High-order iterative learning identification of projectile's aerodynamic drag coefficient curve from radar measured velocity data

1998 ◽  
Vol 6 (4) ◽  
pp. 563-570 ◽  
Author(s):  
Yangquan Chen ◽  
Changyun Wen ◽  
Jian-Xin Xu ◽  
Mingxuan Sun
Keyword(s):  
Drag Coefficient ◽  
Aerodynamic Drag ◽  
Iterative Learning ◽  
High Order ◽  
Velocity Data ◽  
Measured Velocity ◽  
Aerodynamic Drag Coefficient

A new moving model test method for the measurement of aerodynamic drag coefficient of high-speed trains based on machine vision

2017 ◽  
Vol 232 (5) ◽  
pp. 1425-1436 ◽  
Author(s):  
Zhiwei Li ◽  
Mingzhi Yang ◽  
Sha Huang ◽  
Dan Zhou
Keyword(s):  
Machine Vision ◽  
Drag Coefficient ◽  
Model Test ◽  
High Speed ◽  
Aerodynamic Drag ◽  
Full Scale ◽  
Test Method ◽  
Test Accuracy ◽  
Friction Resistance ◽  
Aerodynamic Drag Coefficient

A moving model test method has been proposed to measure the aerodynamic drag coefficient of a high-speed train based on machine vision technology. The total resistance can be expressed as the track friction resistance and the aerodynamic drag according to Davis equation. Cameras are set on one side of the track to capture the pictures of the train, from which the line marks on the side surface of the train are extracted and analyzed to calculate the speed and acceleration of the train. According to Newton’s second law, the aerodynamic drag coefficient can be resolved through multiple tests at different train speeds. Comparisons are carried out with the full-scale coasting test, wind tunnel test, and numerical simulation; good agreement is obtained between the moving model test and the full-scale field coasting test with difference within 1.51%, which verifies that the method proposed in this paper is feasible and reliable. This method can accurately simulate the relative movement between the train, air, and ground. The non-contact measurement characteristic will increase the test accuracy, providing a new experimental method for the aerodynamic measurement.

scholarly journals Numerical Study of the Generic Sports Utility Vehicle Design with a Drag Reduction Add-On Device

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Shubham Singh ◽  
M. Zunaid ◽  
Naushad Ahmad Ansari ◽  
Shikha Bahirani ◽  
Sumit Dhall ◽  
...  
Keyword(s):  
Drag Reduction ◽  
Drag Coefficient ◽  
Aerodynamic Drag ◽  
Numerical Study ◽  
Fuel Efficiency ◽  
Ansys Fluent ◽  
Mean Pressure ◽  
Aerodynamic Drag Coefficient ◽  
Total Base ◽  
Aerodynamic Parameters

CFD simulations using ANSYS FLUENT 6.3.26 have been performed on a generic SUV design and the settings are validated using the experimental results investigated by Khalighi. Moreover, an add-on inspired by the concept presented by Englar at GTRI for drag reduction has been designed and added to the generic SUV design. CFD results of add-on model and the basic SUV model have been compared for a number of aerodynamic parameters. Also drag coefficient, drag force, mean surface pressure, mean velocities, and Cp values at different locations in the wake have been compared for both models. The main objective of the study is to present a new add-on device which may be used on SUVs for increasing the fuel efficiency of the vehicle. Mean pressure results show an increase in the total base pressure on the SUV after using the device. An overall reduction of 8% in the aerodynamic drag coefficient on the add-on SUV has been investigated analytically in this study.

A METHOD TO DETERMINE AERODYNAMIC DRAG COEFFICIENT IN COPPER–NICKEL MINE SHAFTS

2020 ◽  
Vol 56 (6) ◽  
pp. 1032-1039
Author(s):  
S. V. Mal’tsev ◽  
M. A. Semin ◽  
D. S. Kormshchikov
Keyword(s):  
Drag Coefficient ◽  
Aerodynamic Drag ◽  
Copper Nickel ◽  
Aerodynamic Drag Coefficient
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