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Approximate and analytic flow models for leak detection and identification

Abstract

The article presents a comprehensive quantitative comparison of four analytical models that, in different ways, describe the flow process in transmission pipelines necessary in the task of detecting and isolating leaks. First, the analyzed models are briefly presented. Then, a novel model comparison framework was introduced along with a methodology for generating data and assessing diagnostic effectiveness. The study presents basic assumptions, experimental conditions and considered scenarios. Finally, the quality of the model-based diagnostic estimators is assessed, focusing on their bias, standard deviation, and computational complexity. Here, several optimality criteria are used as detailed indicators of the quality and performance of the estimators in a multi-criteria Pareto optimality assessment.

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Accepted or Published Version
DOI:
Digital Object Identifier (open in new tab) 10.61822/amcs-2024-0028
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Creative Commons: CC-BY-NC-ND open in new tab

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Details

Category:
Articles
Type:
artykuły w czasopismach
Published in:
International Journal of Applied Mathematics and Computer Science no. 34, pages 391 - 407,
ISSN: 1641-876X
Language:
English
Publication year:
2024
Bibliographic description:
Tatara M., Kowalczuk Z.: Approximate and analytic flow models for leak detection and identification// International Journal of Applied Mathematics and Computer Science -Vol. 34,iss. 3 (2024), s.391-407
DOI:
Digital Object Identifier (open in new tab) 10.61822/amcs-2024-0028
Sources of funding:
  • Statutory activity/subsidy
Verified by:
Gdańsk University of Technology

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