Research of nonlinear simulation on sweep voltage of streak tube imaging lidar

2016 ◽  
Author(s):  
Qian Zhai ◽  
Shao-kun Han ◽  
Yu Zhai ◽  
Jie-yu Lei ◽  
Jian-feng Yao
Keyword(s):  
Nonlinear Simulation ◽  
Sweep Voltage ◽  
Streak Tube

NONLINEAR SIMULATION OF A HIGH-SPEED, VISCOUS LIQUID JET

1998 ◽  
Vol 8 (2) ◽  
pp. 155-178 ◽  
Author(s):  
J. H. Hilbing ◽  
Stephen D. Heister
Keyword(s):  
Viscous Liquid ◽  
High Speed ◽  
Liquid Jet ◽  
Nonlinear Simulation

scholarly journals Acoustic Modeling and Vibration Characteristics of Supersonic Inlet Buzz

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 2048
Author(s):  
Jianfeng Zhu ◽  
Wenguo Luo ◽  
Yuqing Wei ◽  
Cheng Yan ◽  
Yancheng You
Keyword(s):  
Numerical Simulations ◽  
Pressure Oscillation ◽  
Resonant Mode ◽  
Acoustic Model ◽  
Oscillation System ◽  
Nonlinear Simulation ◽  
Supersonic Inlet ◽  
Nonlinear Amplification ◽  
Oscillation Damping ◽  
The Ideal

The buzz phenomenon of a typical supersonic inlet is analyzed on the basis of numerical simulations and duct acoustic theory. Considering that the choked inlet could be treated as a duct with one end closed, a one-dimensional (1D) mathematical model based on the duct acoustic theory is proposed to describe the periodic pressure oscillation of the little buzz and the big buzz. The results of the acoustic model agree well with that of the numerical simulations and the experimental data. It could verify that the dominated oscillation patterns of the little buzz and the big buzz are closely related to the first and second resonant mode of the standing wave, respectively. The discrepancies between the numerical simulation and the ideal acoustic model might be attributed to the viscous damping in the fluid oscillation system. In order to explore the damping, a small perturbation jet is introduced to trigger the resonance of the buzz system and the nonlinear amplification effect of resonance might be helpful to estimate the damping. Through the comparison between the linear acoustic model and the nonlinear simulation, the calculated pressure oscillation damping of the little buzz and the big buzz are 0.33 and 0.16, which could be regarded as an estimation of real damping.

Research on a flash imaging lidar based on a multiple-streak tube

Laser Physics ◽  
2009 ◽  
Vol 19 (1) ◽  
pp. 115-120 ◽  
Author(s):  
J. Liu ◽  
Q. Wang ◽  
S. Li ◽  
Y. Cheng ◽  
J. Wei
Keyword(s):  
Streak Tube

Large photocathode area picosecond streak tube

2008 ◽  
Author(s):  
S. V. Andreev ◽  
V. S. Belolipetski ◽  
S. R. Ivanova ◽  
T. P. Kulechenkova ◽  
G. P. Levina ◽  
...  
Keyword(s):  
Streak Tube

Improvement of image quality of framing streak tube with FOP output window

1993 ◽  
Author(s):  
Kuniyoshi Mori ◽  
Kenji Suzuki ◽  
Koichiro Oba
Keyword(s):  
Image Quality ◽  
Output Window ◽  
Streak Tube

Small-size streak tube with high edge spatial resolution

Optik ◽  
2021 ◽  
pp. 166791
Author(s):  
Liping Tian ◽  
Lingbin Shen ◽  
Lili Li ◽  
Xing Wang ◽  
Ping Chen ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Streak Tube

Active Noise Hybrid Feedforward/Feedback Control Using Neural Network Compensation*

2001 ◽  
Vol 124 (1) ◽  
pp. 100-104 ◽  
Author(s):  
Zhang Qizhi ◽  
Jia Yongle
Keyword(s):  
Neural Network ◽  
Noise Control ◽  
Control Method ◽  
Active Noise Control ◽  
Equivalent Model ◽  
Gradient Descent Method ◽  
Nonlinear Simulation ◽  
Control Approach ◽  
Active Noise ◽  
Nonlinear Noise

The nonlinear active noise control (ANC) is studied. The nonlinear ANC system is approximated by an equivalent model composed of a simple linear sub-model plus a nonlinear sub-model. Feedforward neural networks are selected to approximate the nonlinear sub-model. An adaptive active nonlinear noise control approach using a neural network enhancement is derived, and a simplified neural network control approach is proposed. The feedforward compensation and output error feedback technology are utilized in the controller designing. The on-line learning algorithm based on the error gradient descent method is proposed, and local stability of closed loop system is proved based on the discrete Lyapunov function. A nonlinear simulation example shows that the adaptive active noise control method based on neural network compensation is very effective to the nonlinear noise control, and the convergence of the NNEH control is superior to that of the NN control.

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