DATA-DRIVEN ASSESSMENT OF WALL SHEAR FORCES IN BOX CULVERTS UNDER VARIABLE HYDRAULIC CONDITIONS: A CASE STUDY OF OGBA RIVER, BENIN-CITY, EDO STATE
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This research investigates the structural behavior of a reinforced concrete box culvert under variable hydraulic conditions typical of urban drainage systems in Benin City. The study addresses the problem of culvert deterioration caused by internal sedimentation, foundation scour and variable headwater levels. The aim of the research was to develop a data-driven model that links observable hydraulic conditions to quantifiable structural responses, thereby improving performance evaluation and maintenance prioritization.To achieve this, field investigations were conducted at the Ogba River drainage corridor to determine practical ranges for the three hydraulic variables. Response Surface Methodology (RSM) was employed to generate a design matrix with 20 experimental runs. Finite Element Analysis (FEA) was performed for each run to simulate the resulting wall shear force response. Six center points were observed in the matrix to ensure adequate degrees of freedom for estimating pure error and testing lack of fit in the ANOVA. The RSM model achieved a coefficient of determination (R²) of 98.6%, confirming the model’s high predictive accuracy. Results showed that the headwater level had the most significant effect on the wall shear force. The effect of the headwater level on the wall shear force is amplified by its interaction with foundation scour. Optimization analysis identified critical combinations of the variables that produced maximum WSF values greater than 70 kN/m, indicating the threshold beyond which the culvert’s structural integrity may be compromised. The developed model provides a quantitative framework for predicting wall shear forces based on measurable hydraulic conditions, offering a practical decision-support tool for culvert maintenance and management in resource-constrained urban environments such as Benin City.
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