Scour at selected bridge sites in Mississippi

Wilson, K.V.

doi:10.3133/wri944241

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…One of the common methods for estimating the scour depth near bridge pier is the use of empirical relationships. A lot of research has been done by researchers in this field that has led to a variety of empirical relationships [11,[35][36][37][38][39][40][41]. The results of scour depth estimation with the empirical relationships are compared with the results of the proposed models (…”

Section: Comparison Of Results With Empirical Relationshipsmentioning

confidence: 99%

Meta-heuristic Optimization Algorithms for Predicting the Scouring Depth Around Bridge Piers

Hassanzadeh¹,

Jafari-Bavil-Olyaei²,

Taghi-Aalami³

et al. 2019

Period. Polytech. Civil Eng.

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An accurate estimation of bridge pier scour has been considered as one of the important parameters in designing of bridges. However, due to the numerous involved parameters and convolution of this phenomenon, many existing approaches cannot predict scour depth with an acceptable accuracy. Obtained results from the empirical relationships show that these relationships have low accuracy in determining the maximum scour depth and they need a high safety factor for many cases, which leads to uneconomic designs of bridges. To cover these disadvantages, three new models are provided to estimate the bridge pier scour using an adaptive networkbased fuzzy inference system. The parameters of the system are optimized by using the colliding bodies optimization, enhanced colliding bodies optimization and vibrating particles system methods. To evaluate the efficiency of the proposed methods, their results were compared with those of simple adaptive network-based fuzzy inference system and its improved versions by using the particle swarm optimization and genetic algorithm as well as the empirical equations. Comparison of results showed that the new vibrating particles system based algorithm could find better results than other two ones. In addition, comparison of the results obtained by the proposed methods with those of the empirical relations confirmed the high performance of the new methods.

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Section: Comparison Of Results With Empirical Relationshipsmentioning

confidence: 99%

Meta-heuristic Optimization Algorithms for Predicting the Scouring Depth Around Bridge Piers

Hassanzadeh¹,

Jafari-Bavil-Olyaei²,

Taghi-Aalami³

et al. 2019

Period. Polytech. Civil Eng.

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Scour at bridge sites in Delaware, Maryland, and Virginia

Hayes¹

1996

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Scour data were obtained from discharge measurements to develop and evaluate the reliability of constriction-scour and local-scour equations for rivers in Delaware, Maryland, and Virginia. No independent constriction-scour or local-scour equations were developed from the data because no significant relation was determined between measured scour and streamflow, streambed, and bridge characteristics. Two existing equations were evaluated for prediction of constriction scour and 14 existing equations were evaluated for prediction of local scour. Constriction-scour data were obtained from historical stream discharge measurements, field surveys, and bridge plans at nine bridge sites in the three-State area. Constriction scour was computed by subtracting the average-streambed elevation in the constricted reach from an uncontracted-channel reference elevation. Hydraulic conditions were estimated for the measurements with the greatest discharges by use of the Water-Surface Profile computation model. Measured and calculated constrictionscour data were used to evaluate the reliability of Laursen's clear-water constriction-scour equation and Laursen's live-bed constriction-scour equation. Laursen's clear-water constriction-scour equation underestimated 21 of 23 scour measurements made at three sites. A sensitivity analysis showed that the equation is extremely sensitive to estimates of the channel-bottom width. Reduction in estimates of bottom width by one-third resulted Name Leipsic River at Leipsic, Del.

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Scour at selected bridge sites in Mississippi

Cited by 2 publications

References 12 publications

Meta-heuristic Optimization Algorithms for Predicting the Scouring Depth Around Bridge Piers

Meta-heuristic Optimization Algorithms for Predicting the Scouring Depth Around Bridge Piers

Scour at bridge sites in Delaware, Maryland, and Virginia

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