scholarly journals Gene-expression programming to predict pier scour depth using laboratory data

2011 ◽  
Vol 14 (3) ◽  
pp. 628-645 ◽  
Author(s):  
Mujahid Khan ◽  
H. Md. Azamathulla ◽  
M. Tufail
Keyword(s):  
Gene Expression ◽  
Gene Expression Programming ◽  
Laboratory Data ◽  
Bridge Pier ◽  
Scour Depth ◽  
Bridge Scour ◽  
Regression Equations ◽  
Pier Scour ◽  
Depth Prediction ◽  
Bridge Pier Scour

Prediction of bridge pier scour depth is essential for safe and economical bridge design. Keeping in mind the complex nature of bridge scour phenomenon, there is a need to properly address the methods and techniques used to predict bridge pier scour. Up to the present, extensive research has been carried out for pier scour depth prediction. Different modeling techniques have been applied to achieve better prediction. This paper presents a new soft computing technique called gene-expression programming (GEP) for pier scour depth prediction using laboratory data. A functional relationship has been established using GEP and its performance is compared with other artificial intelligence (AI)-based techniques such as artificial neural networks (ANNs) and conventional regression-based techniques. Laboratory data containing 529 datasets was divided into calibration and validation sets. The performance of GEP was found to be highly satisfactory and encouraging when compared to regression equations but was slightly inferior to ANN. This slightly inferior performance of GEP compared to ANN is offset by its capability to provide compact and explicit mathematical expression for bridge scour. This advantage of GEP over ANN is the main motivation for this work. The resulting GEP models will add to the existing literature of AI-based inductive models for bridge scour modeling.

Prediction of Scour at Bridge Pier Foundations Founded on Rock and Other Earth Materials

2000 ◽  
Vol 1696 (1) ◽  
pp. 67-70 ◽  
Author(s):  
George W. Annandale
Keyword(s):  
Laboratory Data ◽  
Bridge Pier ◽  
Scour Depth ◽  
Stream Power ◽  
Index Method ◽  
Pier Scour ◽  
Bridge Pier Scour

The erodibility index method, which can be used to predict scour thresholds for rock and other earth materials, is described. The scour threshold is defined by a relationship between the erodibility index and stream power that is based on analysis of field and laboratory data. An explanation of how the method is applied to calculate scour depth is presented, followed by a case study to calculate bridge pier scour.

Numerical study of the bridge pier scour using gene expression programming

2019 ◽  
Vol 7 (4) ◽  
pp. 287-294
Author(s):  
Layla Ali Mohammed Saleh ◽  
Sumayah Amal Al-din Majeed ◽  
Fatin Abd el-kadhium M. Alnasrawi
Keyword(s):  
Gene Expression ◽  
Numerical Study ◽  
Gene Expression Programming ◽  
Bridge Pier ◽  
Pier Scour ◽  
Bridge Pier Scour

Discussion: Bridge pier scour prediction by gene expression programming

2014 ◽  
Vol 167 (6) ◽  
pp. 368-369 ◽  
Author(s):  
Mujahid Khan ◽  
Hazi M. Azamathulla ◽  
Mohammad Tufail ◽  
Aminuddin Ab Ghani ◽  
Charles Neill ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Programming ◽  
Bridge Pier ◽  
Pier Scour ◽  
Bridge Pier Scour

Bridge pier scour prediction by gene expression programming

2012 ◽  
Vol 165 (9) ◽  
pp. 481-493 ◽  
Author(s):  
Mujahid Khan ◽  
Hazi M. Azamathulla ◽  
Mohammad Tufail ◽  
Aminuddin Ab Ghani
Keyword(s):  
Gene Expression ◽  
Gene Expression Programming ◽  
Bridge Pier ◽  
Pier Scour ◽  
Bridge Pier Scour

NF-GMDH-Based self-organized systems to predict bridge pier scour depth under debris flow effects

2017 ◽  
Vol 36 (5) ◽  
pp. 589-602 ◽  
Author(s):  
Mohammad Najafzadeh ◽  
Farid Saberi-Movahed ◽  
Saeed Sarkamaryan
Keyword(s):  
Debris Flow ◽  
Bridge Pier ◽  
Scour Depth ◽  
Pier Scour ◽  
Self Organized ◽  
Flow Effects ◽  
Bridge Pier Scour

scholarly journals ANFIS-based approach for scour depth prediction at piers in non-uniform sediments

2009 ◽  
Vol 12 (3) ◽  
pp. 303-317 ◽  
Author(s):  
M. Muzzammil ◽  
M. Ayyub
Keyword(s):  
Fuzzy Inference ◽  
Bridge Piers ◽  
Scour Depth ◽  
Fuzzy Inference Systems ◽  
Foundation Design ◽  
Pier Scour ◽  
Depth Prediction ◽  
Alternative Approach ◽  
Inference Systems ◽  
Bridge Pier Scour

An estimation of scour depth is a prerequisite for the efficient foundation design of important hydraulic structures such as bridge piers and abutments. Most of the scour depth prediction formulae available in the literature have been developed based on the analysis of the laboratory/field data using statistical methods such as the regression method (RM). Conventional statistical analysis is generally replaced in many fields of engineering by the alternative approach of artificial neural networks (ANN) and adaptive network-based fuzzy inference systems (ANFIS). These recent techniques have been reported to provide better solutions in cases where the available data is incomplete or ambiguous by nature. An attempt has been made to compare the performance of ANFIS over RM and ANN in modeling the depth of bridge pier scour in non-uniform sediments. It has been found that the ANFIS performed best amongst all these methods.

scholarly journals A Comparative Study on the Efficiency of Reliability Methods for the Probabilistic Analysis of Local Scour at a Bridge Pier in Clay-Sand-Mixed Sediments

Modelling ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 63-77
Author(s):  
Jafar Jafari-Asl ◽  
Mohamed El Amine Ben Seghier ◽  
Sima Ohadi ◽  
You Dong ◽  
Vagelis Plevris
Keyword(s):  
Comparative Study ◽  
Probabilistic Analysis ◽  
Safety Evaluation ◽  
Local Scour ◽  
Bridge Pier ◽  
Pier Scour ◽  
Depth Prediction ◽  
Reliability Method ◽  
Reliability Methods ◽  
Bridge Pier Scour

In this work, the performance of reliability methods for the probabilistic analysis of local scour at a bridge pier is investigated. The reliability of bridge pier scour is one of the important issues for the risk assessment and safety evaluation of bridges. Typically, the depth prediction of bridge pier scour is estimated using deterministic equations, which do not consider the uncertainties related to scour parameters. To consider these uncertainties, a reliability analysis of bridge pier scour is required. In the recent years, a number of efficient reliability methods have been proposed for the reliability-based assessment of engineering problems based on simulation, such as Monte Carlo simulation (MCS), subset simulation (SS), importance sampling (IS), directional simulation (DS), and line sampling (LS). However, no general guideline recommending the most appropriate reliability method for the safety assessment of bridge pier scour has yet been proposed. For this purpose, we carried out a comparative study of the five efficient reliability methods so as to originate general guidelines for the probabilistic assessment of bridge pier scour. In addition, a sensitivity analysis was also carried out to find the effect of individual random variables on the reliability of bridge pier scour.

Composite reliability model for local scour around cylindrical bridge piers

2001 ◽  
Vol 28 (3) ◽  
pp. 520-535 ◽  
Author(s):  
A Melih Yanmaz ◽  
Ozgur Cicekdag
Keyword(s):  
Joint Probability ◽  
Bridge Pier ◽  
External Loading ◽  
Bridge Scour ◽  
Reliability Model ◽  
Pier Scour ◽  
Static Resistance ◽  
Bridge Pier Scour ◽  
Available Information ◽  
Composite Reliability

Bridge scour is an extremely complex phenomenon because of the random characteristics of sediment laden flow in close proximity to piers and abutments. This occurrence leads to high uncertainties and unavoidable risk in bridge pier and abutment design. In this study, a composite reliability model is developed for the reliability assessment of bridge pier scour using static resistance – loading interference. Based on the physical interpretation of the phenomenon and a statistical analysis of the available information, the relative maximum scour depth (corresponding to the minimum required relative pier footing elevation) and the linear combination of the relative approach flow depth and flow Froude number are defined as the system resistance and external loading, respectively. By examining a set of laboratory and field data, a two-parameter bivariate lognormal distribution is found to represent the joint probability density function of resistance and loading. Reliability expressions are developed in terms of resistance. Use of the model is illustrated in a practical application in which a relationship is obtained between the reliability and safety factors under various return periods. This information is of importance in decision making.Key words: reliability, bridge pier, scour, resistance, loading, safety factor, return period.

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