Assessing Viscoelastic Parameters of Polymer Pipes via Transient Signals and Artificial Neural Networks-Reference-Cited by-同舟云学术

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

Published:2024-09-06 Issue: Volume:17 Page:74
ISSN:
Container-title:The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024)
language:
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Author:

Rahmanshahi Mostafa¹^ORCID,Duan Huan-Feng¹^ORCID,Keramat Alireza¹^ORCID,Rad Nasim Vafaei²^ORCID,Nadian Hossein Azizi³^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China

2. Department of Water Structures, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz 6135783151, Iran

3. Department of Civil, Environmental, Architectural Engineering and Mathematics, University of Brescia, Via Branze 43, 25123 Brescia, Italy

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/69/1/74/pdf

Reference6 articles.

1. Pipeline Leak Diagnosis Based on Leak-Augmented Scalograms and Deep Learning;Siddique;Eng. Appl. Comput. Fluid Mech.,2023

2. Leak Detection and Size Identification in Fluid Pipelines Using a Novel Vulnerability Index and 1-D Convolutional Neural Network;Ahmad;Eng. Appl. Comput. Fluid Mech.,2023

3. Determination of the Creep Function of Viscoelastic Pipelines Using System Resonant Frequencies with Hydraulic Transient Analysis;Gong;J. Hydraul. Eng.,2016

4. Multistage Frequency-Domain Transient-Based Method for the Analysis of Viscoelastic Parameters of Plastic Pipes;Pan;J. Hydraul. Eng.,2020

5. Estimating Viscoelasticity of Pipes with Unknown Leaks;Wang;Mech. Syst. Signal Process.,2020