Probabilistic Prediction of Scouring around Piers using Monte Carlo Simulation

Abstract

Abstract Assessing local scour around a pier is important in terms of creating a good design for any bridge. Many equations are available to predict local scour around pier, though the reliability of these must be checked using statistical tools. A Monte Carlo simulation was thus used in this study to check the probabilistic accuracy of lab equations of local scour around a test pier so that the observation data and prediction equation were both tested probabilistically before use in simulation. The parameters of the prediction equation were specified based on the probabilistic and deterministic variables, with average velocity, critical velocity, water depth, median bed diameter, and Froude number being the unknown variables. The deterministic variables were the diameter of the pier and the spacing from the pier to the abutment. The optimum number of iterations utilised in the Monte Carlo simulation was also investigated based on standard deviation. The independent terms of the prediction equation for the simulation model were derived based on the original distribution of the equation of local scour and the relevant statistical values. The distribution of observation data of local scour was assumed to be normal, while the simulation model was lognormal. The input data was then used to check the probabilistic outcomes of the deterministic equation. The deterministic equation of local scour gave the results at the corresponding confidence level of about 20%, depending on the curve of a cumulative probability distribution. The probabilistic results were thus deemed preferable for the computation of local scour around the pier.