Comparative Analysis of 1D and 2D Modeling Approaches for Scour Depth Estimation: A Case Study of the Kelanisiri Bridge, Sri Lanka
Journal Title: Journal of Civil and Hydraulic Engineering - Year 2024, Vol 2, Issue 3
Abstract
The scouring process, characterised by the erosion of sediment around bridge piers due to fluid flow, poses a significant risk to the structural integrity of bridges. Scour depth, defined as the vertical distance from the initial riverbed level to the bottom of the scour hole, is driven by the formation of vortices near bridge piers. Mitigating scour damage after it has advanced to a critical stage is often more disruptive and costly than preemptive measures based on accurate predictions. In response to this challenge, a range of one-dimensional (1D) and two-dimensional (2D) numerical modelling techniques has been developed for scour depth estimation around bridge piers. Among the available methods, the Hydrologic Engineering Center's River Analysis System (HEC-RAS) is widely employed, with the majority of studies focusing on the 1D modelling approach. The current study evaluates the relative efficacy of 1D and 2D models using the case of the Kelanisiri Bridge, which traverses the Kelani River in Sri Lanka. The performance of the 1D model was assessed by comparing predicted water levels at an intermediate river gauge with field data, while the 2D model was calibrated and validated against observed riverbed levels. Both approaches were applied to estimate scour depths following the 2016 flood event. The findings revealed that the 2D HEC-RAS model provided a superior match with observed field data when compared to the 1D model, achieving a coefficient of determination (R2) of 0.98 and a root mean square error (RMSE) of 0.13, indicating a higher degree of accuracy and reliability. As a result, the 2D model is recommended as the more effective approach for predicting scour depth around bridge piers. Further validation of these numerical results through scaled laboratory physical modelling is recommended to ensure greater accuracy in future predictive efforts.
Authors and Affiliations
Ashvinie Thembiliyagoda, Kasun De Silva, Nimal Wijayaratna
Development of an Intelligent Monitoring Framework for Concrete Tensioning Quality Based on the Radial Basis Function Neural Network
Traditional tensioning monitoring techniques for prestressed concrete structures often exhibit limitations in real-time performance, accuracy, and adaptability to complex stress distributions. To address these challenges...
Assessment of Fatigue Life in H-Type Bridge Hangers Subjected to Torsional Vibration
The fatigue life of H-type rigid hangers, crucial components in bridge engineering, is investigated in this study, particularly under the influence of torsional vibrations induced by wind loads. These hangers, integral t...
Numerical and Experimental Investigation of Hail Impact-Induced Dent Depth on Steel Sheets
The impact of artificial hailstones on G300 steel sheets with varying thicknesses has been systematically investigated to evaluate the resulting dent depths. Two distinct methods for producing simulated hailstones were e...
Calculation of Circumferential Stress in Steel Epoxy Sleeve-Reinforced Pipelines Under Internal Pressure
To address the lack of clear formulae for calculating the circumferential stress in steel epoxy sleeve-reinforced pipelines under internal pressure, this study constructs a mechanical model based on the specific stress c...
Evaluation of Rainwater Harvesting and Bio-pore Infiltration Holes for Flood Mitigation and Soil Conservation
Rainwater harvesting (RH) techniques, specifically the implementation of Bio-pore Infiltration Holes (BIH), have been investigated as cost-effective and practical methods for managing surface runoff and mitigating flood...