Types Of Flow Regimes Research Articles

Microfluidic study of effect of dispersed phase viscosity and continuous phase viscosity on emulsification in a cross-junction chip

Immiscible flow of oil phase and displacing phase with surfactant can cause emulsification during the oil development. However, it is still unclear how the viscosity of each phase influences the emulsification at the micro level. In this study, we investigated the flow regimes and emulsification of two immiscible fluids in a cross-junction device by using an oil-surfactant system and an oil-surfactant/polymer system. Based on the experimental data, we analyzed the flow regimes and draw flow regime maps of the two systems. Moreover, we established the new scaling laws that include the capillary number, the flow rate ratio, and the viscosity ratio of two phases to predict the droplet diameter or slug length. The findings indicated that there are four flow regimes in the oil-surfactant system, including threading, squeezing, dripping, and jetting regimes. Besides, a new type of flow regime, irregular dripping regime, appears in the oil-surfactant/polymer system. According to the regime maps, the area of dripping regime decreases with the increase of the viscosity of dispersed phase or continuous phase. For both systems, the regression equations with the viscosity ratio have better fitting effect than those without the viscosity ratio. Meanwhile, compared with the effect of viscosity ratio of two phases, the flow rate ratio of two phases has higher influence on droplet diameter and slug length. The experiments present detailed emulsification processes at pore scale and provide new insights for the prediction of emulsion droplets and slugs.

Numerical study of flow past two square cylinders with horizontal detached control rod through passive control method

A two dimensional (2-D) numerical study is conducted through the lattice Boltzmann method for flow past two square cylinders with a detached control rod placed in the horizontal position of the channel. The range of Reynolds number (Re) is fixed at Re = 150, with the length (l) of the control rod varying from l = 0.1d–21d. First, we check the accuracy of grid points and the validity of the code for present problems by comparing the results with already available data in the literature. After that, we discussed the obtained results in terms of vorticity contour, drag and lift coefficients, and force statistics. In our study of flow structure mechanisms, we examined four types of flow regimes: a small length control rod, a small and moderate length control rod, a moderate length control rod, and a larger length control rod according to flow behavior. In force statistics, we calculated the values of CDmean, CDrms, CLrms, CDamp, CLamp, and St, respectively. The mean drag coefficient contains the smallest values at the largest length, i.e., l = 19 and 21d. The maximum value of CDmean is examined at the first cylinder (C1) as compared to the second cylinder (C2) at l = 2.25d, and it is 1.2789. The values of CDmean for C2 at the length of the control rod, l = 0.1d–1.25d, and at l = 21d are negative due to the effect of thrust. The value of the Strouhal number is the same for both cylinders C1 and C2, and its highest value is 0.1036. The pressure amplitude of the drag coefficient is maximum for C1, while the pressure amplitude of the lift coefficient is maximum for C2, and its value is 2.1569.

A computational study on transition mechanism of dripping to jetting flow in a flow‐focusing geometry

Abstract2D simulations have been performed to investigate flow regimes in a flow‐focusing geometry by changing the dispersed phase and continuous phase velocities. The dispersed phase is polydimethylsiloxane (PDMS), and the continuous phase is water. Simulations have been performed in a range of oil–water viscosity ratio from 3 to 50, and interfacial tension ranges from 0.0118 to 0.002 N/m. The walls of the microchannel are considered to be poly(methyl methacrylate) (PMMA) surfaces. The contact angle (θ) of an oil droplet in the presence of water wetting the PMMA surface is 140°. Our study observed two types of flow regimes, namely dripping and jetting, by changing the dispersed phase and continuous phase velocities. The sequential time steps of void fraction contour have been presented to explore the droplet formation mechanism. The droplet pinch‐off time and jet growth time have been calculated for the dripping and jetting regime, respectively. The outcomes are summarized in the form of a flow pattern map at a viscosity ratio of 12 and interfacial tension of 0.0118 N/m, which shows the transition boundary between dripping and jetting phenomena. The simulated transition boundary agrees well with the analytical solution available in the literature. The effect of oil–water viscosity ratio and interfacial tension on droplet size is also investigated. These findings will help understand different flow regimes and their transition in a flow focusing geometry and will directly apply to microfluidic platform‐based devices.

Blade aerodynamic model for thick airfoils of the series NACA00xx in pre-stall conditions

Blade aerodynamic modeling is needed for design, control, and aeroelastic studies of wind turbines. The ultimate aim of this study is to establish a blade aerodynamic model with well-quantified accuracy for thick airfoils, predominant in wind turbine blades. The study is limited to pre-stall conditions, involving only attached and trailing-edge separated flows. The account of dynamic stall will be considered in further studies. The analysis of the Glasgow University database on the family of symmetrical airfoils NACA 00xx (xx = 12,…,30) has been made by considering particularly the 2D spatiotemporal contours of the surface pressure coefficients on the suction side. Such contours provide a clear visualization of flow regime type (attached, separated or stalled) and, therefore, allow the selection of oscillatory test cases in attached or trailing-edge separated flows. The aerodynamic model of the normal force coefficient is established by improving the Beddoes–Leishman BL model. An important modification is carried on the calculation of the delayed angle of attack using the Goman–Khrabrov model, instead of the complex original procedure. There is a new aerodynamic component for simulating the trailing-edge separation. The present model, although limited to pre-stall conditions, involves ten parameters for the unsteady aerodynamic behavior. They can be obtained with the global optimization of the deviations between experimental results and model predictions. Previous optimization studies of the parameters of the BL model involve all flow regimes for test cases and do not lead to conclusive results. The parameter values obtained in the present study show a coherent and physics-expected variation with airfoil thickness that is not negligible.

Hydrochemical and hydrodynamic study to explore the origin of water in a volcanic aquifer

Abstract The current research aimed to determine the origin of ions and the type of flow system in groundwater flowing out through two types of atmospheric and hydrothermal springs by hydrochemical and hydrodynamic approaches in a volcanic aquifer. Findings revealed that the major ion types in atmospheric waters are calcic and magnesium bicarbonate, whereas hydrothermal springs predominantly indicated chloride–sodic composition, showing an evolving pattern resulting from hydrothermal and atmospheric waters mixing. Investigating the ionic ratios and the saturation index to determine the origin of ions suggests that the presence of ions in the waters can be attributed to the weathering of silicates and plagioclase-bearing minerals in the volcanic units, and in some cases, ionic exchange also plays a role. The recession curve analysis revealed a predominant conduit flow with α = 0.144 in the system feeding the representative hydrothermal spring. Two micro-regimes with α1 = 0 = 0.46 and α2 = 2.68 were detected on the hydrograph of the atmospheric representative spring, indicating the development of systems with two types of flow regimes. Estimating the Qmax/Qmin ratio for selected hydrothermal and atmospheric springs as 2.3 and 36.8, respectively, and calculating the electrical conductivity coefficient as 11% and 18% respectively, confirmed the recession curve analysis result.

Flow-induced vibrations of ten tandem cylinders at low Reynolds number

Flow-induced vibrations of ten cylinders in tandem arrangement are numerically investigated by using the immersed boundary method with a low Reynolds number (Re = 100). Seven spacing ratios L/D (where L = center–center spacing between tandem cylinders and D = diameter of the cylinder) are selected from 1.1 to 4.0, and the reduced velocity Ur ranges from 2.0 to 13.5 with an increment of 0.5. Small (L/D < 2.0) and large (L/D > 2.0) spacing ranges are identified, both including two types of responses: wake-induced vibration (WIV; Ur = 2.0–9.0∼10.5 for a small L/D and Ur = 2.0–6.0∼6.5 for a large L/D) and wake-induced galloping (WIG; Ur > 9.0∼10.5 for a small L/D and Ur > 6.0∼6.5 for a large L/D). The largest vibration amplitude of each cylinder is obtained in the WIG region for the small L/D condition. The presence of downstream cylinders suppresses the vortex shedding of upstream cylinders and thus postpones the vibration of upstream cylinders at a small Ur, whereas the downstream cylinder enhances the vibration at a larger Ur due to the wake interference. For a small L/D, three flow regimes with the extended-body, reattachment, and co-shedding patterns are successively presented as Ur increases. For a large L/D, four types of flow regimes, namely, EB-2S (the extended-body with “2S” pattern), RT-2S (the reattachment with “2S” pattern), TR-2S (two-row vortex street with “2S” pattern), and CS-VS (co-shedding with variation shedding), are classified. Two new vortex shedding patterns, “2G (two counter-rotating vortices shed from each side per vibration cycle)” and “2C (two co-rotating vortices shed from each side per vibration cycle),” have been identified. In the WIV region, there is only one dominant vibration frequency for upstream cylinders (C1–C7), while a sub-harmonic frequency emerges and dominates C8–C10 when L/D is large. The fluctuating lift force spectra show a broad-band frequency distribution due to the irregular positions of the vortex generation and merging, and the dominant frequency in the WIG region decreases consecutively from C1 to C10.

Investigating pressure changes at the bottom of the stilling basin after the stepped spillway using a numerical model

Stepped spillways are hydraulic components of dams used to dissipate energy downstream of the dams. Numerous studies have been conducted to understand the hydraulics of flow on stepped spillways, primarily in laboratory settings. The flow passing over stepped spillways can be categorized into two types of flow regimes: Nappe Flow and non-Nappe Flow. In this research, the FLOW-3D software was utilized to model the Cardan configuration of the downstream basin of the stepped overflow based on laboratory data. In this investigation, we compared the distribution profile of maximum, minimum, and average pressures in three areas: the center, right, and left, with the laboratory data in the numerical model using graphical methods and statistical indicators. The results revealed that 08% of the pressures obtained from the model closely matched the laboratory data with an error rate of only 5.1%.

Effects of operating parameters on residence time distribution in a REFLUX flotation cell

Residence time distribution (RTD) is a critical parameter in design and optimization of flotation processes and machines. RTD measurements provide valuable indication into the distribution of residence times experienced by particulates (e.g., particles, oil droplets) within the system, enabling the identification of flow regimes and potential issues such as short-circuiting, dead zones or inadequate mixing. While previous studies in the literature have generally focused on RTD measurements in mechanical flotation cells, there are limited experimental studies available for pneumatic flotation cells. In this study, RTD measurements were performed to characterize the type of flow regime in the REFLUXTM Flotation Cell (RFC), and to investigate the impacts of operational parameters, including bias, feed flux, and gas flux, using a laboratory-scale RFC-100. An impulse-response methodology was employed with a KCl solution used as a tracer in a two-phase (liquid–gas) system. Large and Small Tanks in Series (LSTS), N-mixer in Series, and Perfect Mixer models were applied to a database created by experimental results. The results revealed that the fluid behavior in RFC-100 approached a plug-flow pattern rather than perfect mixing in the two-phase (liquid–gas) system. Furthermore, an increase in bias resulted in a decrease in mean residence time (MRT), and the tracer concentration inside the cell could be adjusted by varying the gas flux under the same feed flux.

Focused Reservoir Fluid Sampling Uses Artificial Intelligence Technology

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 210091, “Optimizing Focused Reservoir Fluid Sampling Using a Deterministic Causation Artificial Intelligence Intuition Technology,” by Rabindra Chakraborty, Senslytics; Chengli Dong, Shell; and Hani Elshahawi, SPE, NoviDigiTech, et al. The paper has not been peer reviewed. _ Samples collected using wireline formation testing (WFT) provide vital information throughout the lifetime of a reservoir. Contaminated samples can lead to erroneous fluid analysis results with potentially huge economic consequences. A need exists for an application that can assist engineers in accurately inferring the state of fluid contamination. The complete paper describes the development of a WFT contamination-forewarning application based on a framework that advises real-time decisions regarding the state of fluid contamination and recommending changes that will help optimize the WFT operation. Focused Fluid Sampling During the past decade, focused fluid sampling has emerged as a viable alternative to conventional formation-fluid sampling. The method uses a special probing tool containing two distinct flow areas. The central (sample) inlet is connected to a sample line, often with an associated pump, while the peripheral (guard) ring is also associated with a dedicated pump. Focused sampling usually results in faster cleanup but comes with increased operational complexity. The flow rate of the sample and guard lines must be properly adjusted and synchronized for each case at hand, and the interpretation of downhole measurements on both sides is significantly more complex than for conventional sampling operations. The success of fluid-sampling operations is highly dependent on human interpretations of the real-time downhole sensor data. Focused sampling is carried out by manipulating the differential rates of sample and guard pumps to stimulate and accelerate sample cleanup. Various types of flow regimes observed during focused sampling operations may be classified as follows: - Idle: During such regimes, both sample and guard pumps are turned off. Thus, no cleanup takes place, and fluids in the tool’s sample lines that are detected by the downhole analyzers remain stagnant. - Commingled: During commingling, either the sample pump or the guard pump is running, but flow occurs through both the sample and guard areas combined. - Split flow: In such periods, both sample and guard pumps run simultaneously but at different flow rates, with fluids moving at different speeds through the sample (central) and guard (outer) areas. The physics of fluid flow in near-wellbore porous media are highly complex and challenging to compute analytically and difficult to numerically simulate at a relevant scale, especially in the context of real-time operations. The authors have developed what they term “intuition technology,” an artificial-intelligence paradigm that uses scientific learning as its fabric and mimics the human decision-making process by iterating hypotheses and weighing situational changes surrounding dynamics simultaneously while keeping an eye on possible asymptomatic behavior. The process involves harnessing experts’ subtle knowledge of fluid properties and change behavior as hypotheses and iterating them with the situational and time-series data to generate a scientific fabric that governs the cleanup. A contamination-forewarning application built on this intuition framework was able to interpret the fluid-cleanup state successfully in all examples examined as part of this pilot.

Hydrodynamic feature extraction and intelligent identification of flow regimes in vaneless space of a pump turbine using improved empirical wavelet transform and Bayesian optimized convolutional neural network

Hydrodynamic feature extraction of pressure pulsation signals (PPSs) and intelligent identification of flow regimes in vaneless space (VAS) of a pump turbine (PT) are crucial to the safe and stable operations of the pumped storage power station. In this work, the scheme based on an improved empirical wavelet transform (IEWT), energy feature vector (EFV) and Bayesian optimized convolutional neural network (BOCNN) is innovatively proposed. Firstly, the IEWT is proposed by introducing the least square method and mathematical morphology to improve the decomposition shortcomings of existing methods. The phenomenon of mode aliasing is eliminated and the influence of background noise is greatly reduced, as verified by both simulated and measured PPSs. Secondly, based on the IEWT, several significant mode components are obtained, and the energy feature indexes of them are calculated to extract the hydrodynamic feature information and construct the EFVs that can accurately reflect the features of different flow regimes in the VAS. Then, the BO algorithm is adopted to optimize the important hyperparameters of CNN, and the intelligent identification model of BOCNN is constructed and trained to identify four typical types of flow regimes in the VAS. Finally, the average identification accuracy of the proposed IEWT-EFV-BOCNN scheme can reach 99.15%, which is much higher than traditional schemes, illustrating that the proposed scheme has significant engineering application value.

Experimental Study of Flow Regimes of Stepped Weir


 Depending on the discharge and the stepped weir's dimensions, flow over a stepped weir can be primarily divided into three different flow regimes: nappe, transition, and skimming. The different properties for each flow regime make the decision of the flow regime an important component in the design of a stepped weir. Five stepped weir models have been used in experiments to determine the flow regime limits for these weirs. The models were made with various numbers of steps (3, 5, 7, 10, and 14) and downstream slope angle of 30˚. The configurations of steps that tested were flat step, fully pooled step, and zig zag pooled step . The results showed the end sills have a large impact on the type of flow regime. Based on the experimental data for flow regimes (nappe flow , transition flow and skimming flow ), a new set of empirical equations was proposed, with a determination coefficient〖 R〗^2 for these regimes (0.87, 0.71 ,0.7 ) respectively.
 
 

A review of frictional pressure drop characteristics of single phase microchannels having different shapes of cross sections

Abstract This paper theoretically studied pressure drop variation in microchannels having different cross sections (circular, rectangular, square, trapezoidal, triangular, elliptical, parallel plate, co-centric circles, hexagonal, wavy, smoothed or rounded corners cross sections, and rhombus) for single phase Newtonian fluid (gas and liquid) flow. Based on 41 years (approximately) prior literature (1981–till now), 249 articles were studied and number of correlations of pressure drop calculation in microchannels with or without friction factor equation for four cross sections i.e., rectangular, square, circular, trapezoidal, wavy and triangular is collected and also mentioned their limitations at one place. Other than these four cross sections, there is very few experimental/numerical works was present in the literature. A comparable study was performed for laminar as well as turbulent friction factor to calculate the pressure drop with the help of classical theory for gas and liquid flow in microchannels with circular and rectangular cross sections. Results show wonderful outcomes i.e., correlations of laminar pressure drop study can be extendable for transition and turbulent regime in both types (circular and rectangular) of cross sections of microchannels. In different types of flow regime, it is suggested that for each type of cross section (circular and rectangular) we can go for single correlation for gas/liquid system. It is also investigated that the macro channels pressure drop equations can be used for microchannels up to the certain values of Reynolds number. Basically, this paper provides all possible equations of friction factor related to the microchannels that helps to calculate the pressure drop, is collected at one platform also compared their deviation with conventional channels.

Experimental survey of static pressure in stepped chutes with inclined and horizontal steps equipped with end sills in nappe and skimming flow regimes

A spillway is one of the most important parts of a dam for controlling floods. Among different types of spillways, stepped spillways are one of the best energy dissipaters. Due to technological advances and the satisfaction of two elements for safe and low-cost construction, the use of stepped spillways has increased widely. Due to this, more studies are focused on stepped spillways. Researchers have made some efforts and proposed different methods to improve structural efficiency to dissipate energy. Modifications on step geometry, regarding flow regime type, are one of these efforts. Flow pressure and its fluctuations on the steps of the stepped spillways is one of the main factors affecting structural design and safety. In this experimental research, reverse inclined steps combined with the end sills have been applied in four degrees [0o (horizontal), 5o, 8o, and 11o] to obtain static pressure in both the nappe flow and skimming flow regimes of stepped spillways. Static pressure obtained from reverse inclined steps with end sills have been compared to the amount in the horizontal step. Results indicate a slight increase in the energy loss rate when reverse inclined steps have been applied in the nappe flow regime of stepped spillways.

The effect of channel dimensions and configuration of thermoelectric elements on the performance of thermoelectric generator module for waste heat recovery

The use of thermoelectric modules can be effective in recovering waste heat in combustion gasses due to their special properties. In this study, due to the low efficiency of thermoelectric generators, the effects of channel dimensions and configuration of thermoelectric element pairs on heat transfer between a working fluid and a pair of PN elements were studied horizontally and vertically. To develop the simulation of the present model, temperature dependence of generator properties, variations in the convective heat transfer coefficient, temperature gradient, and pressure drop in both hot and cold working fluids along the channel were considered simultaneously. Additionally, it was found that geometric dimensions of rectangular channels affected the four main factors of temperature difference between the two sides of generators, pumped power, number of generators, and type of flow regime. Besides, the findings revealed that the increase in each dimension of the channel reduced the temperature difference between the two sides of elements. This factor was found to play a major role in the efficiency of the thermoelectric generator device, production of power peak, optimal module, channel area, and optimal channel height. In addition, the flow regime changed from turbulent to laminar at cold channel widths greater than 0.11 m. As a result, the total power dropped. Furthermore, the configuration model of PN elements affected the dimensions of the channel. At the length of 1.275 m of the channel, the power generation capacity of the vertical model was by 2.138 times greater than that of the horizontal model per 100 thermoelectric generators.

Wettability control on imbibition behavior of oil and water in porous media

Wettability determines the spreading or adherence behavior of fluids at the solid surface and significantly influences the displacement and entrapment of multiphase fluids in porous media. The present study sets out to determine how wettability controls the imbibition physics of oil and water in a matrix–fracture medium. The displacement and distribution characteristics of fluids, the types of flow regimes, and the fluid morphology under various conditions were revealed in depth. The influences of wettability on oil recovery and energy conversion were analyzed. Finally, the application of the conventional scaling model to simulated imbibition data was also discussed. Results show that the imbibition front is complete and stable in a water-wet medium with the one-end open boundary condition. There are three flow regimes occurring in countercurrent imbibition, depending on the wettability and Ca (capillary number) situations. Increasing θ (contact angle, the affinity of wetting phase to the solid) or Ca can shift the flow pattern from the capillary regime to the capillary-viscous regime to the viscous regime. Additionally, the imbibition oil recovery is greatly affected by wettability, and a more water-wet state does not signify a larger oil recovery. There is a power-law relationship between the oil recovery and the fractal dimension of the nonwetting phase. On the other hand, we performed the energy conversion analysis in the strongly water-wet condition. The external work is positive for both the capillary-viscous and viscous regimes and declines with the decreased Ca. Oil recovery could be linked to the surface energy ratio to some degree, which is relevant to Ca. For the capillary regime, oil recovery is proportional to the final reduced surface energy and does not have an evident relationship with the dissipation energy ratio. Through scaling the recovery factor data vs time via the linear, the power-law, and the conventional models, we find that the conventional scaling model can be used to fit the data point, and the fitting performance is good when Ca is relatively high. However, the linear model is more appropriate when scaling the data in low Ca. Overall, our pore-scale simulation study could pave the way for a further step toward investigating other influencing factors on imbibition behaviors of fluids in more complex media like natural rock materials, which exhibit strong heterogeneity of wettability and pore structure.

Employing GMDH-Type Neural Network and Signal Frequency Feature Extraction Approaches for Detection of Scale Thickness inside Oil Pipelines

In this paper, gamma attenuation has been utilised as a veritable tool for non-invasive estimation of the thickness of scale deposits. By simulating flow regimes at six volume percentages and seven scale thicknesses of a two phase-flow in a pipe, our study utilised a dual-energy gamma source with Ba-133 and Cs-137 radioisotopes, a steel pipe, and a 2.54 cm × 2.54 cm sodium iodide (NaI) photon detector to analyse three different flow regimes. We employed Fourier transform and frequency characteristics (specifically, the amplitudes of the first to fourth dominant frequencies) to transform the received signals to the frequency domain, and subsequently to extract the various features of the signal. These features were then used as inputs for the group method for data Hiding (GMDH) neural network framework used to predict the scale thickness inside the pipe. Due to the use of appropriate features, our proposed technique recorded an average root mean square error (RMSE) of 0.22, which is a very good error compared to the detection systems presented in previous studies. Moreover, this performance is indicative of the utility of our GMDH neural network extraction process and its potential applications in determining parameters such as type of flow regime, volume percentage, etc. in multiphase flows and across other areas of the oil and gas industry.

Enhanced Gamma-Ray Attenuation-Based Detection System Using an Artificial Neural Network

Scale deposition is the accumulation of various materials in the walls of transmission lines and unwanted parts in the oil and gas production system. It is a leading moot point in all transmission lines, tanks, and petroleum equipment. Scale deposition leads to drastic detrimental problems, reduced permeability, pressure and production losses, and direct financial losses due to the failure of some equipment. The accumulation of oil and gas leads to clogged pores and obstruction of fluid flow. Considering the passage of a two-phase flow, our study determines the thickness of the scale, and the flow regime is detected with the help of two Multilayer Perceptron (MLP) networks. First, the diagnostic system consisting of a dual-energy source, a steel pipe, and a NaI detector was implemented, using the Monte Carlo N Particle Code (MCNP). Subsequently, the received signals were processed, and properties were extracted using the wavelet transform technique. These features were considered as inputs of an Artificial Neural Network (ANN) model used to determine the type of flow regimes and predict the scale thickness. By accurately classifying the flow regimes and determining the scale inside the pipe, our proposed method provides a platform that could enhance many areas of the oil industry.

Introducing a Precise System for Determining Volume Percentages Independent of Scale Thickness and Type of Flow Regime

When fluids flow into the pipes, the materials in them cause deposits to form inside the pipes over time, which is a threat to the efficiency of the equipment and their depreciation. In the present study, a method for detecting the volume percentage of two-phase flow by considering the presence of scale inside the test pipe is presented using artificial intelligence networks. The method is non-invasive and works in such a way that the detector located on one side of the pipe absorbs the photons that have passed through the other side of the pipe. These photons are emitted to the pipe by a dual source of the isotopes barium-133 and cesium-137. The Monte Carlo N Particle Code (MCNP) simulates the structure, and wavelet features are extracted from the data recorded by the detector. These features are considered Group methods of data handling (GMDH) inputs. A neural network is trained to determine the volume percentage with high accuracy independent of the thickness of the scale in the pipe. In this research, to implement a precise system for working in operating conditions, different conditions, including different flow regimes and different scale thickness values as well as different volume percentages, are simulated. The proposed system is able to determine the volume percentages with high accuracy, regardless of the type of flow regime and the amount of scale inside the pipe. The use of feature extraction techniques in the implementation of the proposed detection system not only reduces the number of detectors, reduces costs, and simplifies the system but also increases the accuracy to a good extent.

Investigation of influence of elbow on pump inlet flow behaviour in cavitating flow

This paper discusses the effect of elbows in the downstream region of pipe and pumps inlet flow conditions according to standards. Cavitation is a significant occurrence in such types of flow regimes that causes erosion and ultimately affects the pump's performance. Cavitation is also investigated using computational analysis using ANSYS Fluent. It is concluded that the elbow with 90° angle in pipe with some curvature produce eddies in the fluid flow. The variations in the velocity near the downstream were uneven. Moreover, it is also determined computationally that the effect of cavitation on pump inlet flow conditions is also high and in increasing trend. The effect of cavitation in an elbow pipe can be increased if the curvature of the elbow is reduced. This ultimately effect the performance of the pump.

Modeling stage\u2013discharge\u2013sediment using support vector machine and artificial neural network coupled with wavelet transform

Many real water issues involve rivers’ sediment load or the load that rivers can bring without degrading the fluvial ecosystem. Therefore, the assessment of sediments carried by a river is also crucial in the planning and designing of various water resource projects. In the current study, five different data-driven techniques, namely artificial neural network (ANN), wavelet-based artificial neural network (WANN), support vector machine (SVM), wavelet-based support vector machine (WSVM), and multiple-linear regression (MLR) techniques, were employed for time-series modeling of daily suspended sediment concentration (SSC). Hydrological datasets containing the daily stage (h), discharge (Q), and SSC for 10 years (2004–2013) from June to October at Adityapur and Ghatshila station of Subernrekha river basin, Jharkhand, India, were considered for analysis. The Gamma test was used to determine the input variables in the first step. Various combinations were made by lagging the maximum three-day time step for predicting current-day SSC. The outcomes of ANN, SVM, WAAN, WSVM, and MLR models were evaluated with the actual values of SSC based on statistical metrics. Pearson correlation coefficient (PCC), root-mean-square error (RMSE), Nash–Sutcliffe efficiency (NSE), and Wilmot index (WI) as well as visual inspection of time variation, scatter plots, and Taylor diagrams. Our results stated that the WSVM model discovered the best trustworthy models among all existing models. PCC, RMSE, NSE, and WI values were 0.844 and 0.781, 0.096 g/l and 0.057 g/l, 0.711 and 0.591, 0.907 and 0.878, respectively, throughout the training and testing processes at the Adityapur site. Also, at the Ghatshila location, it was the most accurate model. During the training and testing stages, PCC, RMSE, NSE, and WI values were 0.928 and 0.751, 0.117 g/l and 0.095 g/l, 0.861 and 0.541, 0.962 and 0.859, respectively. Our findings showed that the WANN model was the second-best model during the testing phase for both sites. Hence, the WSVM technique can model SSC at this location and other similar (i.e., geomorphology and flow regime type) rivers.