Pier Width Research Articles

The influence of collar parameters on local scour mechanism around the circular pier at the bend

Analysis of bridge failures due to scouring has been extensively studied by different researchers in recent years and as a result various methods of controlling local scour cavity have been given. Since most of the research in this field has been done on straight paths and also the complexity of the flow pattern in bends, studying the scouring pattern around the bridge piers located in the bends has become a necessity. Therefore, one of the main objectives of this study is to investigate the scouring around the circular piers which are protected by collars at the river bends. The performance of the collar significantly depends on its level around the pier, which has been studied in this study. The results showed that the optimal performance of this structure, in positions 60°, 90° and 120° at the level of 0.2 pier width under the bed with 3 mm thickness (0.06 of pier width) by approximately 68, 63 and 70% of the maximum pier scour depth was reduced compared with collarless pier, respectively. By analyzing the results of this research, it was observed that the optimum level range of collar around the pier at various bend angles is the initial bed level up to 0.4 times the pier width at the bottom of the incipient level of the bed. Moreover, getting closer to the plate placement level toward the initial bed elevation enhances the collar’s function in decreasing scouring.

Hydrodynamic Modeling and Comprehensive Assessment of Pier Scour Depth and Rate Induced by Wood Debris Accumulation

This study mainly investigates the impact of debris accumulation on scour depth and scour hole characteristics around bridge piers. Through controlled experiments with uniform sand bed material, the influence of various debris shapes (high wedge, low wedge, triangle yield, rectangular, triangle bow, and half-cylinder), upstream debris length, downstream debris extension, and debris thickness on scour depth and scour hole area and volume around the cylindrical pier were analyzed. The findings revealed that the shape and location of debris in the water column upstream of piers are key factors that determine the depth of scour, with high wedge shapes inducing the deepest scour and potentially the largest scour hole, particularly when positioned close to the pier and fully submerged. Scenarios in which triangle bow debris was submerged at full depth upstream of the pier closely resembled situations devoid of debris. Conversely, debris extension downstream of the pier was found to reduce local scour depth while concurrently enlarging the dimensions of the scour hole. The existing scour prediction equations tend to overestimate scour depth in scenarios involving debris, particularly when applying effective and equivalent pier width. This discrepancy arises because these equations were originally developed to predict scour depth around piers in the absence of debris. In response, a refined model for predicting scour induced by debris was proposed, integrating factors such as upstream debris length, downstream extension, obstruction percentage, and debris shape factor. This model demonstrated strong agreement with experimental data within the scope of this study and underwent further validation using additional experimental datasets from other research endeavors. In conclusion, this experimental study advances the comprehension of scour processes around cylindrical bridge piers, providing valuable insights into the role of debris characteristics and positioning.

Experimental and theoretical study of sediment scour around angled bridge piers

The present study investigated a square-shaped group pier with attack angles of 0°, 10°, 15°, 20°, and 30° and spacing of 2, 3, and 4 times the pier width and a single pier with the same attack angles in the same experimental conditions. Also, a semi-empirical equation was presented for predicting the maximum depth of scour for single pier and group pier, which had good agreement with experimental results. Results indicated that by considering the angle of the single square pier, the flow impact area on the pier was altered, and the maximum depth of scour was reduced due to deformation resulting from the attack angle of the pier. In the tests related to the group pier, the attack angle of 15° was known as the critical attack angle in this study, which agreed with the results of previous studies.

New formula for scour depth at piles based on energy equilibrium

An accurate prediction of local scour depth at piles is essential for bridge safety. Lots of formulae were proposed but most of them are empirical ones without rigorous analysis. In this study a new formula for predicting maximum scour depth is established on the basis of the balance between the energy required for scour caused by downflow, longitudinal flow as well horseshoe vortex and the energy of sediment moving out of the scour hole. The present formula including its coefficient is entirely derived from theoretical analysis, making it more convincing and precise, hence is more reliable than other existing formulas for predicting maximum scour depth at piles. It is of both theoretical and computational significance that the exponents of our formula items are all rational numbers, namely the dimensionless scour depth at piles is proportional to 2/3 power of the Froude number, 1/3 power of the relative pier width and 1/3 power of the characteristic sediment parameter. The maximum scour depth calculated from our formula agrees well with the measured data from laboratory and field site.

Discrete Analysis of Local Scour Morphology of Bridge Piers Affected by Sediment Storage Dam

In order to solve the prediction and protection problems of local pier scour with a downstream sediment storage dam on non-uniform sand riverbeds in mountainous areas, the Xi’an Chanhe Bridge in China was taken as the research object. Through comprehensive physical model experiments, the influence of sediment storage dam layout on the surrounding water flow and local scour morphology around bridge piers was studied. The relationship between boundary conditions and local scour pit morphology was studied using a discrete analysis model. The research results showed that the inflow rate Q was the most significant factor affecting local scour, and local scour generally developed rapidly within 0.5–1.0 h and then gradually reached a dynamic equilibrium. The maximum depth was located within 0.25B in front of the pier relative to the pier width , and the impact range of local scour behind the pier was [5B, 10B] . The recommended layout of a sediment storage dam has a distance between pier and dam L of [8B,11B] and a dam crest elevation Z higher than that of the original riverbed elevation at the bridge pier, which is [0.4B, 0.5B]. An improved calculation formula for the local scour depth of bridge piers is proposed and verified through experimental measurements to provide a reference for the design and protection of bridge piers with a downstream sediment storage dam.Q

Analysis of Variables Influencing Scour on Large Sand-Bed Rivers Conducted Using Field Data

Throughout the lifespan of a bridge, morphological changes in the riverbed affect the variable action-imposed loads on the structure. This emphasizes the need for accurate and reliable data that can be used in model-based projections targeted for the identification of risk associated with bridge failure induced by scour. The aim of this paper is to provide an analysis of scour depth estimation on large sand-bed rivers under the clear water regime, detect the most influential (i.e., explanatory) variables, and examine the relationship between them and scour depth as a response variable. A dataset used for the analysis was obtained from the United States Geological Survey’s extensive field database of local scour at bridge piers, i.e., the Pier-Scour Database (PSDB-2014). The original database was filtered to exclude the data that did not reflect large sand-bed rivers, and several influential variables were omitted by using the principal component analysis. This reduction process resulted in 10 influential variables that were used in multiple non-linear regression scour modeling (MNLR). Two MNLR models (i.e., non-dimensional and dimensional models) were prepared for scour estimation; however, the dimensional model slightly overperformed the other one. According to the Pearson correlation coefficients (r), the most influential variables for estimating scour depth were as follows: Effective pier width (r = 0.625), flow depth (r = 0.492), and critical and local velocity (r = 0.474 and r = 0.436), respectively. In the compounded hydraulic-sediment category, critical velocity had the greatest impact (i.e., the highest correlation coefficient) on scour depth in comparison to densimetric Froude and critical Froude numbers that were characterized by correlation coefficients of r = 0.427 and r = 0.323, respectively. The remaining four variables (local and critical bed shear stress, Froude number, and particle Reynolds number) exhibited a very weak correlation with scour depth, with r < 0.3.

Preliminary results of parametric study of structural behaviour of Persian brick masonry groined multipartite (Tarkin) vaults

In this paper, the structural behaviour of Persian brick masonry groined quadripartite, sexpartite and octopartite vaults is studied. Three different spans, three different pier heights and three different pier widths adopted from real structures are considered. Seven different cross-sectional shapes are selected for the vaults and the supporting arches. Vaults are subjected to four cases of pier settlement and seven cases of pier rotation. Three-dimensional non-linear finite element has been used for analysis. Results show that the load bearing capacity is sensitive to the type of the vault and the shape of the arches, to the type of pier settlement and pier rotation. Ranges for the pier height to the pier width ratio for the highest resistance of the vaults are proposed for pier settlement and rotation.

Machine Learning Model for Estimation of Local Scour Depth around Cylindrical Bridge Piers

Scour around bridge piers is a well-known threat to bridge stability worldwide. It can cause losses in lives and the economy, especially during floods. Therefore, an artificial intelligence approach called artificial neural network (ANN) was used to predict the scour depth around bridge piers. The ANN model was trained with laboratory data, including pier width, flow velocity, particle diameter, sediment critical velocity, flow depth, and scour depth. The data was divided into 70% for training, 15 for validation, and 15% for testing. Besides, the ANN model was trained using various training algrthins and a single hidden layer with 20 neurons in the hidden layer. The results showed that the ANN model with Bayesian regularization backpropagation training algorithm provides a better predicted scour depth with a correlation coefficient (R) equal to 0. 9692 and 0.926 for training and test stages, respectively. Besides, it showed a low mean squared error (MSE), which was 0.0034 for training and 0.0066 for the test. These results were slightly better than the ANN with Levenberg-Marquardt backpropagation with R training equals 0.9552 (MSE training = 0.0047), and R test equals 0.838 (MSE test = 0.007).On the other hand, the ANN model with a scaled conjugate gradient backpropagation training algorithm showed worse predictions (R training = 0.7407 and R test = 0.6409). Besides, the ANN model shows better outcomes than the linear regression model. Finally, the sensitivity analysis has shown that the pier width is the most crucial parameter for estimating scour depth using the ANN model.

Experimental and numerical investigation on masonry arch bridges under uniform and line loads

In this paper, the performance of Persian skewed brick masonry arch bridges under uniform and line loads has been investigated. Three types of semi-circular, pointed and four-centred arches have been studied. Bridges with two spans and six spans have been analysed using the three-dimensional non-linear finite element method. The parameters considered are four skew angles, three pier width to span ratios, three bridge width to span ratios, three pier height to span ratios, and three deck thickness to span ratios. Loading includes uniformly distributed load on the entire surface of the bridge deck, line load at the middle of the middle pier, and line load at the apex of one of the arches. The suitable ranges of the skew angle to create the maximum load-bearing capacity have been obtained for different loadings, different types of the arches and other parameters.

Effects of hooked-collar on the local scour around a lenticular bridge pier

This paper presents the results of comprehensive laboratory experiments to investigate the effects of hooked-collar on the scour development around a vertical pier with a lenticular cross section. The flow around the pier was uniform, steady, and under the clear-water condition. The axial scour profiles for cases without and with a lenticular hooked-collar were measured and the effects of hooked-collar dimensions and elevation from the bed were examined. To compute the efficiency of hooked-collar for scour prevention, the results of local scour for a bridge pier without a collar and a bridge pier with a plain collar, without a hooked wall, were used as benchmark data sets. A wide range of hooked-collar geometries such as the ratio of collar width to the pier width, Wc/Wp, ranging from 1.5 to 3.5, the ratio of hooked-collar wall height to the pier width, Hc/Wp, ranging from 0.15 to 0.6, and the ratio of collar elevation to the pier width, Ec/Wp, of −0.5, 0, and 0.5 were tested. The experimental results indicated that the equilibrium scour depth decreased with the ratio of hooked-collar to the pier width when Wc is twice the pier width, Wp. For Wc/Wp > 2, the scour depth was similar to the tests with an infinitely large pier width. In addition, the scour depth consistently reduced as the hooked-collar wall height, Hc, to the pier width, Wp, approached 0.3. The highest scour reduction efficiency was achieved when the hooked-collar being placed on the bed surface. Empirical models were developed for prediction of maximum scour depth near the lenticular bridge pier with a modified collar. The results showed that the volume of scour hole around a lenticular pier increased non-linearly with the maximum scour depth and it was independent of the hooked-collar geometry.

Live-bed pier scour in supercritical open-channel flows

Under a flow in supercritical regime, depending on the pier width to water depth ratio, the flow pattern around a bridge pier can take the form of a wall-jet-like bow wave or a detached hydraulic jump. The present work aims at analysing the maximum scour depth at piers in both flow patterns. A dedicated experimental set-up was used to produce the live-bed scour experiments, varying the inflow velocity and pier diameter. During the experiments, scour developed very rapidly, achieving equilibrium conditions after few minutes. No major differences between the maximum scour depth in the wall-jet-like bow wave and detached hydraulic jump cases were observed. Measured scour depths were of comparable magnitude and followed similar tendencies with controlling parameters as in subcritical flows. Scour formulas for piers in subcritical flow thus achieve a good accuracy in prediction of maximum scour depth at piers in supercritical flows.

Prediction of Local Scour around Bridge Piers in the Cohesive Bed Using Support Vector Machines

Local scour around bridge piers is one of the most important factors threatening the life of bridges. The three-dimensional highly complicated horseshoe vortex and downflow are known to be the main agents responsible for pier scour. If the bed consists of cohesive sediment, it will add another level of complexity to the pier scour problem. Various approaches have attempted to predict scour depth, but no universal method is available to date. This study presents a prediction of local scour around bridge piers in the cohesive bed using support vector machines (SVMs), a machine learning technique. The maximum scour depth is predicted with seven dimensional variables, including velocity, flow depth, size of bed sediment, pier width, clay content, water content, and bed shear strength. The training and validation of the SVMs are conducted with 197 data from six datasets. Comparisons are made with the training and validation of the adaptive-network-based fuzzy inference system (ANFIS) method. The training of the ANFIS method appears successful, but the validation fails because of overfitting. The predictions with dimensionless variables are compared, and shown to be worse. In addition, the SVMs are found to predict the maximum scour depths better than three existing formulas, gene expression programming (GEP), and a non-linear regression model. The SVMs are applied to two datasets, revealing the importance of the coverage of the training data. Finally, to investigate the contributions of each variable, the mean absolute percent errors (MAPEs) and correlation coefficient are computed by predicting the maximum scour depths by excluding each variable.

Evaluation of gene expression programming and artificial neural networks in PyTorch for the prediction of local scour depth around a bridge pier

Local scouring around the piers of bridges has been identified as one of the main problems contributing to bridge failure globally. As such, the accurate prediction of safe scouring depths is crucial to assure safety and to develop effective maintenance routines. This study was thus intended to develop a new empirical equation and models to expect the depth of scour occurring around the pier of a bridge by utilising and assessing a variety of modelling proposals to develop the best possible performance. Three methods were used for this purpose: artificial neural networks (ANN), gene expression programming (GEP), and statistical non-linear regression (NLR). The ANN model used in this study was coded in Python, a major modern coding language, being based on the PyTorch interface. The empirical equations and models derived to predict local scour depth were all amended to incorporate the shape of the pier, flow depth, flow intensity, pier width and the attack angle based on data computed within a numerical simulation model in Flow-3D software. The performance of the functional relationship derived from the GEP approach was then compared to the results computed from both the ANN model and NLR empirical equation, with three statistical indices: root mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2), as well as appropriate scatter plots used to identify the most efficient of the three models. Based on this comparison, the ANN model performed more accurately than the other two empirical equations derived from the NLR and GEP models based on its smaller values for MAE (0.012) and RMSE (0.029), and its greater R2 value (0.969). Sensitivity analysis results from the model also suggest that flow depth has the most significant impact on depth of scour predictions for compared to different input variables in this model. Based on the results, it can be concluded that the performance of the equation obtained from the ANN-based PyTorch technique is more accurate in predicting the scour depth than GEP and NLR.

Experimental Study Effect of the Flexible Collar on Bridge Pier Scouring Depth

Bridge pier's local scouring is known to be a destructive factor in river engineering science. This phenomenon is widespread in river intersecting structures such as bridge piers, spur dykes, and downstream river structures. Extensive research has been conducted to reduce and control destructive phenomena, and many solutions have been proposed. These solutions are divided into two parts, namely, direct and indirect protection. In this study, the direct method was studied by defining scenarios. Since many bridges are affected by scouring during the operation, in the present study, the collar method, which is known as a direct protection method, in the case of flexible and permeable, is suggested. The technique is presented an adjustable chain collar, three times bigger than the pier's width (w/d=3), and its effect is investigated in clear water conditions. In the defined scenarios, three different diameters of the chain as CI=5 mm, CII=10 mm, and CIII=15 mm were used to control chain shapes' effect, and three dimensionless flow parameters (U/Uc 0.73, 0.85, and 0.96) were selected to investigate the effect of flow conditions. According to the results, the scour depth is related to changes in the diameter of the collar chain, as the final scour depth decreases by increasing the diameter of the chain from CI to CIII. Therefore, in the best conditions, for CIII, the dimensionless ratio of scouring reduction ( ) is equal to 71% near to inception motion parameter (U/Uc=0.96).

Sequential minimal optimization for local scour around bridge piers

Accurate determination of scour depth (ds ) around bridge piers is a major concern and an essential criterion in the safe and economical design of bridge pier foundation. The estimation of ds by the conventional empirical methods is difficult due to the very complex mechanism of the 3D flow around the bridge piers. This paper proposes the Sequential Minimal Optimization Regression (SMOREG) approach for local pier scour depth estimation. Additionally, Gradient Boosted (GBM), K-Nearest Neighbors (K-NN), and Random Forest (RF) methods were developed to compare the statistical performance of SMOREG. The numerous reliable databases from the literature includes six input parameters such as pier width (b), pier length (l), skew of the pier to approach flow (θ), mean velocity (v), flow depth (y), the particle size for which 50 percent of the bed material (D 50), and an output parameter ds . It revealed that the SMOREG can build a relationship between ds and flow characteristics and provides an estimation with an R-value of 0.85 and a mean absolute error (MAE) of 0.35. The comparison between models developed in this study showed that SMOREG and RF gave higher prediction performance than GBM and K-NN with respect to synchronic evaluation between RMSE, R, and Standard Deviation. The sensitivity analysis were also performed to determine the efficiency of each input parameter in the estimation of ds . It is found that pier width and mean velocity of the flow are the most effective parameters than the other parameters to estimate ds . The SMOREG models for sensitivity yielded MAE values in the range of 0.34–0.39.

Evaluation of Local Scour Calculation Equations for Bridge Piers in Sandy Riverbed

Local scour depth is the key index of foundation design of bridge across river. At present, there are many equations to calculate the scour depth of bridge piers, but the results of different equations vary greatly. It is still a difficult problem for bridge designers how to choose the appropriate equation for calculating local scour depth. Six typical equations for calculating local scour depth were selected to compare and analyze the influences of pier width, velocity, water depth in front of piers and bed sand particle size on the local scour depth. The results showed that bed sand particle size and geometric non-uniformity coefficient had the most significant influence on the scour depth. It was proposed that the prediction equation should be selected according to the size range and uniformity of bed sand.

Analysis of Scour Depth Around Bridge Piers With Round Nose Shape by HEC-RAS 5.0.7 Software

Local scour of bridge piers is the main reason for the failure of a hydraulic structure like abutment, bridge piers, etc. Local scours is a complex phenomenon that depends on the discharge, depth of flow, shapes of the pier and distribution of sediment particle. The problems of local scours occurred in Krueng Ineng river, Nagan Raya Regency will cause a structural collapse which has the impact of decreasing the stability of the bridge structure. In this study, the software of Hydrologic Engineering Center River Analysis System (HEC-RAS) 5.0.7 is used to evaluate local scour around the bridge pier which employs the Colorado State University method as a default equation. Flow conditions were simulated using HEC-RAS flow modeling software estimated for 100-year flood. The Results of the analysis with used the peak discharge (Qp100) that occurs in the Krueng Seunagan watershed is 1513m3/sec, pier width of Round Nose shape is 4m, and average grain size analysis D50 and D95 is 0.91mm and 4.35mm, show a maximum scour depth obtained is 5.04m. The results of this study will be a reference for the local government to planning appropriate handling for minimalizing local scours in the study area.

Prediction of the depth of local scouring at a bridge pier using a gene expression programming method

Local scouring around the piers of a bridge is the one of the major reasons for bridge failure, potentially resulting in heavy losses in terms of both the economy and human life. Prediction of accurate depth of local scouring is a difficult task due to the many factors that contribute to this process, however. The main aim of this study is thus to offer a new formula for the prediction the local depth of scouring around the pier of a bridge using a modern fine computing modelling technique known as gene expression programming (GEP), with data obtained from numerical simulations used to compare GEP performance with that of a standard non-linear regression (NLR) model. The best technique for prediction of the local scouring depth is then determined based on three statistical parameters: the determination coefficient (R2), mean absolute error (MAE), and root mean squared error (RMSE). A total data set of 243 measurements, obtained by numerical simulation in Flow-3D, for intensity of flow, ratio of pier width, ratio of flow depth, pier Froude number, and pier shape factor is divided into training and validation (testing) datasets to achieve this. The results suggest that the formula from the GEP model provides better performance for predicting the local depth of scouring as compared with conventional regression with the NLR model, with R2 = 0.901, MAE = 0.111, and RMSE = 0.142. The sensitivity analysis results further suggest that the ratio of the depth of flow has the greatest impact on the prediction of local scour depth as compared to the other input parameters. The formula obtained from the GEP model gives the best predictor of depth of scouring, and, in addition, GEP offers the special feature of providing both explicit and compressed arithmetical terms to allow calculation of such depth of scouring.

Estimating Pier Scour Depth: Comparison of Empirical Formulations with ANNs, GMDH, MARS, and Kriging

Scouring, occurring when the water flow erodes the bed materials around the bridge pier structure, is a serious safety assessment problem for which there are many equations and models in the literature to estimate the approximate scour depth. This research is aimed to study how surrogate models estimate the scour depth around circular piers and compare the results with those of the empirical formulations. To this end, the pier scour depth was estimated in non-cohesive soils based on a subcritical flow and live bed conditions using the artificial neural networks (ANN), group method of data handling (GMDH), multivariate adaptive regression splines (MARS) and Gaussian process models (Kriging). A database containing 246 lab data gathered from various studies was formed and the data were divided into three random parts: 1) training, 2) validation and 3) testing to build the surrogate models. The statistical error criteria such as the coefficient of determination (R2), root mean squared error (RMSE), mean absolute percentage error (MAPE) and absolute maximum percentage error (MPE) of the surrogate models were then found and compared with those of the popular empirical formulations. Results revealed that the surrogate models’ test data estimations were more accurate than those of the empirical equations; Kriging has had better estimations than other models. In addition, sensitivity analyses of all surrogate models showed that the pier width’s dimensionless expression (b/y) had a greater effect on estimating the normalized scour depth (Ds/y).

Experimental Study on the Effect of Thickness and Level of the Collar on the Scour Pattern in 180° Sharp Bend with Bridge Pier

Scouring around the bridge's piers is one of the major causes of serious damage to the bridge pier. A laboratory modelling method has been utilized in this research to study the effect of level and thickness of collar on scouring around the pier. The experiments were carried out in a channel with a 180° bend and a relative curvature radius equal to 2. This channel is composed by the straight upstream- and downstream-directed paths, respectively, 6.5 and 5.1 m long and 1 m wide. All experiments were conducted with a constant discharge capacity equal to 0.07 m3⁄s. The obtained results indicated that the installation of the collar at the initial bed surface and 0.4 pier width under the initial bed level with thickness of 0.12 and 0.06 pier width helped gain the best results in reducing the amount of scouring when placing the pier at 90° of the bend. It also decreased 70% of the maximum depth of the scour hole in comparison with when the collar was not implemented. In the positions of 60° and 120°, the thickness parameter has no appreciable effect on scouring, and the best level of collar in this positions is same as the pier located at 90° of bend.