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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Inclusive hyper- to dilute-concentrated suspended sediment transport study using modified rouse model: parametrized power-linear coupled approach using machine learning

Kumar, S., Singh, H.P., Balaji, S., Hanmaiahgari, P.R., Pu, Jaan H. 31 July 2022 (has links)
Yes / The transfer of suspended sediment can range widely from being diluted to being hyperconcentrated, depending on the local flow and ground conditions. Using the Rouse model and the Kundu and Ghoshal (2017) model, it is possible to look at the sediment distribution for a range of hyper-concentrated and diluted flows. According to the Kundu and Ghoshal model, the sediment flow follows a linear profile for the hyper-concentrated flow regime and a power law applies for the dilute concentrated flow regime. This paper describes these models and how the Kundu and Ghoshal parameters (linear-law coefficients and power-law coefficients) are dependent on sediment flow parameters using machine-learning techniques. The machine-learning models used are XGboost Classifier, Linear Regressor (Ridge), Linear Regressor (Bayesian), K Nearest Neighbours, Decision Tree Regressor, and Support Vector Machines (Regressor). The models were implemented on Google Colab and the models have been applied to determine the relationship between every Kundu and Ghoshal parameter with each sediment flow parameter (mean concentration, Rouse number, and size parameter) for both a linear profile and a power-law profile. The models correctly calculated the suspended sediment profile for a range of flow conditions ( 0.268 𝑚𝑚𝑚𝑚 ≤ 𝑑𝑑50 ≤ 2.29 𝑚𝑚𝑚𝑚, 0.00105 𝑔𝑔 𝑚𝑚𝑚𝑚3 ≤ particle density ≤ 2.65 𝑔𝑔 𝑚𝑚𝑚𝑚3 , 0.197 𝑚𝑚𝑚𝑚 𝑠𝑠 ≤ 𝑣𝑣𝑠𝑠 ≤ 96 𝑚𝑚𝑚𝑚 𝑠𝑠 , 7.16 𝑚𝑚𝑚𝑚 𝑠𝑠 ≤ 𝑢𝑢∗ ≤ 63.3 𝑚𝑚𝑚𝑚 𝑠𝑠 , 0.00042 ≤ 𝑐𝑐̅≤ 0.54), including a range of Rouse numbers (0.0076 ≤ 𝑃𝑃 ≤ 23.5). The models showed particularly good accuracy for testing at low and extremely high concentrations for type I to III profiles.
2

Flood Suspended Sediment Transport: Combined Modelling from Dilute to Hyper-concentrated Flow

Pu, Jaan H., Wallwork, Joseph T., Khan, M.A., Pandey, M., Pourshahbaz, H., Satyanaga, A., Hanmaiahgari, P.R., Gough, Timothy D. 15 February 2021 (has links)
Yes / During flooding, the suspended sediment transport usually experiences a wide-range of dilute to hyper-concentrated suspended sediment transport depending on the local flow and ground con-ditions. This paper assesses the distribution of sediment for a variety of hyper-concentrated and dilute flows. Due to the differences between hyper-concentrated and dilute flows, a linear-power coupled model is proposed to integrate these considerations. A parameterised method combining the sediment size, Rouse number, mean concentration, and flow depth parameters has been used for modelling the sediment profile. The accuracy of the proposed model has been verified against the reported laboratory measurements and comparison with other published analytical methods. The proposed method has been shown to effectively compute the concentration profile for a wide range of suspended sediment conditions from hyper-concentrated to dilute flows. Detailed com-parisons reveal that the proposed model calculates the dilute profile with good correspondence to the measured data and other modelling results from literature. For the hyper-concentrated profile, a clear division of lower (bed-load) to upper layer (suspended-load) transport can be observed in the measured data. Using the proposed model, the transitional point from this lower to upper layer transport can be calculated precisely.

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