Dataset for: Morphology of flashing feeds at critical fluid properties in larger pipes

DOI

This data set contains cross-sectional averaged vapor fraction data obtained for flashing refrigerant in the horizontal feed section (inner pipe diameter of 200 mm) of the TERESA facility. The data was obtained with the Wire-mesh Sensor Framework GUI (Version 1.3.0). The archive 'void' contains .epst-files which are organized as a two column table (ASCII). The first column denotes the time step (in seconds), the second column is the cross-sectional averaged vapor fraction in percent.

Allocation of the files to the operational conditions is included separate .csv-file (overview.csv), which contains 12 columns for each measurement. Here the averaged values of the .epst-files are included as well.

In this study, two wire-mesh sensors were operated simultaneously. WMS1 (_X_Sensor_1.epst) was located in an axial distance of L = 2.5 D from the flash nozzle and WMS2 (_Y_Sensor_2.epst) was located L = 17.5 D away from the flash nozzle.  

Identifier
DOI https://doi.org/10.14278/rodare.419
Related Identifier IsIdenticalTo https://www.hzdr.de/publications/Publ-31573
Related Identifier IsReferencedBy https://www.hzdr.de/publications/Publ-31636
Related Identifier IsPartOf https://doi.org/10.14278/rodare.418
Related Identifier IsPartOf https://rodare.hzdr.de/communities/fwd
Related Identifier IsPartOf https://rodare.hzdr.de/communities/rodare
Related Identifier IsPartOf https://rodare.hzdr.de/communities/topflow
Metadata Access https://rodare.hzdr.de/oai2d?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:rodare.hzdr.de:419
Provenance
Creator Döß, Alexander (ORCID: 0000-0002-4373-849X); Schubert, Markus ORCID logo; Hampel, Uwe ORCID logo
Publisher Rodare
Contributor Wiezorek, Michael
Publication Year 2020
Rights Creative Commons Attribution 4.0 International; Open Access; https://creativecommons.org/licenses/by/4.0/legalcode; info:eu-repo/semantics/openAccess
OpenAccess true
Contact https://rodare.hzdr.de/support
Representation
Resource Type Dataset
Discipline Life Sciences; Natural Sciences; Engineering Sciences