Abstract
Cavitation is a complex multiphase phenomenon, where the production of vapor bubbles leads to opaqueness of the flow. While it is nearly impossible to visualize the interior of the cavitation region with visible light, we show that with X-ray computed tomography it is possible to obtain the time-averaged void fraction distribution in an axisymmetric converging-diverging nozzle (venturi). This technique is based on the amount of energy absorbed by the material, based on its density and thickness. Time-averaged 3D reconstruction of the X-ray images is used (i) to distinguish between vapor and liquid phase, (ii) to get radial geometric features of the flow, and (iii) to quantify the local void fraction. The results show the presence of intense cavitation at the walls of the venturi, and the vapor fraction decreases downstream of the venturi with the vapor cloud.
Original language | English |
---|---|
Title of host publication | Proceedings of the 10th International Symposium on Cavitation (CAV2018) |
Editors | Joseph Katz |
Place of Publication | New York, NY, USA |
Publisher | ASME |
Pages | 1104-1108 |
ISBN (Electronic) | 978-0-7918-6185-1 |
DOIs | |
Publication status | Published - 2018 |
Event | CAV2018: 10th International Symposium on Cavitation - Baltimore, United States Duration: 14 May 2018 → 16 May 2018 |
Conference
Conference | CAV2018: 10th International Symposium on Cavitation |
---|---|
Country/Territory | United States |
City | Baltimore |
Period | 14/05/18 → 16/05/18 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- venturi
- X-ray computed tomography
- cloud cavitation
Fingerprint
Dive into the research topics of 'X-ray computed tomography of cavitating flow in a converging-diverging nozzle'. Together they form a unique fingerprint.Datasets
-
Complete dataset for Converging-Diverging Nozzle
Jahangir, S. (Creator), Hogendoorn, W. J. (Creator) & Poelma, C. (Creator), TU Delft - 4TU.ResearchData, 14 Sept 2018
DOI: 10.4121/UUID:A8A8EECD-C9AC-4699-B01D-98F3393713C9
Dataset/Software: Dataset
-
X-ray dataset for cavitating Converging-Diverging Nozzle
Jahangir, S. (Creator), Wagner, E. C. (Creator), Mudde, R. F. (Creator) & Poelma, C. (Creator), TU Delft - 4TU.ResearchData, 9 Jul 2020
DOI: 10.4121/UUID:1C4FDB71-94ED-4E24-A80E-2FEC718C78C1
Dataset/Software: Dataset