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http://bura.brunel.ac.uk/handle/2438/1616
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kang, H | - |
dc.contributor.author | Yang, QP | - |
dc.contributor.author | Butler, C | - |
dc.coverage.spatial | 5 | en |
dc.date.accessioned | 2008-02-11T16:21:25Z | - |
dc.date.available | 2008-02-11T16:21:25Z | - |
dc.date.issued | 1998 | - |
dc.identifier.citation | IEEE Transactions on Instrumentation and Measurement. 47 (5): 1379-1384 | en |
dc.identifier.issn | 0018-9456 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/1616 | - |
dc.description.abstract | This paper discusses the modeling of the flue gas flow in industrial ducts and stacks using artificial neural networks (ANN's). Based upon the individual velocity and other operating conditions, an ANN model has been developed for the measurement of the volume flow rate. The model has been validated by the experiment using a case-study power plant. The results have shown that the model can largely compensate for the nonrepresentativeness of a sampling location and, as a result, the measurement accuracy of the flue gas flow can be significantly improved. | en |
dc.format.extent | 376670 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | IEEE | en |
dc.subject | Flow measurement | en |
dc.subject | Flow simulation | en |
dc.subject | Neural nets | en |
dc.subject | Pipe flow | en |
dc.title | Modelling and measurement accuracy enhancement of flue gas flow using neural networks | en |
dc.type | Research Paper | en |
dc.identifier.doi | http://dx.doi.org/10.1109/19.746614 | - |
Appears in Collections: | Mechanical and Aerospace Engineering Advanced Manufacturing and Enterprise Engineering (AMEE) Dept of Mechanical and Aerospace Engineering Research Papers |
Files in This Item:
File | Description | Size | Format | |
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Modelling and Measurement Accuracy Enhancement of Flue Gas Flow Using Neural Networks.pdf | 144.12 kB | Adobe PDF | View/Open |
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