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The measurement of flow velocity distribution
Includes bibliography.
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Electrical Engineering
2015
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| _version_ | 1867613236623310848 |
|---|---|
| access_status_str | Open Access |
| author | Dann, Michael Stephen |
| author2 | Greene, J R |
| author_browse | Dann, Michael Stephen Greene, J R |
| author_facet | Greene, J R Dann, Michael Stephen |
| author_sort | Dann, Michael Stephen |
| collection | Thesis |
| description | Includes bibliography. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/15438 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:56.154Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/15438 The measurement of flow velocity distribution Dann, Michael Stephen Greene, J R Electrical Engineering Includes bibliography. A method for the improvement of the range and accuracy achieved by the cross-correlation flowmeter is investigated. The principles of the flowmeter operation and fundamental digital signal processing techniques are reviewed. The process of the Fourier transform deconvolution is investigated. Computer simulation of the flow system is described and is shown to require impractical amounts of computer time to achieve the necessary averaging times. Consequently, correlation and velocity profile measurements are made from an experimental flow rig. A waveform analysis program is used to analyse these measurements. The Fourier transform deconvolution is shown in this case to have poor noise immunity. For this reason, an alternative method of Bayesian deconvolution is investigated. The correlation functions measured from the experimental flow rig are deconvolved using the Bayesian deconvolution algorithm. The resulting transit time distribution is shown to converge to the transit time distribution obtained from the velocity profile measurements. From an analysis of the flow signals the velocity distribution of the flow may thus be found. 2015-11-30T08:23:45Z 2015-11-30T08:23:45Z 1981 Master Thesis Masters MSc (Eng) http://hdl.handle.net/11427/15438 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Electrical Engineering Dann, Michael Stephen The measurement of flow velocity distribution |
| thesis_degree_str | Master's |
| title | The measurement of flow velocity distribution |
| title_full | The measurement of flow velocity distribution |
| title_fullStr | The measurement of flow velocity distribution |
| title_full_unstemmed | The measurement of flow velocity distribution |
| title_short | The measurement of flow velocity distribution |
| title_sort | measurement of flow velocity distribution |
| topic | Electrical Engineering |
| url | http://hdl.handle.net/11427/15438 |
| work_keys_str_mv | AT dannmichaelstephen themeasurementofflowvelocitydistribution AT dannmichaelstephen measurementofflowvelocitydistribution |