Loading…
A Comprehensive Model to Predict Simplex Atomizer Performance
The pressure swirl atomizer, or simplex atomizer, is widely used in liquid fuel combustion devices in the aerospace and power generation industries. A computational, experimental, and theoretical study was conducted to predict its performance. The Arbitrary-Lagrangian-Eulerian method with a finite-v...
Saved in:
Published in: | Journal of engineering for gas turbines and power 1999-04, Vol.121 (2), p.285-294 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | The pressure swirl atomizer, or simplex atomizer, is widely used in liquid fuel combustion devices in the aerospace and power generation industries. A computational, experimental, and theoretical study was conducted to predict its performance. The Arbitrary-Lagrangian-Eulerian method with a finite-volume scheme is employed in the CFD model. Internal flow characteristics of the simplex atomizer, as well as its performance parameters such as discharge coefficient, spray angle and film thickness, are predicted. A temporal linear stability analysis is performed for cylindrical liquid sheets under three-dimensional disturbances. The model incorporates the swirling velocity component, finite film thickness and radius that are essential features of conical liquid sheets emanating from simplex atomizers. It is observed that the relative velocity between the liquid and gas phases, density ratio and surface curvature enhance the interfacial aerodynamic instability. The combination of axial and swirling velocity components is more effective than only the axial component for disintegration of liquid sheet. For both large and small-scale fuel nozzles, mean droplet sizes are predicted based on the linear stability analysis and the proposed breakup model. The predictions agree well with experimental data at both large and small scale. |
---|---|
ISSN: | 0742-4795 1528-8919 |
DOI: | 10.1115/1.2817119 |