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Multiphase CFD Modeling and Experimental Validation of Polymer and Attenuating Air Jet Interactions in Nonwoven Annular Melt Blowing
In annular melt blowing, fiber formation is achieved by accelerating a molten polymer via drag forces imparted by high velocity air that attenuates the polymer jet diameter. The interactions at the polymer–air interface, which govern the motion of the jets and impact the resulting fiber characterist...
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Published in: | Industrial & engineering chemistry research 2022-09, Vol.61 (37), p.13962-13971 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | In annular melt blowing, fiber formation is achieved by accelerating a molten polymer via drag forces imparted by high velocity air that attenuates the polymer jet diameter. The interactions at the polymer–air interface, which govern the motion of the jets and impact the resulting fiber characteristics, are important but not well understood yet. This work details the development and validation of a multiphase computational fluid dynamics (CFD) model to investigate these interactions and the effects of three key melt blowing process parameters (polymer viscosity and throughput and air velocity) on two critical fiber attributeswhipping instability and fiber diameter. Simulation results highlighted that whipping instability was driven by the polymer–air velocity differential, and the fiber diameter was primarily modulated by polymer throughput and air velocity. The CFD model was validated by modulating the polymer and air throughputs and analyzing the fiber diameter experimentally. Empirical results showed good agreement between fabricated and model-estimated fiber diameters, especially at lower air velocities. An additional CFD simulation performed using a melt blowing nozzle geometry and process parameters described in the literature also confirmed good correlation between model estimates and literature empirical data. |
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ISSN: | 0888-5885 1520-5045 |
DOI: | 10.1021/acs.iecr.2c01710 |