斑点大小为0.5至8毫米。斑点尺寸与粒径有关，但也取决于照明条件。实际上，该点对应于由粒子而不是粒子本身反射的光。 </li></ol></li></ol></li><li> 跟踪粒子 <ol><li>右键单击创建的" 粒子"记录 ，然后选择" 打开图像视图" 。 </li><li>通过单击向前和向后箭头按钮滚动框。通过将光标移动到显示的点和读取坐标上，观察连续图像之间的典型粒子位移。相应地确定适当的搜索窗口。 </li><li>右键单击创建的粒子记录 ，然后选择打开进程视图 </em&gt;。 </li><li>点击新建 ，选择PTV分析管道 ，点击OK 。给进程一个名称，然后单击确定 。双击PTV分析管道 ，单击新建 。在" 成本"页面中，选择" 距离" 。在" 优化"页面中，输入搜索窗口的流向和横向位置和维度，然后单击" 确定" 。 </li><li>选择创建的进程，单击添加到管道 ，然后执行 。 注意:粒子轨道理想地到达焦点区域的最后或最后的实验时间。类似地，它必须从焦点区域的开始处或者在初始时间开始。然而，测量的轨迹可能会意外中断，这通常是因为由于两个连续帧之间的错误的粒子匹配，由于低强度或较不频繁地在一些帧中未检测到粒子。如果轨道结束而没有到达ti的边界空间观察窗口，可以搜索重新连接的候选人;在中断之前的最后一帧结束后的一个位置选择一个。以这种方式，可以在步骤7.3.6中详细描述一个粒子的单个轨道。 </li><li>如果测量轨迹中存在中断，则使用专门用于该目的的搜索窗口，通过轨道重新连接进行修复。 <ol><li>右键单击创建的粒子记录 ，然后选择打开进程视图 。单击新建 ，选择创建拉格朗日路径字段 ，然后单击确定 。再次单击确定 。将进程添加到管道，然后单击执行 。 </li><li>右键单击创建的粒子记录 （第二个），然后选择打开进程视图 。单击新建 ，选择加入拉格朗日路径 ，然后单击确定 。在" 参数"页面中，输入搜索窗口的详细信息，c舔OK 。将进程添加到管道，然后单击执行 。 </li></ol></li><li>右键单击创建的粒子记录 （第二个），然后选择将路径保存到文本文件 。输入路径和文件名，然后单击确定 。 </li></ol></li></ol> 8.从不同的摄像机连接轨迹注意:这是一个必要的操作，以利用多个相机来扩大测量区域的大小。步骤由作者开发的图形用户界面的MatLab代码（ join_cameras.m ）执行（请参阅补充代码文件 ）。 <ol><li>浏览计算机文件夹并查找两个摄像机的跟踪文件，然后单击查找轨道属性 。 </li><li>通过对下游相机的数据应用坐标转换来使两个相机的（ x ， y ）参考一致。确定用于从两个相机的图像中可见的目标沿着两个方向转换的常数。输入所需的值，然后单击" 使参考系统统一" 。 注意:直到此为止，独立参考用于图像左下角为（0,0）的相机， x轴向右， y轴向上。这项工作中使用的坐标的平移分别是流向和横向的760.15和-1.5像素。 </li><li>确定两个数据之间的重叠区域，并在适当的文本框中输入其限制。 注意:这个工作的重叠长度在流向方向为760.15到880.11像素，并覆盖了整个通道宽度。 </li><li>从样本中删除比重叠区域的长度短的所有轨迹，以便将分析限于简单的情况（ 见图1 ）。在在相关文本框中放置一个阈值长度，然后单击" 删除"小于或等于（mm） 。 </li><li> 加入曲目 <ol><li>通过单击合并表合并来自两台摄像机的粒子轨迹数据库。在流方向和横向上输入请求的重叠公差值（这里为10 mm），然后单击加注 。 注意:单击JOIN后 ，执行以下操作。滚动轨道，直到找到在重叠区域结束的轨道。搜索候选人加入，在开始和退出重叠区域的轨道之间。如果找到候选人，则比较两个轨道在重叠区域内的时间。如果这些时间段彼此一致，则在所有可能的点计算两个轨道中的粒子坐标之间的差异。取x和y值的均方差的平方根作为电位值两颗粒子轨迹相等。如果此指标低于阈值，请加入轨道。在重叠部分中构造一个与之前的两个平均值相对应的新轨迹。重复所有这些操作，直到没有新的关节是可能的。该工作中使用的阈值在两个方向上为10mm。 </li></ol></li><li>命名结果文件，然后点击保存已加入的曲目 ， 保存加入的曲目 。 </li></ol><img alt="图1" class="xfigimg" src="/files/ftp_upload/55874/55874fig1.jpg" /> 图1.轨道交接情况来自上游相机的轨道为红色，下游相机为绿色（为简单起见，为一维表示）。垂直虚线限定重叠的标称长度。由于轨道的可能中断，结果的多样性大于预期的直接tracks（对应于前四个草图的情况），具有来自第一相机的轨道到达重叠区域，以及来自第二相机的轨道离开它。总共有13个理论上可能的情况。为了简化分析，从初步数据中排除比重叠区域的长度短的轨迹。 <a href="//ecsource.jove.com/files/ftp_upload/55874/55874fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> 9.分析沉积物运输运动学<ol><li>从包含每个运输粒子的轨迹的所获得的数据集开始，以在任何时间点获取的（ x ， y ）位置表示，对载荷粒子运动学3的描绘进行各种统计分析， 4，5，8 </suP&gt;，16，17，18。 </li></ol>

<ol>
	<li>Francis, J. R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experiments+on+the+motion+of+solitary+grains+along+the+bed+of+a+water-stream.">Experiments on the motion of solitary grains along the bed of a water-stream.</a> Proc Royal Soc London, A. 332, 443-471 (1973).</li><li>Drake, T. G., Shreve, R. L., Dietrich, W. E., Whiting, P. J., Leopold, L. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bedload+transport+of+fine+gravel+observed+by+motion-picture+photography.">Bedload transport of fine gravel observed by motion-picture photography.</a> J Fluid Mech. 192, 193-217 (1988).</li><li>Campagnol, J., Radice, A., Ballio, F., Nikora, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Particle+motion+and+diffusion+at+weak+bed+load:+accounting+for+unsteadiness+effects+of+entrainment+and+disentrainment.">Particle motion and diffusion at weak bed load: accounting for unsteadiness effects of entrainment and disentrainment.</a> J Hydraul Res. 53 (5), 633-648 (2015).</li><li>Fathel, S. L., Furbish, D. J., Schmeeckle, M. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+evidence+of+statistical+ensemble+behavior+in+bed+load+sediment+transport.">Experimental evidence of statistical ensemble behavior in bed load sediment transport.</a> J Geophys Res: Earth Surf. 120 (11), 2298-2317 (2015).</li><li>Lajeunesse, E., Malverti, L., Charru, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bedload+transport+in+turbulent+flow+at+the+grain+scale:+experiments+and+modeling.">Bedload transport in turbulent flow at the grain scale: experiments and modeling.</a> J Geophys Res: Earth Surf. 115, F04001 (2010).</li><li>Tsakiris, A. G., Papanicolaou, A. N., Lauth, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Signature+of+bedload+particle+transport+mode+in+the+acoustic+signal+of+a+geophone.">Signature of bedload particle transport mode in the acoustic signal of a geophone.</a> J Hydraul Res. 52 (2), 185-204 (2014).</li><li>Mendes, L., Antico, F., Sanches, P., Alegria, F., Aleixo, R., Ferreira, R. M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+particle+counting+system+for+calculation+of+bedload+fluxes.">A particle counting system for calculation of bedload fluxes.</a> Meas Sci Technol. 27 (12), 125305 (2016).</li><li>Heays, K. G., Friedrich, H., Melville, B. W., Nokes, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+the+dynamic+evolution+of+graded+gravel+beds+using+Particle+Tracking+Velocimetry.">Quantifying the dynamic evolution of graded gravel beds using Particle Tracking Velocimetry.</a> J Hydraul Eng. 140 (7), 04014027 (2014).</li><li>Radice, A., Malavasi, S., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Solid+transport+measurements+through+image+processing.">Solid transport measurements through image processing.</a> Exp Fluids. 41 (5), 721-734 (2006).</li><li>Radice, A., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Double-average+characteristics+of+sediment+motion+in+one-dimensional+bed+load.">Double-average characteristics of sediment motion in one-dimensional bed load.</a> Acta Geophys. 56 (3), 654-668 (2008).</li><li>Radice, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+the+Lorenz+curve+to+quantify+statistical+nonuniformity+of+sediment+transport+rate.">Use of the Lorenz curve to quantify statistical nonuniformity of sediment transport rate.</a> J Hydraul Eng. 135 (4), 320-326 (2009).</li><li>Radice, A., Ballio, F., Nikora, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+statistical+properties+of+bed+load+sediment+concentration.">On statistical properties of bed load sediment concentration.</a> Water Resou. Res. 45 (6), W06501 (2009).</li><li>Radice, A., Ballio, F., Nikora, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Statistics+and+characteristic+scales+for+bed+load+in+a+channel+flow+with+sidewall+effects.">Statistics and characteristic scales for bed load in a channel flow with sidewall effects.</a> Acta Geophys. 58 (6), 1072-1093 (2010).</li><li>Campagnol, J., Radice, A., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Scale-based+statistical+analysis+of+sediment+fluxes.">Scale-based statistical analysis of sediment fluxes.</a> Acta Geophys. 60 (6), 1744-1777 (2012).</li><li>Radice, A., Nikora, V., Campagnol, J., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Active+interactions+between+turbulence+and+bed+load:+Conceptual+picture+and+experimental+evidence.">Active interactions between turbulence and bed load: Conceptual picture and experimental evidence.</a> Water Resour Res. 49 (1), 90-99 (2013).</li><li>Campagnol, J., Radice, A., Nokes, R., Bulankina, V., Lescova, A., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lagrangian+analysis+of+bed-load+sediment+motion:+database+contribution.">Lagrangian analysis of bed-load sediment motion: database contribution.</a> J Hydraul Res. 51 (5), 589-596 (2013).</li><li>Ballio, F., Radice, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluctuations+and+time+scales+for+bed-load+sediment+motion+over+a+smooth+bed.">Fluctuations and time scales for bed-load sediment motion over a smooth bed.</a> Int J Sediment Res. 30 (4), 321-327 (2015).</li><li>Hosseini-Sadabadi, S. A., Radice, A., Ballio, F., Rowi&#324;ski, P. M., Marion, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+analysis+of+entrainment+and+deposition+rate+fluctuations+in+weak+bed+load+transport.">An analysis of entrainment and deposition rate fluctuations in weak bed load transport.</a> Hydrodynamic and mass transport at freshwater aquatic interfaces. , 333-342 (2016).</li><li>Papanicolaou, A. N., Diplas, P., Balakrishnan, M., Dancey, C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computer+vision+technique+for+tracking+bed+load+movement.">Computer vision technique for tracking bed load movement.</a> J Comput Civil Eng. 13 (2), 71-79 (1999).</li><li>Ramesh, B., Kothyari, U. C., Murugesan, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Near-bed+particle+motion+over+transitionally-rough+bed.">Near-bed particle motion over transitionally-rough bed.</a> J Hydraul Res. 49 (6), 757-765 (2011).</li><li>Amir, M., Nikora, V., Witz, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+experimental+technique+and+its+application+to+study+the+effects+of+particle+density+and+flow+submergence+on+bed+particle+saltation.">A novel experimental technique and its application to study the effects of particle density and flow submergence on bed particle saltation.</a> J Hydraul Res. 55 (1), 101-113 (2017).</li><li>Ettema, R., Garc&#236;a, M. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ice+effects+on+sediment+transport+in+rivers.">Ice effects on sediment transport in rivers.</a> Sedimentation Engineering. , 613-648 (2008).</li><li>Knack, I., Shen, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sediment+transport+in+ice-covered+channels.">Sediment transport in ice-covered channels.</a> Int J Sediment Res. 30 (1), 63-67 (2015).</li><li>Goring, D. G., Nikora, V. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Despiking+acoustic+Doppler+velocimeter+data.">Despiking acoustic Doppler velocimeter data.</a> J Hydraul Eng. 128 (1), 117-126 (2002).</li><li>Nowak, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wall+shear+stress+measurement+in+a+turbulent+pipe+flow+using+ultrasound+Doppler+velocimetry.">Wall shear stress measurement in a turbulent pipe flow using ultrasound Doppler velocimetry.</a> Exp Fluids. 33 (2), 249-255 (2002).</li><li>McCuen, R. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Microcomputer applications in statistical hydrology. , (1993).</li><li>Lloyd, P. M., Ball, D. J., Stansby, P. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unsteady+surface-velocity+field+measurement+using+particle+tracking+velocimetry.">Unsteady surface-velocity field measurement using particle tracking velocimetry.</a> J. Hydraul. Res. 33 (4), 519-534 (1995).</li><li>Radice, A., Aleixo, R., Hosseini-Sadabadi, S. A., Sarkar, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+image+grabbing+and+processing+for+measurement+of+geophysical+flows.">On image grabbing and processing for measurement of geophysical flows.</a> Proc. HydroSenSoft 2017, International Symposium and Exhibition on Hydro-Environment Sensors and Software. , (2017).</li><li>Hosseini-Sadabadi, S. A., Radice, A., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Post-processing+of+particle+tracking+data+for+phenomenological+depiction+of+weak+bed-load+sediment+transport.">Post-processing of particle tracking data for phenomenological depiction of weak bed-load sediment transport.</a> Proc. River Flow 2016. VIII Int. Conf. on Fluvial Hydraulics, St. , 780-786 (2016).</li></ol>

作者宣称他们没有竞争的经济利益。

用粒子可视化设计床载运输实验包括几个步骤，包括实验配置和硬件工具的选择，流量测量，粒子播种和可视化以及图像分析。每一步的变化都有优缺点。本手稿中提出的方案的主要特点是:（i）使用加压流和固定粗糙床，（ii）将少量具有对比色的床载粒子播种到固定床颜色，（iii）使用自然光，并且（iv）使用多个摄像机来获得彼此连接的独立轨道组。 实验方法和数据处理使得能够可靠地跟踪床载颗粒进行最终测量。覆盖的流动保证移动颗粒的最佳视觉。然而，固定床防止观察某些过程（ 例如 ，与vertica相关的过程）<html> l沉积物颗粒在活动床载荷层内的位移），从而限制了该技术对弱载荷的适用性。 仅使用100s电影获得的数据样本的大小相对较小。然而，通过延长图像获取和处理的实验持续时间，可以容易地增加样本大小。喂食有限数量的颗粒需要更长的实验时间，而不是以相当高的速率喂食;但是由于运动中颗粒的浓度较小以及使用不同的颜色，因此粒径跟踪相对简单，这两者都降低了跟踪错误的可能性，这是非常值得的。在实验中使用自然光避免了照明设备的需要;然而，缺点是良好的照明取决于天气条件。 粒子跳长度和持续时间的差价合约克"&gt;图4示出了最低值作为最常见的。跳跃长度和持续时间的最大测定值分别600毫米和7秒，都围绕，这是相比于由文献4，16，30类似的值显著较大，因为测量较长的轨迹会导致长的粒子跳跃的风险，使用两个摄像机的好处是明显的，因为单个摄像机的焦点区域长度大约为850毫米，这不会大于要测量的跳跃长度值。使用两个摄像机的测量方案，确保了工艺长度尺度与测量场的长度尺度之间的令人满意的分离，从而降低了由于实验限制而偏压现象结果的风险，同时，可以将焦点区域另外延长增加沿着水槽放置的摄像机的数量。 与本文描述的协议相比，替代过程是在粒子识别和跟踪之前创建重叠的图像。我们的协议（执行跟踪两次并链接粒子轨迹）是首选的，因为图像合并方法将使数据文件的大小翻倍，需要不可负担的内存消耗。 利用这里描述的处理算法，丢弃了比重叠区域的长度短的多个粒子轨迹，因为它们阻止了沉积轨道的完全重建。然而，120mm的阈值长度比可以获得的轨迹长度短一个数量级，因此这些数据的损失是可以接受的。此外，在图1的低8个情况下看到的轨道连接将不能使获得的轨道长度显着增加。另一方面，这些情况可能会有所帮助在检索长轨道，例如图5中可能由于轨道中断造成的情况。在类似的情况下，可以通过迭代连接操作重建长轨道。然而，重要的是要记住， 如图5所示的轨道中断与跟踪过程明显相关，而不是加入过程。 这份手稿为单一实验提供了概念验证结果，以证明所采用协议的功能。在未来的实验中，该方案将应用于一系列不同的水动力条件，以便对载重泥沙输送过程进行详细分析。 <img alt="图5" class="xfigimg" src="/files/ftp_upload/55874/55874fig5.jpg" /> 图5:中断连线情况。 </strong&gt;这里描述的协议不可能将这些轨道加入到单个轨道中。 如图1的标题和本协议的步骤8.4所述，排除比重叠区域的长度短的轨迹。这消除了短的红色和绿色轨迹;因此，剩下的很长的一个没有共同点。 <a href="//ecsource.jove.com/files/ftp_upload/55874/55874fig5large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>

由于开创性工作出现了一些几十年前1，2，河流输沙的研究中利用图像分析一直不断增加。这种技术确实证明了它的能力的物理现象3，4，5详细的分析，以比较提供高分辨率和低成本的数据。随着时间的推移，硬件和软件工具都获得了显着的改进。 沉积物运输的测量可以使用欧洲方法进行，其目标是测量泥沙流量，或拉格朗日方法，用于测量各个颗粒移动时的轨迹。图像处理提供了相比于其它方法欧拉6,7粒子跟踪独特的可能性。但是，在这些潜力的背景下，图像分析对床载沉积物运输的应用在数据样本的测量和尺寸的空间/时间支持尺度方面受到一些关键的实验限制。例如，它是难以同时实现大的空间区域，一个实验的持续时间长，且高测量频率3，4，8的适当组合，而不会影响数据的质量和数量。另外，粒子跟踪可手动进行2,4，这需要很大的人的努力，或自动3,8，与由用于分析的软件由跟踪错误的可能性。 本文提出了一种用于床载沉积物tr的实验调查方案ansport通过所使用的相机类型实现了长时间的持续时间，通过在不同位置同时使用两个摄像机来确保大视场，并且通过特殊的实验条件可靠的自动处理成为可能。实验操作的设计和加工工具是基于作者在多个研究获得的经验入选作品处理的图像的方法3，9，10，11，12，13，14，15，16输沙的详细调查，17，18。 描述了沉积物运输实验，即进行释放特性在一个固定的粗糙的床上。颗粒进料远小于保持低浓度移动颗粒的流动的输送能力，从而避免了要追踪的颗粒的拥挤。此外，输送的颗粒不是连续移动，而是观察到间歇运动。使用固定床而不是可移动的床代表与自然条件相似的损失。但是，固定床在沉积物转运实验19，20，21的假设的结果是比那些从复杂的情况与各种作用过程的更简单和说明性的下频繁使用。使用固定床显然可以防止沉积物埋藏和再现的过程。另一方面，在弱床负载的情况下，沉积物的输送发生在松散床的表层中，在这种情况下，使用固定床可能是足够的。事实上，在实验与两个条件下运行颗粒运动的特性之间的特定的比较没有提出任何显著差异3,14。最后，这里提出的实验是用加压流进行的，以确保通过透明盖子进行颗粒可视化的最佳条件。用加压流沉积物运输已经实验研究在研究原型冰覆盖的河流，显示出近床边界层和沉积物之间的相互作用是类似于开放通道流22，23的。在以下各节中，概述了所有方法，并提供了一些代表性的结果。

<table><tbody><tr><td>Laser distance sensor</td><td>METRICA</td><td>PREXISOX2</td><td>Used to measure the flume slope</td></tr><tr><td>Two-component polyester resin</td><td>Gelson</td><td>MS 65213</td><td>Used to glue sediment particles onto steel plates</td></tr><tr><td>Water-resistant spray paint</td><td>Any</td><td></td><td>Used to paint the fixed bed</td></tr><tr><td>Ultrasonic Velocity Profiler</td><td>Signal Processing</td><td>DOP 2000</td><td>Used to measure the water velocity profiles</td></tr><tr><td>Camera</td><td>Go-Pro</td><td>Hero 4 Black</td><td>Used to acquire movies of bed-load particle motion</td></tr><tr><td>Streams</td><td>University of Canterbury</td><td>2.01</td><td>Used for particle identification and tracking</td></tr><tr><td>MatLab</td><td>MathWorks</td><td>R14</td><td>Used to develop ad hoc codes for a variety of operations</td></tr><tr><td>Plexiglas</td><td></td><td></td><td>Transparent acrylic material</td></tr></tbody></table>

image-based lagrangian particle tracking in bed-load experiments

图像分析越来越多地用于测量河流，因为其能够以相对较低的成本提供详细的定量描述。该手稿描述了一种使用粒子跟踪测速（PTV）对轻载沉积物进行床载实验的应用。研究的沉积物运输条件的关键特征是存在覆盖流动和固定粗糙床，其上在水槽入口处有限数量地释放颗粒。在施加的流动条件下，单独的床载颗粒的运动是间歇性的，具有交替的运动和静止项。流动模式通过流动速度的垂直分布的声学测量来初步表征。在过程可视化期间，使用放置在水槽不同位置的两个动作摄像机获得了大视场。实验方案用chan来描述nel校准，实验实现，图像预处理，自动粒子跟踪和后处理两个相机的粒子轨迹数据。提出的概念验证结果包括粒子跳长度和持续时间的概率分布。将这项工作的成果与现有文献进行了比较，以证明该方案的有效性。

本节提供的结果用于将水槽坡度设置为零（斜率值以±0.05％精度计算）的实验。所使用的沉淀有人提出，是准球形PBT颗粒的，具有大小为d = 3毫米，密度ρP =1270千克/ m 3以下。实验以流速Q = 9.7×10 -3 m 3 / s进行，导致体积速度U = 0.31m / s。 对于使用UVP的速度测量，以81°倾角使用2 MHz探头。速度数据在20 Hz下获得250 s。代表性的速度曲线如图2所示 。它在通道轴线处和距水槽入口4.5m处被采集，其中流动被完全显影。删除与无效高程测量相关的一些值。不对称c型材由塑料盖和沉积床的不同粗糙度引起。曲线图还显示了用于估计剪切速度的轮廓的部分，得到u s = 25.9±1.3mm / s。因此，粒子雷诺数（ Re p = u s × d / v ， ν作为水的运动粘度）等于78，表明过渡粗糙的状态。 沉积物输送的可视化是用两个相机放置在距水槽入口3.5米和4.3米处。相机以30 fps的频率运行，分辨率为1,920 x 1,080像素。图像失真校正因子为k = 0.6。去除畸变后，图像校准为1像素= 0.5mm。重叠长度为760.15至880.11毫米（后者为冷杉重点区域的长度）st相机从其上游边缘）。颗粒识别的阈值强度设置为80，预期斑点大小范围为0.5至8 mm。粒子跟踪搜索窗口如下:上游1 mm，下游7 mm，横向4 mm。重新连接中断轨道的搜索窗口如下:上游1 mm，下游31 mm，沿4个后框架横向16 mm。将要连接的两个轨道之间的x和y值的均方差的平方根的阈值设置为10mm。 使用来自每个摄像机的3,000个图像的子集测量的粒子轨迹（对应于100秒的持续时间）在图3中示出 。数据库分别从上游和下游摄像头中了解到37条和34条轨道。首先提出由两个摄像机获得的轨道的重叠，然后产生完整的一组t显示机架。很明显，测量区域的中心部分的重叠是令人满意的。在最后59个轨道上获得了12个链接。最长轨道跨越的整个观察窗与约16米（530个多的粒径，15.2流动深度或5.3水槽宽度），这是非常大的，相较于其他文献的研究，其中类似的分析进行了3，4的总长度，5，8。 通过采用拉格朗日框架，粒子运动学的关键指标在这里应用于粒子跳的性质。在如本实验中的间歇式床载运输中，这些跳跃是通过休息时间分开的运动。为了检测单个粒子的完整轨迹中的跳跃，粒子运动和静止的识别是必要的初步步骤。在这项工作中，我们应用了一个标准30 ，如果其在当时的x位置大于所有先前的位置并且低于所有以下的位置，则在某一时刻考虑运动的粒子。从59个测量的粒子轨迹获得总共98跳。 图4描绘了所获得的针对跳跃长度和持续时间的累积频率分布（CFD）。 <img alt="图2" class="xfigimg" src="/files/ftp_upload/55874/55874fig2.jpg" /> 图2:测量速度曲线。 （上）流速度分量的时间平均垂直分布。 （下）通过将对数方程拟合到轮廓的下部来估计剪切速度。注意，在第一个图中使用从通道顶部开始并向下定向的垂直轴代表<html>用UVP测量结果。根据需要通过方程拟合来估计剪切速度，在第二个图中使用从通道底部和向上指向的轴。 <a href="//ecsource.jove.com/files/ftp_upload/55874/55874fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图3" class="xfigimg" src="/files/ftp_upload/55874/55874fig3.jpg" /> 图3:测量粒子轨迹的平面图。 （上）来自两台摄像机的轨道（上游摄像机以红色和下游为黑色）。 （底部）连接轨迹的样本（为了清晰度而改变颜色，而某些轨迹由较粗线突出显示）。 <a href="//ecsource.jove.com/files/ftp_upload/55874/55874fig3large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> 4"class ="xfigimg"src ="/ files / ftp_upload / 55874 / 55874fig4.jpg"/&gt; 图4:跳跃长度（上）和持续时间（底部）的累积频率分布（CFD）。在图3的每个轨道内，在每个时间点对颗粒进行标记以表示颗粒是否在该时刻运动或静止。然后从轨道中提取粒子跳，作为颗粒夹带（从静止到运动的过渡）和分离（从运动到静止的转变）之间的部分。使用获得的跳数和持续时间的样本来创建此处描述的分布。 <a href="//ecsource.jove.com/files/ftp_upload/55874/55874fig4large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> 补充代码文件: join_cameras.m <a href="http://ecsource.jove.com/files/ftp_upload/55874/join_cameras.m">请</a>点击这里下载此文件。

Watch this Scientific Journal Video about Image-based Lagrangian Particle Tracking in Bed-load Experiments at JoVE.com

Image-based Lagrangian Particle Tracking in Bed-load Experiments

手稿提出了一种用于进行床载沉积物输送实验的方案，其中移动颗粒通过图像分析进行跟踪。实验设施，运行实现和数据处理程序，以及最终的一些概念验证结果。

基于图像的拉格朗日粒子跟踪在床载荷实验

Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a ...

image-based-lagrangian-particle-tracking-in-bed-load-experiments

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Civil Engineering

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SCIENTISTS IN ACTION

8.9K 次观看.  Politecnico di Milano. 手稿提出了一种用于进行床载沉积物输送实验的方案，其中移动颗粒通过图像分析进行跟踪。实验设施，运行实现和数据处理程序，以及最终的一些概念验证结果。 

视频: Image-based Lagrangian Particle Tracking in Bed-load Experiments

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures

The behavior of confined colloidal suspensions with attractive interparticle interactions is critical to the rational design of materials for directed assembly1-3, drug delivery4, improved hydrocarbon recovery5-7, and flowable electrodes for energy storage8. Suspensions containing fluorescent colloids and non-adsorbing polymers are appealing model systems, as the ratio of the polymer radius of gyration to the particle radius&#160;and concentration of polymer control the range and strength of the interparticle attraction, respectively. By tuning the polymer properties and the volume fraction of the colloids, colloid fluids, fluids of clusters, gels, crystals, and glasses can be obtained9.&#160;Confocal microscopy, a variant of fluorescence microscopy, allows an optically transparent and fluorescent sample to be imaged with high spatial and temporal resolution in three dimensions. In this technique, a small pinhole or slit blocks the emitted fluorescent light from regions of the sample that are outside the focal volume of the microscope optical system. As a result, only a thin section of the sample in the focal plane is imaged. This technique is particularly well suited to probe the structure and dynamics in dense colloidal suspensions at the single-particle scale: the particles are large enough to be resolved using visible light and diffuse slowly enough to be captured at typical scan speeds of commercial confocal systems10. Improvements in scan speeds and analysis algorithms have also enabled quantitative confocal imaging of flowing suspensions11-16,37.&#160;In this paper, we demonstrate confocal microscopy experiments to probe the confined phase behavior and flow properties of colloid-polymer mixtures. We first prepare colloid-polymer mixtures that are density- and refractive-index matched. Next, we report a standard protocol for imaging quiescent dense colloid-polymer mixtures under varying confinement in thin wedge-shaped cells. Finally, we demonstrate a protocol for imaging colloid-polymer mixtures during microchannel flow.

Confocal microscopy is used to image quiescent and flowing colloid-polymer mixtures, which are studied as model systems for attractive suspensions. Image analysis algorithms are used to calculate structural and dynamic metrics for the colloidal particles that measure changes due to geometric confinement.

密闭静态和流动胶体聚合物混合物的共聚焦成像

The behavior of confined colloidal suspensions with attractive interparticle interactions is critical to the rational design of materials for directed ...

科研

化学

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation

Advective exchange between the pore space of sediments and the overlying water column, called hyporheic exchange in fluvial environments, drives solute transport in rivers and many important biogeochemical processes. To improve understanding of these processes through visual demonstration, we created a hyporheic flow simulation in the multi-agent computer modeling platform NetLogo. The simulation shows virtual tracer flowing through a streambed covered with two-dimensional bedforms. Sediment, flow, and bedform characteristics are used as input variables for the model. We illustrate how these simulations match experimental observations from laboratory flume experiments based on measured input parameters. Dye is injected into the flume sediments to visualize the porewater flow. For comparison virtual tracer particles are placed at the same locations in the simulation. This coupled simulation and lab experiment has been used successfully in undergraduate and graduate laboratories to directly visualize river-porewater interactions and show how physically-based flow simulations can reproduce environmental phenomena. Students took photographs of the bed through the transparent flume walls and compared them to shapes of the dye at the same times in the simulation. This resulted in very similar trends, which allowed the students to better understand both the flow patterns and the mathematical model. The simulations also allow the user to quickly visualize the impact of each input parameter by running multiple simulations. This process can also be used in research applications to illustrate basic processes, relate interfacial fluxes and porewater transport, and support quantitative process-based modeling.

This manuscript describes how to create regular bedforms in a flume, visualize flow through the bedforms, and use computer simulations to simulate the hyporheic flow. The computer simulations compare well with the experimental observations. This coupled simulation and experiment is well-suited for both research and educational purposes.

可视化潜流流通过底形用染料试验及仿真

Advective exchange between the pore space of sediments and the overlying water column, called hyporheic exchange in fluvial environments, drives solute ...

工程学

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

3D-PTV is a quantitative flow measurement technique that aims to track the Lagrangian paths of a set of particles in three dimensions using stereoscopic recording of image sequences. The basic components, features, constraints and optimization tips of a 3D-PTV topology consisting of a high-speed camera with a four-view splitter are described and discussed in this article. The technique is applied to the intermediate flow field (5 &#60;x/d &#60;25) of a circular jet at Re &#8776; 7,000. Lagrangian flow features and turbulence quantities in an Eulerian frame are estimated around ten diameters downstream of the jet origin and at various radial distances from the jet core. Lagrangian properties include trajectory, velocity and acceleration of selected particles as well as curvature of the flow path, which are obtained from the Frenet-Serret equation. Estimation of the 3D velocity and turbulence fields around the jet core axis at a cross-plane located at ten diameters downstream of the jet is compared with literature, and the power spectrum of the large-scale streamwise velocity motions is obtained at various radial distances from the jet core.

A three-dimensional particle tracking velocimetry (3D-PTV) system based on a high-speed camera with a four-view splitter is described here. The technique is applied to a jet flow from a circular pipe in the vicinity of ten diameters downstream at Reynolds number Re &#8776; 7,000.

湍流应用三维粒子跟踪测速:一喷流病例

3D-PTV is a quantitative flow measurement technique that aims to track the Lagrangian paths of a set of particles in three dimensions using stereoscopic ...

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions

Two different experimental methods for determining the threshold of particle motion as a function of geometrical properties of the bed from laminar to turbulent flow conditions are presented. For that purpose, the incipient motion of a single bead is studied on regular substrates that consist of a monolayer of fixed spheres of uniform size that are regularly arranged in triangular and quadratic symmetries. The threshold is characterized by the critical Shields number. The criterion for the onset of motion is defined as the displacement from the original equilibrium position to the neighboring one. The displacement and the mode of motion are identified with an imaging system. The laminar flow is induced using a rotational rheometer with a parallel disk configuration. The shear Reynolds number remains below 1. The turbulent flow is induced in a low-speed wind tunnel with open jet test section. The air velocity is regulated with a frequency converter on the blower fan. The velocity profile is measured with a hot wire probe connected to a hot film anemometer. The shear Reynolds number ranges between 40 and 150. The logarithmic velocity law and the modified wall law presented by Rotta are used to infer the shear velocity from the experimental data. The latter is of special interest when the mobile bead is partially exposed to the turbulent flow in the so-called hydraulically transitional flow regime. The shear stress is estimated at onset of motion. Some illustrative results showing the strong impact of the angle of repose, and the exposure of the bead to shear flow are represented in both regimes.

Two different methods for characterizing the incipient particle motion of a single bead as a function of the sediment bed geometry from laminar to turbulent flow are presented.

从层流到湍流条件下的规则基底表面初始粒子运动的可视化表征

Two different experimental methods for determining the threshold of particle motion as a function of geometrical properties of the bed from laminar to ...

Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity

Biofilms are surface-attached microbial communities that have complex structures and produce significant spatial heterogeneities. Biofilm development is strongly regulated by the surrounding flow and nutritional environment. Biofilm growth also increases the heterogeneity of the local microenvironment by generating complex flow fields and solute transport patterns. To investigate the development of heterogeneity in biofilms and interactions between biofilms and their local micro-habitat, we grew mono-species biofilms of Pseudomonas aeruginosa and dual-species biofilms of P. aeruginosa and Escherichia coli under nutritional gradients in a microfluidic flow cell. We provide detailed protocols for creating nutrient gradients within the flow cell and for growing and visualizing biofilm development under these conditions. We also present protocols for a series of optical methods to quantify spatial patterns in biofilm structure, flow distributions over biofilms, and mass transport around and within biofilm colonies. These methods support comprehensive investigations of the co-development of biofilm and habitat heterogeneity.

Biofilms have complex interactions with their surrounding environment. To comprehensively investigate biofilm-environment interactions, we present here a series of methods to create heterogeneous chemical environment for biofilm development, to quantify local flow velocity, and to analyze mass transport in and around biofilm colonies.

方法表征的共同发展生物膜和生境异质性

Biofilms are surface-attached microbial communities that have complex structures and produce significant spatial heterogeneities. Biofilm development is ...

生物工程

Generation and Control of Electrohydrodynamic Flows in Aqueous Electrolyte Solutions

To drive electrohydrodynamic (EHD) flows in aqueous solutions, the separation of cation and anion transport pathways is essential because a directed electric body force has to be induced by ionic motions in liquid. On the other hand, positive and negative charges attract each other, and electroneutrality is maintained everywhere in equilibrium conditions. Furthermore, an increase in an applied voltage has to be suppressed to avoid water electrolysis, which causes the solutions to become unstable. Usually, EHD flows can be induced in non-aqueous solutions by applying extremely high voltages, such as tens of kV, to inject electrical charges. In this study, two methods are introduced to generate EHD flows induced by electrical charge separations in aqueous solutions, where two liquid phases are separated by an ion-exchange membrane. Due to a difference in the ionic mobility in the membrane, ion concentration polarization is induced between both sides of the membrane. In this study, we demonstrate two methods. (i) The relaxation of ion concentration gradients occurs via a flow channel that penetrates an ion-exchange membrane, where the transport of the slower species in the membrane selectively becomes dominant in the flow channel. This is a driving force to generate an EHD flow in the liquid. (ii) A long waiting time for the diffusion of ions passing through the ion-exchange membrane enables the generation of an ion-dragged flow by externally applying an electric field. Ions concentrated in a flow channel of a 1 x 1 mm2 cross-section determine the direction of the liquid flow, corresponding to the electrophoretic transport pathways. In both methods, the electric voltage difference required for an EHD flow generation is drastically reduced to near 2 V by rectifying the ion transport pathways.

The rectification of ion transport pathways is an effective method to generate one-directional ion-dragged electrohydrodynamic flows. By setting an ion-exchange membrane in a flow channel, an electrically polarized condition is generated and causes a liquid flow to be driven when an electric field is externally applied.

水电解质溶液中 Electrohydrodynamic 流的产生与控制

To drive electrohydrodynamic (EHD) flows in aqueous solutions, the separation of cation and anion transport pathways is essential because a directed ...

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Numerous problems in scientific and engineering fields involve understanding the kinematics of particles in turbulent flows, such as contaminants, marine micro-organisms, and/or sediments in the ocean, or fluidized bed reactors and combustion processes in engineered systems. In order to study the effect of turbulence on the kinematics of particles in such flows, simultaneous measurements of both the flow and particle kinematics are required. Non-intrusive, optical flow measurement techniques for measuring turbulence, or for tracking particles, exist but measuring both simultaneously can be challenging due to interference between the techniques. The method presented herein provides a low cost and relatively simple method to make simultaneous measurements of the flow and particle kinematics. A cross section of the flow is measured using a particle image velocimetry (PIV) technique, which provides two components of velocity in the measurement plane. This technique utilizes a pulsed-laser for illumination of the seeded flow field that is imaged by a digital camera. The particle kinematics are simultaneously imaged using a light emitting diode (LED) line light that illuminates a planar cross section of the flow that overlaps with the PIV field-of-view (FOV). The line light is of low enough power that it does not affect the PIV measurements, but powerful enough to illuminate the larger particles of interest imaged using the high-speed camera. High-speed images that contain the laser pulses from the PIV technique are easily filtered by examining the summed intensity level of each high-speed image. By making the frame rate of the high-speed camera incommensurate with that of the PIV camera frame rate, the number of contaminated frames in the high-speed time series can be minimized. The technique is suitable for mean flows that are predominantly two-dimensional, contain particles that are at least 5 times the mean diameter of the PIV seeding tracers, and are low in concentration.

The technique described herein offers a low cost and relatively simple method to simultaneously measure particle kinematics and turbulence in flows with low particle concentrations. The turbulence is measured using particle image velocimetry (PIV), and particle kinematics are calculated from images obtained with a high-speed camera in an overlapping field-of-view.

流成像技术同时测量湍流和粒子运动学

Numerous problems in scientific and engineering fields involve understanding the kinematics of particles in turbulent flows, such as contaminants, marine ...

In Situ Mapping of the Mechanical Properties of Biofilms by Particle-tracking Microrheology

Bacterial cells are able to form surface-attached biofilm communities known as biofilms by encasing themselves in extracellular polymeric substances (EPS). The EPS serves as a physical and protective scaffold that houses the bacterial cells and consists of a variety of materials that includes proteins, exopolysaccharides and DNA. The composition of the EPS may change, which remodels the mechanic properties of the biofilm to further develop or support alternative biofilm structures, such as streamers, as a response to environmental cues. Despite this, there are little quantitative descriptions on how EPS components contribute to the mechanical properties and function of biofilms. Rheology, the study of the flow of matter, is of particular relevance to biofilms as many biofilms grow in flow conditions and are constantly exposed to shear stress. It also provides measurement and insight on the spreading of the biofilm on a surface. Here, particle-tracking microrheology is used to examine the viscoelasticity and effective crosslinking roles of different matrix components in various parts of the biofilm during development. This approach allows researchers to measure mechanic properties of biofilms at the micro-scale, which might provide useful information for controlling and engineering biofilms.

In Situ Mapping of the Mechanical Properties of Biofilms by Particle-tracking Microrheology

Particle-tracking microrheology investigates the viscoelasticity of materials. Here, the technique is used to determine the viscoelasticity, creep compliance and effective crosslinking roles of different matrix components of a bacterial biofilm. The matrix consists of polymeric substances secreted by the bacteria and its components determine biofilm structure and mechanical properties.

在生物膜的力学性能原位制图粒子追踪Microrheology

Bacterial cells are able to form surface-attached biofilm communities known as biofilms by encasing themselves in extracellular polymeric substances ...

Controlling Flow Speeds of Microtubule-Based 3D Active Fluids Using Temperature

We present a method for using temperature to tune the flow speeds of kinesin-driven, microtubule-based three-dimensional (3D) active fluids. This method allows for tuning the speeds in situ without the need to manufacture new samples to reach different desired speeds. Moreover, this method enables the dynamic control of speed. Cycling the temperature leads the fluids to flow fast and slow, periodically. This controllability is based on the Arrhenius characteristic of the kinesin-microtubule reaction, demonstrating a controlled mean flow speed range of 4&#8211;8 &#181;m/s. The presented method will open the door to the design of microfluidic devices where the flow rates in the channel are locally tunable without the need for a valve.

The goal of this protocol is to use temperature to control the flow speeds of three-dimensional active fluids. The advantage of this method not only allows for regulating flow speeds in situ but also enables dynamic control, such as periodically tuning flow speeds up and down.

使用温度控制基于微管的3D活性流体的流速

We present a method for using temperature to tune the flow speeds of kinesin-driven, microtubule-based three-dimensional (3D) active fluids. This method ...

A Protocol for Real-time 3D Single Particle Tracking

Real-time three-dimensional single particle tracking (RT-3D-SPT) has the potential to shed light on fast, 3D processes in cellular systems. Although various RT-3D-SPT methods have been put forward in recent years, tracking high speed 3D diffusing particles at low photon count rates remains a challenge. Moreover, RT-3D-SPT setups are generally complex and difficult to implement, limiting their widespread application to biological problems. This protocol presents a RT-3D-SPT system named 3D Dynamic Photon Localization Tracking (3D-DyPLoT), which can track particles with high diffusive speed (up to 20 &#181;m2/s) at low photon count rates (down to 10 kHz). 3D-DyPLoT employs a 2D electro-optic deflector (2D-EOD) and a tunable acoustic gradient (TAG) lens to drive a single focused laser spot dynamically in 3D. Combined with an optimized position estimation algorithm, 3D-DyPLoT can lock onto single particles with high tracking speed and high localization precision. Owing to the single excitation and single detection path layout, 3D-DyPLoT is robust and easy to set up. This protocol discusses how to build 3D-DyPLoT step by step. First, the optical layout is described. Next, the system is calibrated and optimized by raster scanning a 190 nm fluorescent bead with the piezoelectric nanopositioner. Finally, to demonstrate real-time 3D tracking ability, 110 nm fluorescent beads are tracked in water.

This protocol details the construction and operation of a real-time 3D single particle tracking microscope capable of tracking nanoscale fluorescent probes at high diffusive speeds and low photon count rates.

一种实时3D 单粒子跟踪协议

Real-time three-dimensional single particle tracking (RT-3D-SPT) has the potential to shed light on fast, 3D processes in cellular systems. Although ...