جستجوی مقالات مرتبط با کلیدواژه "آبشستگی" در نشریات گروه "محیط زیست"

One of the significant issues in hydraulic engineering is reducing erosion in rivers by using groynes to preserve soil. The purpose of this study is to investigate numerically the groynes' presence on the sedimentary flow parameters using FLOW-3D software. For this purpose, groynes were examined at angles 30°, 60°, and 90° under 10 scenarios in various discharge and hydraulic conditions. Here, the mesh block with dimensions of 5 mm was chosen as the optimal mesh block for simulating models. In addition, Large Eddy Simulation (LES) turbulence model was used for simulations. In the scenarios where two blades are used scouring is observed in the first blade, while the sedimentation phenomenon was observed in the groyne after the first groyne in the direction of the flow. In the two blades with a distance of 0.60 m from each other, 48 mm erosion occurred. The highest amount of scour is related to the arched groyne (LLeft-Q285) with 45 mm. Discharges have an increased effect on scouring, so by comparing the scenarios with one groyne (I-Q285, I-Q200, and I-Q350), the lowest amount is with the value of 5.5mm corresponding to I-Q200. The insufficient erosion in the angled groynes corresponds to the smaller angle scenario.

Rivers accumulate huge amounts of floating debris including the trunk, branches and leaves during the floods, leading to increase the depth of local scour around bridge piers. A large number of the laboratorial and field studies have been performed to understand the mechanism of scouring phenomenon under floating debris. Over two past decades, different types of the artificial intelligence methods have been used to estimate the maximum scour depth around bridges piers. In this study, the Neuro-Fuzzy model based on group method data handling (NF-GMDH) was used to estimate the scour under effect of debris accumulations. The NF-GMDH network was developed using evolutional algorithms: genetic algorithm (GA), particle swarm optimization (PSO), and gravitational search algorithm (GSA). Parameters effective on the maximum scour depth included average velocity of upstream flow of the bridge pier, critical velocity of river bed sediments, depth of flow in section without debris, thickness of submerged debris, debris diameter, average particle size, pier diameter, and channel width. After training and experiencing each NF-GMDH models, the performances of each one was evaluated through statistical parameters. The results showed that the models proposed had better performance compared with emperical relationships. NF-GMDH-PSO (R=0.8413 and RMSE=0.37) and NF-GMDH-GA (R=0.8407 and RMSE=0.3640) had relatively similar performance. Finally, sensitivity analysis indicated that the ratio of pile diameter (D) to mean diameter of bed sediments (d50) has the most influence on determination of maximum scour depth.

The erosion of bed and river banks and sediment transport is one of the reasons for migration and changes in river morphology, which causes changes in the quality and quantity of flow. Groins are among the rivers' structures that extend from the coast to the river's axis. One of the important issues in their design is the localized scouring phenomenon on the nose, which appears due to changes in the pattern of flow and the presence of strong vortices. In recent years, most of the research on single-row open and closed open spray guns has been carried out and has been performed in a laboratory. Therefore, in this research, scouring and three-dimensional flow patterns were simulated near the open two-row openings with two zigzag and parallel formations with Flow-3D model and using the RNG turbulence model and compared with experimental results. The results showed that the scour area and the dimensions obtained from numerical simulation as well as flow patterns are in good agreement with experimental results.

One of the main reasons of bridge destruction is the bridge piers scour. A more accurate computation of scour depth would lead to a more solid design of bridge piers. Empirical equations can be applied to compute the scour depth. In this study, the coefficients of 17 empirical equations were optimized using genetic algorithm and fieldwork values. 80% of the field data were used to optimize the equations and the rest were used to verify them. The RMSE, MAE, E and R2 criteria were applied to evaluate the optimization method where the results showed the ability of genetic algorithm in empirical equations optimization. The (Froehlich 1988) equation had the highest degree of precision among the empirical equations, so the genetic algorithm has had the least effect on the optimization of this equation. The optimized (Neill 1964), (Melville 1975), (Laursen & Toch 1956), (Blench II 1962) and (Hancu 1971) equations with respectively, 75, 72, 71, 71 and 71 percent showed the highest reduction in RMSE error criteria. The optimized (Blench II 1962) equation with RMSE, MAE, E and R2 criteria equal to 0.57m, -0.085m, 62 percent and 0.65 respectively, presented the highest correlation coefficient and lowest error. In the end, more equations were proposed to predict the bridge piers scour depth