Trifunovic, N: Pattern Recognition for Reliability Assessmen
Language: English
Published by CRC Press, 2017
- Hardcover
- New
Seller: moluna, Greven, Germanymoluna
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Condition: New
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Add to basketItem description from seller
Nemanja. Trifunovic is Associate Professor of Water Supply at UNESCO-IHE Institute for Water Education. He is specialist in the field of Water Transport and Distribution in general and in application of computer models in urban distribution networks in part.
Seller Inventory # 595404849
- Title
- Trifunovic, N: Pattern Recognition for Reliability Assessmen
- Author
- N. Trifunovic
- Publisher
- CRC Press
- Publication year
- 2017
- Condition
- New
- Binding
- Gebunden
- Language
- English
- ISBN 10
- 1138474444
- ISBN 13
- 9781138474444
This study investigates the patterns that describe reliability of water distribution networks focusing to the node connectivity, energy balance, and economics of construction, operation and maintenance. A number of measures to evaluate the network resilience has been developed and assessed to arrive at more accurate diagnostics of regular and irregular demand scenarios. These measures have been proposed as a part of the methodology for snap-shot assessment of network reliability based on its configuration and hydraulic performance.
Practical outcome of the research is the decision support tool for reliability-based design of water distribution networks. This computer package named NEDRA (Network Design and Reliability Assessment) consists of the modules for network generation, filtering, initialisation, optimisation, diagnostics and cost calculation, which can be used for sensitivity analyses of single network layout or assessments of multiple layouts.
The study concludes that none of the analysed aspects develops clear singular patterns. Nevertheless, the proposed network buffer index (NBI) and the hydraulic reliability diagram (HRD) as visual representation of the network resilience give sufficient snap-shot pointing the composition of the index value, and displaying possible weak points in the network that can be hidden behind the averaged values of various reliability measures.
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