Practical Design of Stepped Spillways using Fuzzy Inference System

Abstract

Abstract Climate change causes flooding in some regions and increases the need for spillways in dam reservoirs. Energy-dissipating pools or flip bucket structures dissipate the flow energy downstream of conventional spillways. Recently, stepped spillways have been widely used to dissipate the flow of energy downstream. Flows on the stepped spillways are complex and advanced techniques such as fuzzy, neuro-fuzzy, artificial neural network (ANN), and genetic programming (GP) models are required to calculate energy dissipation ratios. Fuzzy logic is superior to the other methods from the aspect of considering physical processes about examined problems. In this study, energy dissipation over stepped spillways is calculated using the fuzzy inference system in Python programming language. Experimental data by different researchers are used to model stepped spillways. Two new parameters, approach channel and step-top geometric ratios, are used to obtain energy dissipation ratios on stepped spillways. Fuzzy logic represents good results with low mean percentages and absolute errors (-1.69% and 2.00), and the produced Python function using the fuzzy inference system can be applied easily to different flow conditions and stepped spillways.