Computation of design coefficients in ogee-crested spillway structure using GEP and regression models

Abstract

The ogee-crested spillway is a passage in a dam through which the design flood could be disposed of safely to the downstream. Spillways of improper design or insufficient capacities have caused failures of dams. Therefore, the spillway must be hydraulically and structurally adequate. This paper presents Gene-Expression Programming (GEP) models as an alternative approach to prediction of design coefficients in ogee-crested spillway structure. New formulations for prediction of design coefficient are developed using GEP and regression models. The performance of GEP was found to be satisfactory and encouraging when compared with regression model in predicting of design coefficient. This capability of GEP makes it unique and more effective when compared with regression models evaluated in this paper. The superior performance of GEP is attributed to the powerful Artificial Intelligence (AI) techniques for computer learning inspired by natural evolution to find the appropriate mathematical model (expression) to fit a set of fits. This study highlights the utility of AI-based models with a view to increase their usage by engineers and planners working on spillway design problems.