Flow Modelling and Control in Pipeline Systems

A Formal Systematic Approach
 
 
Springer (Verlag)
  • erscheint ca. am 7. Dezember 2020
 
  • Buch
  • |
  • Hardcover
  • |
  • XI, 218 Seiten
978-3-030-59245-5 (ISBN)
 

This book introduces novel methods for leak and blockage detection in pipelines. The leak happens as a result of ageing pipelines or extreme pressure forced by operational error or valve rapid variation. Many factors influence blockage formation in pipes like wax deposition that leads to the formation and eventual growth of solid layers and deposition of suspended solid particles in the fluids. In this book, initially, different categories of leak detection are overviewed. Afterwards, the observability and controllability of pipeline systems are analysed. Control variables can be usually presented by pressure and flow rates at the start and end points of the pipe. Different cases are considered based on the selection of control variables to model the system. Several theorems are presented to test the observability and controllability of the system. In this book, the leakage flow in the pipelines is studied numerically to find the relationship between leakage flow and pressure difference. Removing leakage completely is almost impossible; hence, the development of a formal systematic leakage control policy is the most reliable approach to reducing leakage rates.

1st ed. 2021
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • Für Beruf und Forschung
  • 4
  • |
  • 67 farbige Abbildungen, 4 s/w Abbildungen
  • |
  • 67 Illustrations, color; 4 Illustrations, black and white; XI, 218 p. 71 illus., 67 illus. in color.
  • Höhe: 23.5 cm
  • |
  • Breite: 15.5 cm
978-3-030-59245-5 (9783030592455)
10.1007/978-3-030-59246-2
weitere Ausgaben werden ermittelt
The importance of pipeline transportation.- A review on different pipeline defect detection techniques.- Modelling of pipeline flow.- Theory and applications of Fuzzy logic Controller for Flowing Fluids.- Basic concepts of neural networks and deep learning and their applications for pipeline damage detection.- Leakage modelling for pipeline.- Blockage detection in Pipeline.- Leakage Detection in Pipeline Based on Second Order Extended Kalman Filter Observer.- Control of flow rate in heavy-oil pipelines using PD and PID controller.

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