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GravelSens:一种用于高分辨率、非破坏性监测堵塞动态的智能砾石传感器。

GravelSens: A Smart Gravel Sensor for High-Resolution, Non-Destructive Monitoring of Clogging Dynamics.

作者信息

Koca Kaan, Schleicher Eckhard, Bieberle André, Haun Stefan, Wieprecht Silke, Noack Markus

机构信息

Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart, 70569 Stuttgart, Germany.

Faculty of Architecture and Civil Engineering, Karlsruhe University of Applied Sciences, 76133 Karlsruhe, Germany.

出版信息

Sensors (Basel). 2025 Jan 17;25(2):536. doi: 10.3390/s25020536.

Abstract

Engineers, geomorphologists, and ecologists acknowledge the need for temporally and spatially resolved measurements of sediment clogging (also known as colmation) in permeable gravel-bed rivers due to its adverse impacts on water and habitat quality. In this paper, we present a novel method for non-destructive, real-time measurements of pore-scale sediment deposition and monitoring of clogging by using wire-mesh sensors (WMSs) embedded in spheres, forming a smart gravel bed (GravelSens). The measuring principle is based on one-by-one voltage excitation of transmitter electrodes, followed by simultaneous measurements of the resulting current by receiver electrodes at each crossing measuring pores. The currents are then linked to the conductive component of fluid impedance. The measurement performance of the developed sensor is validated by applying the Maxwell Garnett and parallel models to sensor data and comparing the results to data obtained by gamma ray computed tomography (CT). GravelSens is tested and validated under varying filling conditions of different particle sizes ranging from sand to fine gravel. The close agreement between GravelSens and CT measurements indicates the technology's applicability in sediment-water research while also suggesting its potential for other solid-liquid two-phase flows. This pore-scale measurement and visualization system offers the capability to monitor clogging and de-clogging dynamics within pore spaces up to 10,000 Hz, making it the first laboratory equipment capable of performing such in situ measurements without radiation. Thus, GravelSens is a major improvement over existing methods and holds promise for advancing the understanding of flow-sediment-ecology interactions.

摘要

工程师、地貌学家和生态学家都认识到,由于其对水质和栖息地质量的不利影响,需要对渗透性砾石河床中沉积物堵塞(也称为淤塞)进行时间和空间上的解析测量。在本文中,我们提出了一种新颖的方法,通过使用嵌入球体中的丝网传感器(WMS)进行无损实时孔隙尺度沉积物沉积测量和堵塞监测,从而形成一个智能砾石床(GravelSens)。测量原理基于对发射电极进行逐个电压激励,然后由接收电极在每个交叉测量孔隙处同时测量产生的电流。然后将电流与流体阻抗的导电分量相关联。通过将麦克斯韦·加内特模型和平行模型应用于传感器数据,并将结果与伽马射线计算机断层扫描(CT)获得的数据进行比较,验证了所开发传感器的测量性能。在从沙子到细砾石的不同粒径的不同填充条件下对GravelSens进行了测试和验证。GravelSens与CT测量结果之间的密切一致性表明了该技术在沉积物 - 水研究中的适用性,同时也暗示了其在其他固 - 液两相流中的潜力。这个孔隙尺度测量和可视化系统能够以高达10,000 Hz的频率监测孔隙空间内的堵塞和疏通动态,使其成为首个能够在无辐射情况下进行此类原位测量的实验室设备。因此,GravelSens是对现有方法的重大改进,并有望推动对水流 - 沉积物 - 生态相互作用的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b065/11768524/7e72f94ac519/sensors-25-00536-g001.jpg

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