Application of big data analysis technique on high-velocity airblast atomization: Searching for optimum probability density function

dc.contributor.authorUrbán, Andráscs
dc.contributor.authorGroniewski, Axelcs
dc.contributor.authorMalý, Milancs
dc.contributor.authorJózsa, Viktorcs
dc.contributor.authorJedelský, Jancs
dc.coverage.issue1cs
dc.coverage.volume273cs
dc.date.accessioned2020-08-04T11:02:40Z
dc.date.available2020-08-04T11:02:40Z
dc.date.issued2020-08-01cs
dc.description.abstractIn this paper, the droplet size distributions of high-velocity airblast atomization were analyzed. The spray measurement was performed by a Phase-Doppler anemometer at several points and different diameters across the spray for diesel oil, light heating oil, crude rapeseed oil, and water. The atomizing gauge pressure and the liquid preheating temperature varied from 0.3 to 2.4 bar and 25 to 100 °C, respectively. Approximately 400 million individual droplets were recorded; therefore, a big data evaluation technique was applied. 18 of the most commonly used probability density functions (PDF) were fitted to the histogram of each measuring point and evaluated by their relative log-likelihood. Among the three-parameter PDFs, Generalized Extreme Value and Burr PDFs provided the most desirable result to describe a complete drop size distribution. With restriction to two-parameter PDFs, the Nakagami PDF unexpectedly outperformed all the others, including Weibull (Rosin-Rammler) PDF, which is commonly used in atomization. However, if the spray is characterized by a single value, such as the Sauter Mean Diameter, i.e. an expected value-like parameter is of primary importance over the distribution, Gamma PDF is the best option, used in several papers of the atomization literature.en
dc.formattextcs
dc.format.extent1-12cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationFUEL. 2020, vol. 273, issue 1, p. 1-12.en
dc.identifier.doi10.1016/j.fuel.2020.117792cs
dc.identifier.issn0016-2361cs
dc.identifier.other163951cs
dc.identifier.urihttp://hdl.handle.net/11012/193501
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofFUELcs
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S0016236120307870cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/0016-2361/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectBig dataen
dc.subjectAirblasten
dc.subjectRapeseed oilen
dc.subjectPDAen
dc.subjectProbability density functionen
dc.subjectLikelihooden
dc.titleApplication of big data analysis technique on high-velocity airblast atomization: Searching for optimum probability density functionen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-163951en
sync.item.dbtypeVAVen
sync.item.insts2020.08.04 13:02:40en
sync.item.modts2020.08.04 12:43:33en
thesis.grantorVysoké učení technické v Brně. Fakulta strojního inženýrství. EÚ-odbor termomechaniky a techniky prostředícs
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
1s2.0S0016236120307870main.pdf
Size:
12.79 MB
Format:
Adobe Portable Document Format
Description:
1s2.0S0016236120307870main.pdf