Modeling the hydraulic roughness of a movable flatbed in a sand channel while considering the effects of water temperature

The prediction of the flow resistance (usually quantified as the hydraulic roughness) of a movable flatbed is a key issue affecting the calculation accuracy of flood levels in river training projects. Bedload motion on a movable flatbed causes additional energy loss and increases hydraulic roughness...

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Main Authors: Junzheng Liu, Jinliang Zhang, Zhe Huang, Haijue Xu, Yuchuan Bai, Gang Wang
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-02-01
Series:International Journal of Sediment Research
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Online Access:http://www.sciencedirect.com/science/article/pii/S1001627924001276
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author Junzheng Liu
Jinliang Zhang
Zhe Huang
Haijue Xu
Yuchuan Bai
Gang Wang
author_facet Junzheng Liu
Jinliang Zhang
Zhe Huang
Haijue Xu
Yuchuan Bai
Gang Wang
author_sort Junzheng Liu
collection DOAJ
description The prediction of the flow resistance (usually quantified as the hydraulic roughness) of a movable flatbed is a key issue affecting the calculation accuracy of flood levels in river training projects. Bedload motion on a movable flatbed causes additional energy loss and increases hydraulic roughness. Several theoretical and empirical predictors for characterizing this phenomenon have been proposed, but the accuracy and physical basis of these models should be improved. In this study, the total energy dissipation rate is separated into two components: the energy dissipation rate due to grain drag and the additional energy dissipation rate due to bedload motion. Following the energy dissipation rate balance equation, a new predictor was proposed for movable flatbed flows. The water temperature was empirically coupled with the fluid viscosity and its associated physical variables. A new empirical relation between two dimensionless flow‒sediment combination variables was established to demarcate the various bedform transitions induced by the water temperature. The new predictor was compared with other predictors, and the prediction results were compared to the measured data. The error metric showed that the new predictor provided the highest accuracy, with ∼88.5% of the 826 data points falling within the ±30% error band. The new predictor suggested that the additional drag is nonlinearly proportional to the grain drag, and the scale factor between these two parameters is related to five flow‒sediment variables. In addition, the ability of the new predictor to quantify water temperature effects was examined. The predicted resistance exhibited three change modes with increasing water temperature, and the results suitably agreed with the measurements. The effect of the water temperature on the resistance of a movable flatbed is jointly controlled by the suspension number and roughness Reynolds number. This study provides an effective predictor that can be used by decision makers for modeling the hydraulic roughness of a movable flatbed.
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institution Kabale University
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publishDate 2025-02-01
publisher KeAi Communications Co., Ltd.
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series International Journal of Sediment Research
spelling doaj-art-1c385d0443e1425999b4e169e5bd1ec22025-01-12T05:24:20ZengKeAi Communications Co., Ltd.International Journal of Sediment Research1001-62792025-02-014013144Modeling the hydraulic roughness of a movable flatbed in a sand channel while considering the effects of water temperatureJunzheng Liu0Jinliang Zhang1Zhe Huang2Haijue Xu3Yuchuan Bai4Gang Wang5State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300072, China; Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province, Qinhuangdao 066001, ChinaYellow River Engineering Consulting Co., Ltd., Zhengzhou 450003, China; Corresponding authors.State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300072, China; Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province, Qinhuangdao 066001, China; Corresponding authors.State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300072, China; Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province, Qinhuangdao 066001, ChinaState Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300072, China; Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province, Qinhuangdao 066001, ChinaState Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300072, China; Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province, Qinhuangdao 066001, ChinaThe prediction of the flow resistance (usually quantified as the hydraulic roughness) of a movable flatbed is a key issue affecting the calculation accuracy of flood levels in river training projects. Bedload motion on a movable flatbed causes additional energy loss and increases hydraulic roughness. Several theoretical and empirical predictors for characterizing this phenomenon have been proposed, but the accuracy and physical basis of these models should be improved. In this study, the total energy dissipation rate is separated into two components: the energy dissipation rate due to grain drag and the additional energy dissipation rate due to bedload motion. Following the energy dissipation rate balance equation, a new predictor was proposed for movable flatbed flows. The water temperature was empirically coupled with the fluid viscosity and its associated physical variables. A new empirical relation between two dimensionless flow‒sediment combination variables was established to demarcate the various bedform transitions induced by the water temperature. The new predictor was compared with other predictors, and the prediction results were compared to the measured data. The error metric showed that the new predictor provided the highest accuracy, with ∼88.5% of the 826 data points falling within the ±30% error band. The new predictor suggested that the additional drag is nonlinearly proportional to the grain drag, and the scale factor between these two parameters is related to five flow‒sediment variables. In addition, the ability of the new predictor to quantify water temperature effects was examined. The predicted resistance exhibited three change modes with increasing water temperature, and the results suitably agreed with the measurements. The effect of the water temperature on the resistance of a movable flatbed is jointly controlled by the suspension number and roughness Reynolds number. This study provides an effective predictor that can be used by decision makers for modeling the hydraulic roughness of a movable flatbed.http://www.sciencedirect.com/science/article/pii/S1001627924001276Movable flatbedHydraulic roughnessAdditional dragDrag predictorWater temperature
spellingShingle Junzheng Liu
Jinliang Zhang
Zhe Huang
Haijue Xu
Yuchuan Bai
Gang Wang
Modeling the hydraulic roughness of a movable flatbed in a sand channel while considering the effects of water temperature
International Journal of Sediment Research
Movable flatbed
Hydraulic roughness
Additional drag
Drag predictor
Water temperature
title Modeling the hydraulic roughness of a movable flatbed in a sand channel while considering the effects of water temperature
title_full Modeling the hydraulic roughness of a movable flatbed in a sand channel while considering the effects of water temperature
title_fullStr Modeling the hydraulic roughness of a movable flatbed in a sand channel while considering the effects of water temperature
title_full_unstemmed Modeling the hydraulic roughness of a movable flatbed in a sand channel while considering the effects of water temperature
title_short Modeling the hydraulic roughness of a movable flatbed in a sand channel while considering the effects of water temperature
title_sort modeling the hydraulic roughness of a movable flatbed in a sand channel while considering the effects of water temperature
topic Movable flatbed
Hydraulic roughness
Additional drag
Drag predictor
Water temperature
url http://www.sciencedirect.com/science/article/pii/S1001627924001276
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AT zhehuang modelingthehydraulicroughnessofamovableflatbedinasandchannelwhileconsideringtheeffectsofwatertemperature
AT haijuexu modelingthehydraulicroughnessofamovableflatbedinasandchannelwhileconsideringtheeffectsofwatertemperature
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