A Proposal for Prediction of Pipe Wear Rate Using Neural Network Techniques

摘要

Pipe wear can cause leakage of concretes or other particle-laden liquids, which results in increased production costs, and may also cause environmental damage like contaminating ground. The computer simulations are powerful tools frequently used today in many important fields. In this work, a neural network technique was first proposed to predict the pipe wear rates of concrete feeding pipe. The neural network method was applied for modeling pipes made of different materials and was chosen to develop a neural network model. Model adequacy was established both by visual inspection and statistical techniques.