Flow structures in dividing open channels: a review

The supply of water for human consumption starts with the abstraction of ‘raw’ water from various sources. Most of these facilities convey raw water by pumping it directly from rivers via lateral channels to nearby water treatment plants, but this is badly affected by debris and sediment clogging at the intake structures. Lateral intakes are actually special cases of river bifurcations, where the channel naturally divides into two different branches, each carrying part of the flow and sediment. Many researchers have completed studies on bifurcations/diversions to understand the behaviour of water flow and sediment transport. However, a complete understanding of the phenomenon, especially in relation to secondary flows and vortices, is lacking up to this day. In fact, if this can be overcome, it will greatly contribute to the fundamental study of hydrodynamics at asymmetric fluvial bifurcations as well as in optimal design of diversions. Thus, the distribution of water flow in both main and lateral channels requires further detailed investigation. A review of the current state of research is discussed in this paper, with the objective of identifying the grey areas and gaps specifically in the investigation of complex turbulent behaviour of flow structures in open channels with lateral diversions

Flow-3D CFD model of bifurcated open channel flow: setup and validation

Bifurcation is a morphological feature present in most of fluvial systems; where a river splits into two channels, each bearing a portion of the flow and sediments. Extensive theoretical studies of river bifurcations were performed to understand the nature of flow patterns at such diversions. Nevertheless, the complexity of the flow structure in the bifurcated channel has resulted in various constraints on physical experimentation, so computational modelling is required to investigate the phenomenon. The advantages of computational modelling compared with experimental research (e.g. simple variable control, reduced cost, optimize design condition etc.) are widely known. The great advancement of computer technologies and the exponential increase in power, memory storage and affordability of high-speed machines in the early 20th century led to evolution and wide application of numerical fluid flow simulations, generally referred to as Computational Fluid Dynamics {CFD). In this study, the open-channel flume with a lateral channel established by Momplot et al (2017) is modelled in Flow-3D. The original investigation on divided flow of equal widths as simulated in ANSYS Fluent and validated with velocity measurements

Measurement of Riverbank Erosion Rates of Pusu River Using Erosion Pins Method

Riverbank erosion is a major concern in all parts of the world due to its extensive impacts geomorphologically and economically. This study aims to quantify the rates of riverbank erosion of Pusu River using erosion pins method. Two sections of the river were selected namely site A and site B where site A is a straight section while site B is situated on the outside bend. 21 pins were installed at each site in a grid pattern. Measurement of erosion pins exposure were taken from February 2019 to April 2019. Field observation were made to identify the possible factors influencing the bank erosion. The average rates of bank erosion ranged between 0.05 cm/day to 0.21 cm/day at site A and 0.09 cm/day to 0.51 cm/day at site B. Bank failure occurred at site B towards the end of measurement period due to high flow after heavy rainfall event. Field observations suggest that rates of riverbank erosion were influenced by several factors such as the flow velocity and vegetative cover of the bank

Calculation of proper time of concentration for drainage design in construction projects for urban development

The design and construction of a proper drainage system are important for any urban development project, small or big. Hydrological and hydraulic calculations are used to design the drainage systems. The calculation of peak flow is one of the common hydrological methods applied to determine the drain sizes for all construction projects. Peak flows and hydrographs can be calculated using several techniques. In order to calculate the peak flow, the design rainfall duration has to be appropriate, which will reflect the critical storm duration. The critical storm duration, on the other hand, depends on the time of concentration (tc) of the catchment. However, most of the equations for tc available in the literature are empirical. At least 23 equations could be traced in various references, which consist of different geophysical and other hydrological parameters. This paper is intended to explain the importance of the proper use of tc to calculate peak runoff flow for construction projects, as accurately as possible. A review of the existing methods used to calculate the time of concentration revealed inconsistencies among a few methods found in the literature. The correct value of the time of concentration (tc) is important for the application of the Rational Method, as the value of tc helps the designer assume the storm duration critical to get the maximum peak flow value. If the critical storm duration is not used in the Rational Method, the drain will be undersized, and the overflow of the storm runoff may happen. Therefore, ample attention should be given to the calculation of the time of concentration to ensure the safety, economy, and sustainability of the drainage system in any development project

Voltage Instability and Voltage Regulating Distribution Transformer Assessment Under Renewable Energy Penetration For Low Voltage Distribution System

The Voltage Regulating Distribution Transformer (VRDT) is a tap-changing transformer that regulates the voltage across all three phases. However, its application in the context of renewable energy penetration into low-voltage grids remains understudied. This paper addresses this research gap by presenting a refined voltage drop model tailored for the International Islamic University Malaysia (IIUM) distribution network. Based on a derived mathematical equation, the model is validated and analyzed using Simulink's modeling platform. Simulations are performed without and with the VRDT, revealing that renewable energy penetration can cause instability, leading to voltage deviations proportional to the injected renewable energy. Incorporating the VRDT in the low-voltage grid allows for voltage adjustment under loaded conditions, ensuring uninterrupted renewable energy injection. Voltage stability analysis is conducted using actual load consumption data from the IIUM network for 2020 and 2021, offering valuable insights despite assuming equal energy consumption across buildings. Most hostels exhibit stable distribution systems with solar energy, but instability arises when solar energy comprises 100% of the input for the Safiyyah and Zubair hostels' 11kV distribution transformers. Implementing the VRDT regulates this instability, restoring system stability. This study highlights the importance of VRDT integration in high renewable energy proportion low-voltage grids, enabling voltage regulation and stability under variable renewable energy injection scenarios. The findings demonstrate that VRDTs mitigate voltage instability caused by renewable energy, providing a reliable solution for incorporating renewables into low-voltage distribution networks. It contributes to understanding renewable energy's impact on distribution system stability and offers guidance for VRDT implementation in similar contexts.

Jet Erosion Device (JEd) – measurement of soil erodibility coefficients

Erosion from riverbank is most properly represented by the erodibility factor. One of the methods that can be used for in situ soil erodibility testing is the submerged jet test called Jet Erosion Test (JET). In this study, a newly modified version of the JET device namely Jet Erosion Device (JEd) is fabricated, with improved features and design that facilitates testing in the field and the laboratory. Analysis and calibration of the JEd tests were conducted to check on the reliability and performance of the Jet Erosion Device (JEd). Some preliminary results were shown to give some insights on the capabilities of the JEd. An evaluation of the erosion performance index i.e. jet index was performed to characterize the erosion resistance. The estimation of erodibility coefficients were made using the results of jet index obtained

Sediment load analysis in Lake Chini

This study is significant to be conducted to reduce the physical impacts of human activities such as water quality deterioration and destabilization of the stream bed and banks. The mining activity near Jemberau River can destabilize channel form, which may result in sedimentation at the downstream area. The rate of sediment discharge and the rate of water quality deterioration are expected to increase near the mining area close to Jemberau River. Bedload and suspended load sampling were carried out in the dry and wet months from September to December 2016. High suspended solid concentrations (SSC) were recorded in Chini and Jemberau Rivers especially during the wet months. Total Maximum Daily Load (TMDL) estimation for 5, 10, 15 and 20 years are also given

Importance of time of concentration in run off peak flow estimation

Various methods and equations are used for hydrological calculations. Calculation of hydrograph peak flow is one of the common uses of such methods or equations. Peak flows and hydrographs can be calculated using several techniques. The manual calculation is one of the common ways to determine the peak flows for drainage design and river capacity of small catchments with a simple drainage network. In order to calculate the peak flow, the design rainfall duration has to be appropriate; which will reflect the critical storm duration. The critical storm duration on the other hand depends on the time of concentration (tc) of the catchment. However, most of the equations for tc available in the literature are empirical. At least 23 equations could be traced in various references, which consist of different geophysical and other hydrological parameters. This paper is intended to explain the importance of the proper use of tc to calculate peak runoff flow as accurately as possible. A review of the existing methods revealed inconsistencies among a few methods found in the literature. The correct value of the time of concentration (tc) is important for the application of the Rational Method, as the value of tc helps the designer to assume the storm duration critical to get the maximum peak flow value

Predicting subgrade resistance value of hydrated lime-activated rice husk ash-treated expansive soil: a comparison between M5P, support vector machine, and gaussian process regression algorithms

Resistance value (R-value) is one of the basic subgrade stiffness characterizations that express a material’s resistance to deformation. In this paper, artificial intelligence (AI)-based models—especially M5P, support vector machine (SVM), and Gaussian process regression (GPR) algorithms—are built for R-value evaluation that meets the high precision and rapidity requirements in highway engineering. The dataset of this study comprises seven parameters: hydrated lime-activated rice husk ash, liquid limit, plastic limit, plasticity index, optimum moisture content, and maximum dry density. The available data are divided into three parts: training set (70%), test set (15%), and validation set (15%). The output (i.e., R-value) of the developed models is evaluated using the performance measures coefficient of determination (R2), mean absolute error (MAE), relative squared error (RSE), root mean square error (RMSE), relative root mean square error (RRMSE), performance indicator (ρ), and visual framework (Taylor diagram). GPR is concluded to be the best performing model (R2, MAE, RSE, RMSE, RRMSE, and ρ equal to 0.9996, 0.0258, 0.0032, 0.0012, 0.0012, and 0.0006, respectively, in the validation phase), very closely followed by SVM, and M5P. The application used for the aforementioned approaches for predicting the R-value is also compared with the recently developed artificial neural network model in the literature. The analysis of performance measures for the R-value dataset demonstrates that all the AI-based models achieved comparatively better and reliable results and thus should be encouraged in further research. Sensitivity analysis suggests that all the input parameters have a significant influence on the output, with maximum dry density being the highest