Investigation of Local Scour Factors under Pipelines Using Artificial Neural Network Algorithms

• Main Authors: M. Pourmirza, A. Kamanbedast
• Format: Article
• Language: fas
• Published: Isfahan University of Technology 2019-12-01
• Series: علوم آب و خاک
• Subjects: scour; artificial neural network; neurosolution5 software; multilayer perceptron model (mlp); shields parameter
• Online Access: http://jstnar.iut.ac.ir/article-1-3560-en.html

Occurrence of local scour is one of the most significant causes of damage to the pipes. Therefore, safe and economical design of pipes in the flow path requires a good estimate. In this study, based on the important and effective parameters in the scouring phenomenon, in order to develop educational patterns according to the data obtained in the laboratory of Ahvaz Islamic Azad University, models based on artificial neural networks were created with the NeuroSolution5 software. MLP, GFF and RBF were the models used in this study; after comparing, MLP was selected as the basis for our study. Finally, the effect of each parameter on scouring was determined using the  artificial neural networks technique, based on which the  shields parameter with a very high effect (more than 95 percent) was determined as one of the most effective causes of the local scour.