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

IF 3.5 3区 综合性期刊 Q2 CHEMISTRY, ANALYTICAL Sensors Pub Date : 2025-01-17 DOI:10.3390/s25020536
Kaan Koca, Eckhard Schleicher, André Bieberle, Stefan Haun, Silke Wieprecht, Markus Noack
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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.

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GravelSens:用于高分辨率、无损监测堵塞动态的智能砾石传感器。
工程师、地形学家和生态学家都认识到,由于渗透砾石河床对水和栖息地质量的不利影响,需要对沉积物堵塞(也称为淤积)进行时间和空间分辨率的测量。在本文中,我们提出了一种无损的、实时测量孔隙尺度沉积物沉积和监测堵塞的新方法,该方法使用嵌入在球体中的金属丝网传感器(WMSs),形成智能砾石床(GravelSens)。测量原理是基于发射电极的一个接一个电压激励,然后由接收电极在每个交叉测量孔处同时测量产生的电流。然后将电流连接到流体阻抗的导电部分。通过将Maxwell Garnett模型和并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。GravelSens在不同的填充条件下进行了测试和验证,不同的颗粒尺寸从沙子到细砾石。GravelSens和CT测量结果之间的密切一致表明,该技术在沉积物水研究中的适用性,同时也表明了它在其他固液两相流中的潜力。这种孔隙尺度测量和可视化系统能够监测孔隙空间内高达10,000 Hz的堵塞和解封动态,使其成为第一种能够在无辐射的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,并有望促进对流动-沉积物-生态相互作用的理解。
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来源期刊
Sensors
Sensors 工程技术-电化学
CiteScore
7.30
自引率
12.80%
发文量
8430
审稿时长
1.7 months
期刊介绍: Sensors (ISSN 1424-8220) provides an advanced forum for the science and technology of sensors and biosensors. It publishes reviews (including comprehensive reviews on the complete sensors products), regular research papers and short notes. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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