Hossein Basser

Hybrid ANFIS-PSO approach for predicting optimum parameters of a protective spur dike

A protective spur dike is used to reduce scour depth around main spur dikes.A new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system (ANFIS-PSO) was used.Optimized parameters of the protective spur dike are presented. In this study a new approach was proposed to determine optimum parameters of a protective spur dike to mitigate scouring depth amount around existing main spur dikes. The studied parameters were angle of the protective spur dike relative to the flume wall, its length, and its distance from the main spur dikes, flow intensity, and the diameters of the sediment particles that were explored to find the optimum amounts. In prediction phase, a novel hybrid approach was developed, combining adaptive-network-based fuzzy inference system and particle swarm optimization (ANFIS-PSO) to predict protective spur dikes parameters in order to control scouring around a series of spur dikes. The results indicated that the accuracy of the proposed method is increased significantly compared to other approaches. In addition, the effectiveness of the developed method was confirmed using the available data.

A cooperative expert based support vector regression (Co-ESVR) system to determine collar dimensions around bridge pier

Abstract In this study, a new procedure to determine the optimum dimensions for a rectangular collar to minimize the temporal trend of scouring around a pier model is proposed. Unlike previous methods of predicting collar dimensions around a bridge pier, the proposed approach concerns the selection of different collar dimension sizes around a bridge scour in terms of the flume׳s upstream ( L uc / D ), downstream ( L dc / D ) and width ( L w / D ) of the flume. The projected determination method involves utilizing Expert Multi Agent System (E-MAS) based Support Vector Regression (SVR) agents with respect to cooperative-based expert SVR (Co-ESVR). The SVR agents (i.e. SVR Luc , SVR Ldc and SVR Lw ) are set around a rectangular collar to predict the collar dimensions around a bridge pier. In the first layer, the Expert System (ES) is adopted to gather suitable data and send it to the next layer. The multi agent-based SVR adjusts its parameters to find the optimal cost prediction function in the collar dimensions around the bridge pier to reduce the collar around the bridge scour. The weighted sharing strategy was utilized to select the cost optimization function through the root mean square error (RMSE). The efficiency of the proposed optimization method (Co-ESVR) was explored by comparing its outcomes with experimental results. Numerical results indicate that the Co-ESVR achieves better accuracy in reducing the percentage of scour depth ( r e ) with a smaller network size, compared to the non-cooperative approaches.

Local scour around complex pier groups and combined piles at semi-integral bridge

Abstract This research presents an experimental study on the scouring mechanism at semi-integral bridge piers. Based on laboratory experiments, this study focuses on the relationship between scour depth in complex pier groups and combined piles bridge and various parameters including the variation of inflow velocity, distance, and time. 1 200 data were collected for flow velocity and scour. The flow pattern and scour were analyzed for different flow discharges and flow depths. The results showed that the scour development with respect to time was greater for higher flow depth and bigger flow discharge at semi-integral bridges. In addition, the equilibrium scour depth increased with the approach flow depth around piers at semi-integral bridges. Velocity distribution also affected the scour development. It decreased when approaching the bridge but increased from upstream to downstream of the flume.

Adaptive neuro-fuzzy selection of the optimal parameters of protective spur dike

This study proposes a new approach for determining optimum dimensions of protective spur dike to mitigate scour amount around existing spur dikes. The main objective of this article was to predict the most optimum values of the protective spur dikes to reach the best performance. To predict the protective spur dike parameters for scour controlling around spur dikes, this paper constructed a process which selects the optimal protective spur dike parameters in regard to actual length of the protective spur dike, actual length of the main spur dikes, distance between the protective spur dike and the first spur dike, angle between protective spur dike and flow direction, flow intensity and median size of bed sediments with adaptive neuro-fuzzy (ANFIS) method. To build a protective spur dike with the best features, it is desirable to select and analyze factors that are truly relevant or the most influential to the spur dike. This procedure is typically called variable selection, and it corresponds to finding a subset of the full set of recorded variables that exhibits good predictive abilities. In this study, architecture for modeling complex systems in function approximation and regression was used, based on using ANFIS. Variable searching using the ANFIS network was performed to determine how the five factors affect the protective spur dike. Experimental model of the protective spur dike was used to generate training and checking data for the ANFIS network.

Experimental and Numerical Investigation of the Effect of Different Shapes of Collars on the Reduction of Scour around a Single Bridge Pier

The scour phenomenon around bridge piers causes great quantities of damages annually all over the world. Collars are considered as one of the substantial methods for reducing the depth and volume of scour around bridge piers. In this study, the experimental and numerical methods are used to investigate two different shapes of collars, i.e, rectangular and circular, in terms of reducing scour around a single bridge pier. The experiments were conducted in hydraulic laboratory at university of Malaya. The scour around the bridge pier and collars was simulated numerically using a three-dimensional, CFD model namely SSIIM 2.0, to verify the application of the model. The results indicated that although, both types of collars provides a considerable decrease in the depth of the scour, the rectangular collar, decreases scour depth around the pier by 79 percent, and has better performance compared to the circular collar. Furthermore, it was observed that using collars under the stream’s bed, resulted in the most reduction in the scour depth around the pier. The results also show the SSIIM 2.0 model could simulate the scour phenomenon around a single bridge pier and collars with sufficient accuracy. Using the experimental and numerical results, two new equations were developed to predict the scour depth around a bridge pier exposed to circular and rectangular collars.

Adaptive neuro-fuzzy estimation of the influence of slot on local scour at bridge pier groups

Scouring around bridge pier is a major cause of bridge instability. Thus, providing appropriate methods in order to reduce and control the scour depth have received much attention. Using a slot in the bridge piers is one of modern methods of reducing bridge local scouring. In the present study, the effects of a rectangular slot on local scour mitigation around bridge pier groups have been investigated with adaptive neuro-fuzzy (ANFIS) method. ANFIS shows very good learning and prediction capabilities, which makes it an efficient tool to deal with encountered uncertainties in any system like scouring. The results show that the scour depth increased in the first pier by reinforcing effect and it decreased in the rear piers because of sheltering effect in compare with single pier. In addition, application of the slot in pier groups leads to an increase in the impact of reinforcing effect and reduce the influence of sheltering effect. The use of slot is more influential in front bridge piers than the rear piers in pier groups with 4D distance, however, this effectiveness doesn’t have significant difference among the piers with 2D distance and same as single pier. Laboratory experiments were conducted to create experimental training and checking data for ANFIS network. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.

Modeling sediment transport around a rectangular bridge abutment

In the present paper, the results are explained for an experimental and numerical study on scouring phenomenon around a rectangular, impermeable and non-submerged bridge abutment cross section with perpendicular attitude to the flow axes. In this study, SSIIM 2.0 is used to simulate the scouring problem at the abutment. SSIIM 2.0 is a three-dimensional computational fluid dynamics program that uses a finite volume method to discretize the equations. According to the results, the k–ε turbulence model with some RNG extensions is the best model for predicting turbulence around the rectangular abutment. In addition, different grids are compared in the simulations and the best grid is selected based on the accuracy of numerical results and the computation times. Finally, the findings are explained, and the bed changes and local scour profiles resulting from the numerical simulation are compared with the available experimental results. It is concluded from the achieved results that SSIIM 2.0 numerical modeling is capable of simulating scouring around a rectangular abutment.

Reducing Local Scouring at Bridge Piles Using Collars and Geobags

The present study examines the use of collars and geobags for reducing local scour around bridge piles. The efficiency of collars and geobags was studied experimentally. The data from the experiments were compared with data from earlier studies on the use of single piles with a collar and with a geobag. The results showed that using a combination of a steel collar and a geobag yields the most significant scour reduction for the front and rear piles, respectively. Moreover, the independent steel collar showed better efficiency than the independent geobag below the sediment level around the bridge piles.

Methods for monitoring scour from large-diameter heat probe tests

Scour is the main cause of bridge failures. Monitoring of bridge scour is an essential method to control the damages caused by flood events. In this study, a large-scale tube consisting of heating and temperature-sensing elements was developed, and its application for detecting saturated soil and water was analyzed. Laboratory experiments confirmed the applicability of the thermal sensor for scour-monitoring purposes. Three methods are proposed in this article for analyzing the data obtained from a heat probe. A linear relationship between temperature increase from the initial to the secondary time and heat production in the probe was observed, and a line that can be used to determine scour was introduced. This method is simple and can be used for low-cost, large-diameter heat probes that are easy to fabricate.

Reservoir Sedimentation Based on Uncertainty Analysis

Reservoir sedimentation can result in loss of much needed reservoir storage capacity, reducing the useful life of dams. Thus, sufficient sediment storage capacity should be provided for the reservoir design stage to ensure that sediment accumulation will not impair the functioning of the reservoir during the useful operational-economic life of the project. However, an important issue to consider when estimating reservoir sedimentation and accumulation is the uncertainty involved in reservoir sedimentation. In this paper, the basic factors influencing the density of sediments deposited in reservoirs are discussed, and uncertainties in reservoir sedimentation have been determined using the Delta method. Further, Kenny Reservoir in the White River Basin in northwestern Colorado was selected to determine the density of deposits in the reservoir and the coefficient of variation. The results of this investigation have indicated that by using the Delta method in the case of Kenny Reservoir, the uncertainty regarding accumulated sediment density, expressed by the coefficient of variation for a period of 50 years of reservoir operation, could be reduced to about 10%. Results of the Delta method suggest an applicable approach for dead storage planning via interfacing with uncertainties associated with reservoir sedimentation.