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Machine Learning application in prediction of Scour around Bridge Piers: A Comprehensive review
Scour is one of the most difficult challenges faced by hydraulic engineers, which refers to the
erosion of sediments that surrounds hydraulic structures. In the past, scour prediction has …
erosion of sediments that surrounds hydraulic structures. In the past, scour prediction has …
Prediction of maximum scour depth at clear water conditions: Multivariate and robust comparative analysis between empirical equations and machine learning …
Flow obstructed by bridge piers can increase sediment transport leading to local scour. This
local scour poses a risk to the stability of bridge structures, which could lead to structural …
local scour poses a risk to the stability of bridge structures, which could lead to structural …
Estimating equilibrium scour depth around non-circular bridge piers using interpretable hybrid machine learning models
Scouring at bridge piers is a crucial issue that risks bridge collapses, causing economic
losses and endangering public safety. Classic models struggle to accurately estimate …
losses and endangering public safety. Classic models struggle to accurately estimate …
Predicting flow velocity in a vegetative alluvial channel using standalone and hybrid machine learning techniques
The presence of vegetation in the water bodies has a profound effect on the flow velocity in
an open channel due to the resistance offered by it. In rivers, estuaries, and coastal …
an open channel due to the resistance offered by it. In rivers, estuaries, and coastal …
An in-depth comparative analysis of data-driven and classic regression models for scour depth prediction around cylindrical bridge piers
The study focuses on the critical concern of designing secure and resilient bridge piers,
especially regarding scour phenomena. Traditional equations for estimating scour depth are …
especially regarding scour phenomena. Traditional equations for estimating scour depth are …
Drying shrinkage and crack width prediction using machine learning in mortars containing different types of industrial by-product fine aggregates
Concrete is a material that loses water and changes shape while hardening due to its
structure. Over time, this water loss results in some shrinkage of the hardened concrete …
structure. Over time, this water loss results in some shrinkage of the hardened concrete …
Modelling of clear water scour depth around bridge piers using M5 tree and ANN-PSO
Scouring refers to the process by which bed sediment in a river is eroded around the
periphery of a bridge abutment or pier. Many empirical models are available to estimate the …
periphery of a bridge abutment or pier. Many empirical models are available to estimate the …
Forecasting of time-dependent scour depth based on bagging and boosting machine learning approaches
Forecasting the time-dependent scour depth (dst) is very important for the protection of
bridge structures. Since scour is the result of a complicated interaction between structure …
bridge structures. Since scour is the result of a complicated interaction between structure …
Predicting Max Scour Depths near Two-Pier Groups Using Ensemble Machine-Learning Models and Visualizing Feature Importance with Partial Dependence Plots …
Assessing scour depth (S d) near side-by-side, tandem, and eccentric bridge piers is crucial
for designing resilient structures. Researchers employed soft computing techniques to …
for designing resilient structures. Researchers employed soft computing techniques to …
[HTML][HTML] Influence of local scour on the dynamic response of bridges under barge collisions
The response assessment of bridges crossing navigable waterways under vessel collisions
is commonly conducted assuming intact bridge models. However, local scour may occur at …
is commonly conducted assuming intact bridge models. However, local scour may occur at …