2015
DOI: 10.1016/j.ces.2014.09.036
|View full text |Cite
|
Sign up to set email alerts
|

An integrative image measurement technique for dense bubbly flows with a wide size distribution

Abstract: A robust image analysis approach for highly turbulent bubbly flows is proposed. It can resolve both in-focus and out-of focus bubbles over a wide size range. It can segment individual bubble from large clusters in high void fraction images. The approach was validated using both synthetic bubble images and experimental data. It allows real time analysis of two-phase flows in many industrial applications. a b s t r a c tThe measurements of bubble size distribution are ubiquitous in many industrial applications i… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
48
0
1

Year Published

2015
2015
2024
2024

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 89 publications
(49 citation statements)
references
References 35 publications
0
48
0
1
Order By: Relevance
“…Only projected bubble images could be obtained. This problem is well known and, despite some proposals (Bian et al, 2013;Sahagian and Proussevitch, 1998), a solution is far from being reached and the use of 2D projected images is a common way of processing bubble images (Karn et al, 2015;Lage and Espósito, 1999;Lau et al, 2013aLau et al, , 2013bWongsuchoto et al, 2003). However, the bubble shape data obtained by this approach are considered reliable: the bubble shape information allowed the extrapolation of correlations for the aspect ratio (Besagni, 2016; and flow regime transition criteria .…”
Section: Image Analysis: Uncertaintiesmentioning
confidence: 99%
“…Only projected bubble images could be obtained. This problem is well known and, despite some proposals (Bian et al, 2013;Sahagian and Proussevitch, 1998), a solution is far from being reached and the use of 2D projected images is a common way of processing bubble images (Karn et al, 2015;Lage and Espósito, 1999;Lau et al, 2013aLau et al, , 2013bWongsuchoto et al, 2003). However, the bubble shape data obtained by this approach are considered reliable: the bubble shape information allowed the extrapolation of correlations for the aspect ratio (Besagni, 2016; and flow regime transition criteria .…”
Section: Image Analysis: Uncertaintiesmentioning
confidence: 99%
“…In the present study, we have applied a method based on human recognition of the bubble edge Besagni and Inzoli, 2016b). This method was selected because, despite different image-processing algorithms that have been proposed, these techniques are still limited to resolve large bubble clusters, highly unsteady flows, and large void fractions (Karn et al, 2015). Additionally, at low holdup, there are problems associated with overlapping: if the holdup exceeds 1%, more than 40% of the bubbles are overlapping in the image (Lecuona et al, 2000;Rodríguez-Rodríguez et al, 2003).…”
Section: Introductionmentioning
confidence: 99%
“…H was defined as the ratio of the particle perimeter to the perimeter of a circle having the same area. A perfect circle would have an H of 1 (Karn et al, 2014), while a lettuce area would have a circularity factor between 2 and 5, based on a preliminary investigation of 50 lettuce plants.…”
Section: Image Processing Methods and Regression Analysismentioning
confidence: 99%