Work

Assessing Viscoelastic Parameters of Polymer Pipes via Transient Signals and Artificial Neural Networks

Year: 2024

Type: conference-paper

Abstract: This study presents a soft-computing-based method for determining polymer pipelines’ creep function parameters (CFPs) and pressure wave speeds (PWSs) through transient flow analysis. To this end, first, a numerical model for transient flow in polymer pipes was developed in the time domain. Then, by considering a pipeline with a specific geometry, 2000 transient flow signals were generated for different CFPs and PWSs. The amplitudes obtained by transforming the time-domain pressure signals to the frequency domain using the fast Fourier transform algorithm are the inputs for an artificial neural network model. The results showed that the proposed approach accurately estimated the creep function of the polymer pipes.

DOI: 10.3390/engproc2024069074

Authors: Mostafa Rahmanshahi, Huan-Feng Duan, Alireza Keramat, Nasim Vafaei Rad, Hossein Azizi Nadian

Institutions: Hong Kong Polytechnic University, Shahid Chamran University of Ahvaz, University of Brescia

Language: English

Topic: Water Systems and Optimization

Subfield: Civil and Structural Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Funder: Università degli Studi di Brescia

OpenAlex ID: W4402320210

FWCI: 3.228

Cites: 7

Cited by: 2

Related to: 10