Two-phase Ejector Considering Slip Velocity CFD Simulation, Experimental Paper Validation
Two-phase Ejector Considering Slip Velocity CFD Simulation, Experimental Paper Validation
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€310.00 Original price was: €310.00.€175.00Current price is: €175.00.
Ejectors are commonly utilized in the chemical process industries but can also be employed for mass transfer processes such as liquid-liquid extraction, gas absorption, stripping, fermentation, hydrogenation, and chlorination. It is clear that before proceeding any CFD simulation, there is strong need for a validation study. This is what we`ve targeted; to validate the experimental data of paper “ Design aspects of ejectors: Effects of suction chamber geometry”, published in Chemical Engineering Science journal.
Figure 1: Schematic of paper`s ejector domain
Simulation Process
A 2D-axisymmetric geometry of the ejector is created. It is meshed with hexahedral (structured) elements of uniform size. Given the Euler-Euler approach, it is decided to use the mixture multiphase model. In our study, the in-build slip correlation between primary and secondary phases are not followed, instead, the slip velocity has been directly specified through a user-defined function (UDF) by using the following definition:
Figure 2: Slip velocity definition based on the paper
Post-processing
Prior to any fluid dynamics analysis, we focus on validating the data given in the paper. In the base paper by Bhutada and Pangarkar, Experimental entrainment rate = 0.00294 kg/s. On the other hand, the current CFD simulation reports the value as 0.00288 kg/s. To put it in a nutshell, there is only 2% error! It entirely corroborates the precision of the study.
Experimental Data | Current CFD Simulation | Error | |
Entrainment rate | 0.00294 | 0.00288 | 2% |
We pride ourselves on presenting unique products at CFDLAND. We stand out for our scientific rigor and validity. Our products are not based on guesswork or theoretical assumptions like many others. Instead, most of our products are validated using experimental or numerical data from valued scientific journals. Even if direct validation isn’t possible, we build our models and assumptions on the latest research, typically using reference articles to approximate reality.
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