Effects of Trumpet on the Flow Characteristics of Pressure Swirl Injectors

2018 ◽  
Vol 34 (4) ◽  
pp. 947-959
Author(s):  
Zhongtao Kang ◽  
Zhen-Guo Wang ◽  
Qinglian Li ◽  
Peng Cheng
Keyword(s):  
Flow Characteristics ◽  
Swirl Injectors ◽  
Pressure Swirl

Three phase cavitating flows in high-pressure swirl injectors

2002 ◽  
Vol 26 (6-7) ◽  
pp. 677-681 ◽  
Author(s):  
Ales Alajbegovic ◽  
Gerhard Meister ◽  
David Greif ◽  
Branislav Basara
Keyword(s):  
High Pressure ◽  
Cavitating Flows ◽  
Swirl Injectors ◽  
Three Phase ◽  
Pressure Swirl

scholarly journals Internal flow characteristics in scaled pressure-swirl atomizer

2018 ◽  
Vol 180 ◽  
pp. 02059 ◽  
Author(s):  
Milan Malý ◽  
Marcel Sapík ◽  
Jan Jedelský ◽  
Lada Janáčková ◽  
Miroslav Jícha ◽  
...  
Keyword(s):  
High Speed ◽  
Laser Doppler Anemometry ◽  
Flow Characteristics ◽  
Internal Flow ◽  
Liquid Sheet ◽  
Wide Range ◽  
Swirl Atomizer ◽  
Pressure Swirl ◽  
Pressure Swirl Atomizer ◽  
Working Liquid

Pressure-swirl atomizers are used in a wide range of industrial applications, e.g.: combustion, cooling, painting, food processing etc. Their spray characteristics are closely linked to the internal flow which predetermines the parameters of the liquid sheet formed at the discharge orifice. To achieve a better understanding of the spray formation process, the internal flow was characterised using Laser Doppler Anemometry (LDA) and high-speed imaging in a transparent model made of cast PMMA (Poly(methyl methacrylate)). The design of the transparent atomizer was derived from a pressure-swirl atomizer as used in a small gas turbine. Due to the small dimensions, it was manufactured in a scale of 10:1. It has modular concept and consists of three parts which were ground, polished and bolted together. The original kerosene-type jet A-1 fuel had to be replaced due to the necessity of a refractive index match. The new working liquid should also be colourless, non-aggressive to the PMMA and have the appropriate viscosity to achieve the same Reynolds number as in the original atomizer. Several liquids were chosen and tested to satisfy these requirements. P-Cymene was chosen as the suitable working liquid. The internal flow characteristics were consequently examined by LDA and high-speed camera using p-Cymene and Kerosene-type jet A-1 in comparative manner.

Flow in Atomizers: Influence of Different Parameters on the Performance Characteristics of Plain Orifice Atomizer and Pressure Swirl Atomizer of a Fuel Injection System of Gas Turbine Combustor

2005 ◽  
Author(s):  
Digvijay B. Kulshreshtha ◽  
S. A. Channiwala
Keyword(s):  
Surface Tension ◽  
Drop Size ◽  
Cone Angle ◽  
Flow Characteristics ◽  
Internal Flow ◽  
Performance Characteristics ◽  
Bulk Liquid ◽  
Atomization Process ◽  
Spray Cone ◽  
Pressure Swirl

The atomization process is essentially one in which bulk liquid is converted into small drops. Basically, it can be considered as a disruption of the consolidating influence of surface tension by the action of internal and external forces. In the absence of such disruptive forces, surface tension tends to pull the liquid into the form of a sphere, since this has the minimum surface energy. Liquid viscosity exerts a stabilizing influence by opposing any change in system geometry. On the other end, aerodynamic forces acting on the liquid surface may promote the disruption process by applying an external distortion force to the bulk liquid. Breakup occurs when the magnitude of the disruptive force just exceeds the consolidating surface tension force. In twin fluid atomizers of the air-blast type and air assist type, atomization and spray dispersion tend to be dominated by air momentum forces, with hydrodynamic processes playing only a secondary role. With pressure swirl nozzles, the internal flow characteristics are of primary importance, because they govern the thickness and uniformity of the annular liquid film formed in the final discharge orifice as well as the relative magnitude of the axial and tangential components of velocity of this film. It is therefore of great practical interest to examine the interrelationships that exist between internal flow characteristics, nozzle design variables, and important spray features such as cone angle and mean drop size. The various equations that have been derived for nozzle discharge coefficient are discussed because this coefficient not only affects the flow rate of any given nozzle but also can be used to calculate its velocity coefficients and spray cone angle. Consideration is also given to the complex flow situations that arise on the surface of a rotating cup or disk. These flow characteristics are of basic importance to the successful operation of atomizers, because they exercise a controlling influence on the nature of the atomization process, the quality of atomization, and distribution of drop sizes in the spray. For plain orifice atomizers, the key geometrical variables are the orifice length and diameter. Final orifice diameter is of prime importance for pressure swirl atomizers. The absence of any theoretical treatment of the atomization process has led to the evolution of empirical equations to express the relationship between the mean drop size in a spray and the variable liquid properties. This paper includes the study of different parameters that affect the flow in plain orifice and pressure swirl atomizers. The paper also includes the performance characteristics of plain orifice and pressure swirl atomizers.

Velocity Field Reconstruction in the Mixing Region of Swirl Sprays Using General Regression Neural Network

2005 ◽  
Vol 127 (1) ◽  
pp. 14-23 ◽  
Author(s):  
K. Ghorbanian ◽  
M. R. Soltani ◽  
M. R. Morad ◽  
M. Ashjaee
Keyword(s):  
Neural Network ◽  
Velocity Field ◽  
General Regression Neural Network ◽  
Design And Optimization ◽  
Phase Doppler Anemometry ◽  
Swirl Injectors ◽  
The Neural Network ◽  
Predicted Values ◽  
General Regression ◽  
Pressure Swirl

A general regression neural network technique is proposed for design optimization of pressure-swirl injectors. Phase doppler anemometry measurements for velocity distributions are used to train the neural network. An overall optimized value for the width of the probability is determined. The velocity field in the extrapolation regime is reconstructed with an accuracy of 93%. Excellent agreement between the predicted values and the measurements is obtained. The results indicate that the capability of performing design- and optimization studies for pressure-swirl injectors with sufficient accuracy exists by applying modest amount of data in conjunction with an overall optimized value for the width of the probability.

Sign in / Sign up

Export Citation Format

Share Document