Numerical modeling of converging compound channel flow

Naik, B.; Khatua, Kishanjit Kumar; Wright, Nigel; Sleigh, Andrew; Singh, Prateek Kumar

doi:10.1080/09715010.2017.1369180

Cited by 19 publications

(6 citation statements)

References 42 publications

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“…Calculations involved models k-epsilon and k-ω (omega) for turbulent viscosity and their modificationsk-ε (epsilon) and k-ε RNG (Re-Normalisation Group) (advanced model for turbulent kinetic energy (TKE) and kinetic energy dissipation rate) and k-ω SST (TKE and a comparative rate of kinetic energy dissipation) [17]. The application of the k-ε model assists in solving a system of two nonlinear diffusion equations -TKE density (k ρ ) and kinetic energy dissipation rate (ε)the rate at which TKE converts to heat due to viscous friction.…”

Section: Processesmentioning

confidence: 99%

Investigation on particulate matter and gas motion processes in the advanced multi-channel cyclone-separator with secondary gas inlets

Baltrėnas

Crivellini

Leonavičienė

et al. 2021

Environmental Engineering Research

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Research into gas flow motion as a transported phase and pollutant – particulate matter (PM) is of crucial importance, their changes in particular areas of the object require knowledge of improving the apparatus. A cyclone is considered one of the most popular devices due to the new modified multi-channel design that involves combined separation and filtration phenomena. The findings of an accurate numerical model provide an opportunity to verify long-term experimental studies. In addition, it is possible to determine the impact of the designed principal elements of the structure comprising secondary gas inlets, inner slits and the convex bottom on gas and PM motion through verification conducting experimental research. The study focuses on simulating the upgraded cyclone using the SST k-omega model. The research has been conducted under the specified gas flow conditions such as high temperature and relative humidity (aggressive) gas and presents the results of the physical model to compare with. To achieve greater computational accuracy, a digital model of the cyclone made of specific volumetric elements has been developed thus expanding the grid and stepping to form the boundary zone. As a result, numerical simulation results differ by no more than 12.8% compared to the experimental studies results.

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Section: Processesmentioning

confidence: 99%

Investigation on particulate matter and gas motion processes in the advanced multi-channel cyclone-separator with secondary gas inlets

Baltrėnas

Crivellini

Leonavičienė

et al. 2021

Environmental Engineering Research

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“…In order to detect and evaluate the quality and performance of GPM data, the rain gauge data was applied as a reference for comparison. Several conventional statistical performance metrics were selected, which were the Correlation Coefficient (CC) in Equation (1), the Mean Absolute Error (MAE) in Equation ( 5) [46], the Root Mean Square Error (RMSE) in Equation (4) [47,48] and the Relative Bias (BIAS) in Equation (6). Firstly, the CC described the agreement between satellite estimates and rain gauge observations, and secondly, the MAE, RMSE and BIAS was applied to describe the error and bias of satellite estimates compared with rain gauge observations [49].…”

Section: Data Processingmentioning

confidence: 99%

GPM Annual and Daily Precipitation Data for Real-Time Short-Term Nowcasting: A Pilot Study for a Way Forward in Data Assimilation

Wang

Kong

Yang

et al. 2021

Water

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This study explores the quality of data produced by Global Precipitation Measurement (GPM) and the potential of GPM for real-time short-term nowcasting using MATLAB and the Short-Term Ensemble Prediction System (STEPS). Precipitation data obtained by rain gauges during the period 2015 to 2017 were used in this comparative analysis. The results show that the quality of GPM precipitation has different degrees efficacies at the national scale, which were revealed at the performance analysis stage of the study. After data quality checking, five representative precipitation events were selected for nowcasting evaluation. The GPM estimated precipitation compared to a 30 min forecast using STEPS precipitation nowcast results, showing that the GPM precipitation data performed well in nowcasting between 0 to 120 min. However, the accuracy and quality of nowcasting precipitation significantly reduced with increased lead time. A major finding from the study is that the quality of precipitation data can be improved through blending processes such as kriging with external drift and the double-kernel smoothing method, which enhances the quality of nowcast over longer lead times.

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“…This philosophy inspired us to move forward the method of curve fitting with the strategy of soft computing. Many soft computing techniques have been explored in the field of water resource like neural networks, fuzzy logic, adaptive neuro-fuzzy, gene programming and many more [31][32][33][34][35][36][37]. One such soft computing technique is gene algorithm, which is currently a useful tool for analysing a large data set to explore a potential relationship among the variables involved.…”

Section: Model Of α and β Correction Coefficients By Gene Expression mentioning

confidence: 99%

Models for kinetic energy and momentum correction coefficients for non-prismatic compound channels using regression and gene expression programming

et al. 2019

Self Cite

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This paper studies the effect of different independent variables related to the characteristics of the compound channels on the kinetic energy and momentum correction coefficients (termed as α and β, respectively) of non-prismatic compound channels. A series of experiments were carried out in a converging compound channel with three converging angles, six width ratios, six relative depths and three relative distances. Meanwhile, flow data sets from three different authors were used for diverging compound channels, which include simple rectangular and trapezoidal cross sections. In the present study, conventional multivariable regression technique and gene expression programming were used for developing different models for calculating kinetic energy and momentum correction coefficients for converging and diverging compound channels, respectively. The independent variables used in the curve fitting process were also tested for their accountability and influence on the proposed models. The developed models were finally established with the validation data set and a natural river system.

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Numerical modeling of converging compound channel flow

Abstract: 18This paper presents numerical analysis for prediction of depth-averaged velocity distribution of Numerical simulation in two phases is performed using the ANSYS-Fluent software. k-

Cited by 19 publications

References 42 publications

Investigation on particulate matter and gas motion processes in the advanced multi-channel cyclone-separator with secondary gas inlets

Investigation on particulate matter and gas motion processes in the advanced multi-channel cyclone-separator with secondary gas inlets

GPM Annual and Daily Precipitation Data for Real-Time Short-Term Nowcasting: A Pilot Study for a Way Forward in Data Assimilation

Models for kinetic energy and momentum correction coefficients for non-prismatic compound channels using regression and gene expression programming

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