Iranian Journal of Irrigation & Drainage

Iranian Journal of Irrigation & Drainage

Forecasting the Local Scour Depth around Cylindrical Bridge Foundations on Cohesive Soil Utilizing Meta Models.

Document Type : Original Article

Authors
mahdi Soltani Sotobad 1
Tohid Omidpour Alavian 2
Nazila kardan 3
1 Master's Student, Civil Engineering Water and Hydraulic Structures, Azarbaijan Shahid Madani University,
2 Ph.D. Student, Civil Engineering - Water and Hydraulic Structures, Maragheh University
3 Associate Professor, Department of Civil Engineering, Azarbaijan Shahid Madani University,
Abstract
Scour is the result of erosion from river water flow, particularly prevalent around bridge foundations, and is known to be a process that varies with time. If the depth of scour is inaccurately estimated, it can lead to insufficient or cost-ineffective foundation designs, raising the potential for structural failure. Therefore, the investigation and analysis of efficient methods for predicting scour depth tools for analyzing and forecasting scour. Implementing these sophisticated techniques can significantly improve the efficiency of protective strategies and designs, ultimately enhancing the safety and stability of bridge structures. Consequently, this study assessed the performance of SVM, QNET, and ANN methodologies in predicting local scour depth around cylindrical bridge foundations on cohesive soil through the analysis of 122 sets of laboratory data. The objective of this evaluation was to ascertain the effectiveness of these methods in estimating scour depth and augmenting the performance of bridge structures. The geometric and hydraulic parameters utilized in this study encompass the foundation Froude number, dimensionless approaching flow depth, dimensionless sediment particle size, and bed shear strength. The findings revealed that these methodologies yielded precise forecasts in 96% of instances. The QNET model outperformed SVM and ANN in 92% of scenarios, enhancing prediction accuracy to 98%. In contrast, SVM demonstrated satisfactory outcomes in 80% of instances, while ANN achieved this in 85% of cases. However, QNET showcased superiority over the other methodologies across all scenarios. Sensitivity analysis highlighted the foundation Froude number, exerting an 82% influence, as the pivotal factor in scour depth determination, with potential erosion depth alterations of up to 30%. Ultimately, this study offers a precise and efficient scour prediction solution, aiding engineers in crafting more durable and cost-effective bridge designs.
Keywords
Scour
Bridge piers
Erosion depth
Cohesive soil
Meta Models
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Iranian Journal of Irrigation & Drainage
Volume 19, Issue 2 - Serial Number 111
May and June 2025
Pages 275-290