Development of new sensor systems for continuous bedload monitoring using a submerged load‐cell system (SLS) |
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| Authors: | Takahiro Itoh Takahiko Nagayama Rei Utsunomiya Masaharu Fujita Daizo Tsutsumi Shusuke Miyata Takahisa Mizuyama |
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| Affiliation: | 1. Research and Development Center, Nippon Koei Co., Ltd, Tsukuba, Ibaraki, Japan;2. Hokuriku Office, Nippon Koei Co., Ltd, Kanazawa, Ishikawa, Japan;3. JFE Advantech Co., Ltd, Nishinomiya, Hyogo, Japan;4. Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan;5. Hodaka Sedimentation Observatory, Disaster Prevention Research Institute, Kyoto University, Takayama, Japan;6. National Graduate Institute for Policy Studies (GRIPS), Tokyo, Japan |
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| Abstract: | It is important to evaluate bedload discharge and temporal changes of the bed surface, and bed deformation can be estimated during floods if the bedload discharge is properly evaluated in an arbitrary cross‐section. With the exception of grain size and its distribution within the bedload, bedload discharge has been measured using both direct and indirect methods. Bedload slot is a direct method but cannot be used to measure bedload during a flood because of volume limitations. Indirect methods require correlation between the signals and sediment volume measured using another method. In the present study, a small, automatically recording bedload sensor with an iron plate and a pair of load cells is developed in order to evaluate not only large particles but also sand particles as bedload. Bedload mass is calculated by integrating with respect to both the velocity of sediment particles and the averaged particle weight as measured by a pair of load cells, and, as an example, the velocity is estimated by the cross‐correlation function of weights measured by load cells. The applicability of the proposed sensor is discussed based on the results of flume tests in the laboratory (2014) and the observation flume of the Hodaka Sedimentation Observatory of Kyoto University in Japan (2015). The system was installed in the observation flume in November of 2012, and flume data were obtained using natural sediment particles. In particular, it was difficult to estimate the velocity of averaged bedload particles, and it was better to apply a cross‐correlation function in the laboratory tests. However, it appears that the previous estimation can estimate these velocities in the observation flume using a connecting tube and submerged load‐cell systems. Copyright © 2017 John Wiley & Sons, Ltd. |
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| Keywords: | bedload monitoring load cell velocity of bedload particles cross‐correlation function flume test |
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