Nozzle Performance Maps for Fluidic Thrust Vectoring

2021 ◽  
pp. 1-12
Author(s):  
T. Chandra Sekar ◽  
Kundan Jaiswal ◽  
Rajat Arora ◽  
Ramraj H. Sundararaj ◽  
Abhijit Kushari ◽  
...  
Keyword(s):  
Thrust Vectoring ◽  
Fluidic Thrust Vectoring

scholarly journals Research on control effectiveness of fluidic thrust vectoring

2021 ◽  
Vol 104 (1) ◽  
pp. 003685042199813
Author(s):  
Fei Xue ◽  
Gu Yunsong ◽  
Yuchao Wang ◽  
Han Qin
Keyword(s):  
High Altitude ◽  
Ground State ◽  
Deflection Angle ◽  
Internal Flow ◽  
Lateral Force ◽  
Control Surface ◽  
Low Density ◽  
Thrust Vectoring ◽  
Density State ◽  
Fluidic Thrust Vectoring

In view of the control effects of fluidic thrust vector technology for low-speed aircraft at high altitude/low density and low altitude/high density are studied. The S-A model of FLUENT software is used to simulate the flow field inside and outside the nozzle with variable control surface parameters, and the relationship between the area of control surface and the deflection effect of main flow at different altitudes is obtained. It is found that the fluidic thrust vectoring nozzle can effectively control the internal flow in the ground state and the high altitude/low density state. and the mainstream deflection angle can be continuously adjusted. The maximum deflection angle of the flow in the ground state is 21.86°, and the maximum deviation angle of the 20 km high altitude/low density state is 18.80°. The deflecting of the inner flow of the nozzle is beneficial to provide more lateral force and lateral torque for the aircraft. The high altitude/low density state is taken as an example. When the internal flow deflects 18.80°, the lateral force is 0.32 times the main thrust. For aircraft with high altitude and low density, sufficient lateral and lateral torque can make the flying aircraft more flexible, which can make up the shortcomings of the conventional rudder failure and even replace the conventional rudder surface.

Effect of Control Parameters of Secondary Jet on Fluidic Thrust Vectoring

2014 ◽  
Vol 998-999 ◽  
pp. 613-616
Author(s):  
Li Li ◽  
Dong Ping Wang ◽  
Tsutomu Saito
Keyword(s):  
Flow Field ◽  
Control Parameters ◽  
Jet Injection ◽  
Specific Design ◽  
Initial State ◽  
Thrust Vectoring ◽  
Original Hypothesis ◽  
Fluidic Thrust Vectoring

The flow field was simulated in a 2D convergent-divergent nozzle, for fluidic thrust vectoring with N-S method. Based on the specific design, the effects of control parameters of secondary jet injection is investigated, and a method is proposed to calculate the initial state of secondary jet, which is different from original hypothesis of stagnation. The results showed that the two methods have closed results and the stagnation hypothesis is suitable for the calculation of the initial state of secondary jet.

Lattice-Boltzmann Very Large Eddy Simulations of Fluidic Thrust Vectoring in a Converging/Diverging Nozzle

2020 ◽  
Author(s):  
Avinash Jammalamadaka ◽  
Gregory M. Laskowski ◽  
Yanbing Li ◽  
James Kopriva ◽  
Pradeep Gopalakrishnan ◽  
...  
Keyword(s):  
Lattice Boltzmann ◽  
Large Eddy Simulations ◽  
Thrust Vectoring ◽  
Large Eddy ◽  
Fluidic Thrust Vectoring

Coanda Surface Geometry Optimization for Multi-Directional Co-Flow Fluidic Thrust Vectoring

2009 ◽  
Author(s):  
Fariborz Saghafi ◽  
Afshin Banazadeh
Keyword(s):  
Deflection Angle ◽  
Flow Characteristics ◽  
Geometric Parameters ◽  
Nozzle Geometry ◽  
Surface Geometry ◽  
Thrust Vectoring ◽  
Affective Factors ◽  
Optimization Parameters ◽  
Fluidic Thrust Vectoring ◽  
Maximum Thrust

The performance of Co-flow fluidic thrust vectoring is a function of secondary flow characteristics and the fluidic nozzle geometry. In terms of nozzle geometry, wall shape and the secondary slot aspect ratio are the main parameters that control the vector angle. The present study aims to find a high quality wall shape to achieve the best thrust vectoring performance, which is characterized by the maximum thrust deflection angle with respect to the injected secondary air. A 3D computational fluid dynamics (CFD) model is employed to investigate the flow characteristics in thrust vectoring system. This model is validated using experimental data collected from the deflection of exhaust gases of a small jet-engine integrated with a multi-directional fluidic nozzle. The nozzle geometry is defined by the collar radius and its cutoff angle. In order to find the best value of these two parameters, Quasi-Newton optimization method is utilized for a constant relative jet momentum rate, a constant secondary slot height and insignificant step size. In this method, the performance index is described as a function of thrust deflection angle. Optimization parameters (wall geometric parameters) are estimated in the direction of gradient, with an appropriate step length, in every iteration process. A good guess of initial optimization parameters could lead to a rapid convergence towards an optimal geometry and hence maximum thrust deflection angle. Examination over a range of geometric parameters around the optimum point reveals that this method promises the best performance of the system and has potential to be employed for all the other affective factors.

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