Mohammadmehdi Razmi; Mojtaba Saneie; Shamsa Basirat
Abstract
In this paper, the ANFIS network was optimized using three algorithms comprising the Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), and Genetic algorithm (GA) for the first time. To ameliorate the ability of the numerical models,the Monte Carlo simulations were utilized. Moreover, in order ...
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In this paper, the ANFIS network was optimized using three algorithms comprising the Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), and Genetic algorithm (GA) for the first time. To ameliorate the ability of the numerical models,the Monte Carlo simulations were utilized. Moreover, in order to assess the simulation outcomes, the k-fold cross validation technique was implemented. Initially, using all inputs, five different parameters were used for producing theANFIS, ANFIS-GA, ANFIS-PSO, and ANFIS-FFA methods. After that, a computational fluid dynamics (CFD) model simulated the discharge coefficient (DC) and the outcome of all simulations were compared. The analysis of the results demonstrated that the ANFIS-FFA model approximates the DC with higher precision. For instance, the amount of the coefficient of determination and the scatter index were surmised as 0.961 and 0.039. Also, the side weir height ratio tothe upstream depth (P/y1) was detected as the most influential parameter. About 85% of the DC simulated by the ANFIS-FFA model had an inaccuracy of less than 5%. The performed uncertainty analysis proved that the best model possesses an underestimated efficiency. For this model, the influence of the inputs were analyzed in a ±10% range. Finally, a computational code was presented for the simulation of DC by hydraulic and environmental engineers.
Salma Ajeel Fenjan; Ali Akbar Akhtari; Mohammad Hadi Tavana
Abstract
In this study, the performance of vertical and tilted crown weirs with different angles of the weir crest across the flow has been investigated using numerical and experimental models. Accordingly, various experiments are conducted on tilted crown sharp-crested weirs under different free-flow conditions. ...
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In this study, the performance of vertical and tilted crown weirs with different angles of the weir crest across the flow has been investigated using numerical and experimental models. Accordingly, various experiments are conducted on tilted crown sharp-crested weirs under different free-flow conditions. Moreover, computational fluid dynamic (CFD) modeling has been done using Fluent software to determine the best form of the discharge coefficient (Cd). In this study, the RNG model is used to define turbulence in the fluid flow and the two-phase volume of fluid (VOF) method is applied to define the interface of water-air in the flume. To verify the accuracy of the CFD model, the experimental data that was done in this research are used. Moreover, another goal of this research is to investigate the influence of the different angles of weir on hydraulic characteristics of flow such as pressure, velocity and Cd parameters. The results show that by increasing the weir crest angle across the flow (α), the Cd values are almost constant. Furthermore, the numerical results are in good agreement with the experimental models. As, the comparison of numerical and experimental data shows that the maximum absolute relative error (ARE) obtained are 2.8 %, which indicates the high accuracy of the CFD model. The vortex area with return velocity vectors can be seen in downstream of the weir and these vectors increase near the weir. In all velocity values, by decreasing the angle of weir to the flow direction, the Cd values increased and tends to a constant value while, the pressure values decreased. As for the velocity values in ranges of 0.05-0.23 m/s, the Cd value is ranged in 0.64-0.675. Finally, as the Reynolds and Froude number increase, the discharge coefficient decreases and tends to a constant number of 0.65 approximately.
Ali Azizpor; Ahmad Rajabi; Fariborz Yosefvand; Saeid Shabanlou
Abstract
In the current study, a new hybrid of the genetic algorithm (GA) and adaptive Neuro-fuzzy inference system (ANFIS) was introduced to model the discharge coefficient (DC) of triangular weirs. The genetic algorithm was implemented for increasing the efficiency of ANFIS by adjusting membership functions ...
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In the current study, a new hybrid of the genetic algorithm (GA) and adaptive Neuro-fuzzy inference system (ANFIS) was introduced to model the discharge coefficient (DC) of triangular weirs. The genetic algorithm was implemented for increasing the efficiency of ANFIS by adjusting membership functions as well as minimizing error values. To evaluate the proficiency of the proposed hybrid method, the Monte Carlo simulations (MCS) and the k-fold validation method (k=5) was applied. The results of developed hybrid model indicate that the weir vortex angle, flow Froude number, the ratio of the weir length to its height, the ratio of the channel width to the weir length and ratio of the flow head to the weir height are the most effective parameters in the DC estimation. The quantitative examination of the proposed hybrid method indicates that the Root Mean Square Error (RMSE) and Mean Absolute Percent Error (MAPE) are as 0.016 and 1.647 (respectively) for the superior model. Besides, the Froude number is found as the most effective variable in DC modeling through the quantitative analysis. A comparison of the developed hybrid ANFIS-GA with the individual ANFIS model in the DC estimation indicates the hybrid model outperformed than the individual one.
Mohammad Ali Izadbakhsh; Reza Hajiabadi
Abstract
In the article, through the adaptive neuro-fuzzy inference system (ANFIS), a sensitivity analysis is conducted on the variables affecting the discharge capacity of the weir. To this end, the variables affecting the discharge capacity of labyrinth weirs are initially identified. Then, using these input ...
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In the article, through the adaptive neuro-fuzzy inference system (ANFIS), a sensitivity analysis is conducted on the variables affecting the discharge capacity of the weir. To this end, the variables affecting the discharge capacity of labyrinth weirs are initially identified. Then, using these input parameters, seven ANFIS models are developed for conducting the sensitivity analysis. After that, the most optimal membership function number for the ANFIS model is chosen. In other words, by conducting the trial and error process, the best number of the membership functions in terms of time and modeling accuracy are selected. Then, the sensitivity analysis is performed for the ANFIS models and the superior ANFIS model is chosen finally. The accuracy of the superior model in both the validation and testing artificial intelligence (AI) methods is in an acceptable range. For example, the scatter index (SI), correlation coefficient (R) and the Nash-Sutcliff efficiency coefficient (NSC) for the model in the testing mode are obtained 0.049, 0.964 and 0.924, respectively. It should be noticed that the outcomes of the sensitivity analysis show that the ratio of the weir head to the weir crest and the Froude number are introduced as the most effective input parameters. Eventually, a computer code is proposed to estimate the discharge capacity of labyrinth weirs by this model.
Ehsan Yarmohammadi; Fariborz Yosefvand; Ahmad Rajabi; Saeid Shabanlou
Abstract
In this paper, for the first time, the discharge coefficient of triangular plan form weirs is simulated by the extreme learning machine (ELM). ELM is one of the powerful and rapid artificial intelligence methods in modeling complex and non-linear phenomena. Compared to other learning algorithms such ...
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In this paper, for the first time, the discharge coefficient of triangular plan form weirs is simulated by the extreme learning machine (ELM). ELM is one of the powerful and rapid artificial intelligence methods in modeling complex and non-linear phenomena. Compared to other learning algorithms such as back propagation, this model acts rapidly in the learning process and provides a desirable performance in processing generalized functions. In this study, the Monte Carlo simulation is used for examining capabilities of numerical models. Also, the k-fold cross validation method with k=5 is utilized for evaluating abilities of the ELM models. Then, six ELM models are introduced by means of the parameters affecting the discharge coefficient of triangular plan form weirs. After that, the superior model is identified by analyzing the results of the mentioned models. The superior model predicts discharge coefficient values with reasonable accuracy. This model simulates the discharge coefficient as a function of the flow Froude number, vertex angle of the triangular plan form weir, the ratio of weir length to its height, the ratio of flow head to weir height and the ratio of channel width to weir length. For the best model, the Mean Absolute Error, Root Mean Square Error and determination coefficient are computed 1.173, 0.012 and 0.967, respectively. Furthermore, examination of the influence of the input parameters indicates that the flow Froude number is the most influenced factor in modeling the discharge coefficient. Also, the error distribution showed that roughly 86 % of the superior model results had an error less than 2 %. Furthermore, a practical equation was provided to compute the discharge coefficient.
Azam Akhbari; Amir Hossein Zaji; Hamed Azimi; Mohsen Vafaeifard
Abstract
Weirs are installed on open channels to adjust and measure the flow. Also, discharge coefficient is considered as the most important hydraulic parameter of a weir. In this study, using the Radial Base Neural Networks (RBNN) and M5' methods, the discharge coefficient of triangular plan form weirs is modeled. ...
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Weirs are installed on open channels to adjust and measure the flow. Also, discharge coefficient is considered as the most important hydraulic parameter of a weir. In this study, using the Radial Base Neural Networks (RBNN) and M5' methods, the discharge coefficient of triangular plan form weirs is modeled. At first, the effective parameters in the prediction of the discharge coefficient are identified. Then, by combining the input parameters, for each of the RBNN and M5' methods, six different models are introduced. By analyzing the modeling results for all models, it was shown that the M5' model is capable of modeling the discharge coefficient more accurately. Also, based on the modeling results, a model that considered the impact of all input parameters was introduced as a superior model. The mean absolute percentage error (MAPE) and correlation coefficients (R2) values for the preferred model in the test mode were calculated 2.774 and 0.831, respectively. Also, for each of the M5' models, some relationships were proposed to estimate the triangular plan form weirs. The evaluation of these relationships showed that the parameters of the ratio of head over the weir to channel width (h/B) and Froude number (Fr) were the most effective parameters in the prediction of the discharge coefficient.