Design and analysis of a flat accelerometer-based force balance system for shock tunnel testing

Measurement ◽  
2007 ◽  
Vol 40 (1) ◽  
pp. 93-106 ◽  
Author(s):  
Niranjan Sahoo ◽  
D.R. Mahapatra ◽  
G. Jagadeesh ◽  
S. Gopalakrishnan ◽  
K.P.J. Reddy
Shock Waves ◽  
2005 ◽  
pp. 407-412
Author(s):  
R. Joarder ◽  
D. R. Mahaptra ◽  
G. Jagadeesh

Author(s):  
Jan Martinez Schramm ◽  
Alexander Wagner ◽  
Jeremy Wolfram ◽  
Klaus Hannemann ◽  
Tarik Barth ◽  
...  

2018 ◽  
Vol 5 (5) ◽  
pp. 13547-13555 ◽  
Author(s):  
G. Kalaiarassan ◽  
Krishan ◽  
M. Somanadh ◽  
Chandrasegar Thirumalai ◽  
M. Senthil Kumar

2013 ◽  
Vol 8 (2) ◽  
pp. 209-218 ◽  
Author(s):  
Gouji YAMADA ◽  
Hiromitsu KAWAZOE ◽  
Hiroshi SUEMURA ◽  
Takashi MATSUNO ◽  
Shigeru OBAYASHI

2018 ◽  
Vol 55 (2) ◽  
pp. 382-402
Author(s):  
Manish Mehta ◽  
C. Mark Seaford ◽  
Robert D. Kirchner ◽  
Aaron T. Dufrene

2011 ◽  
Vol 201-203 ◽  
pp. 2803-2806
Author(s):  
Tien Li Chen ◽  
Tsing Tshih Tsung ◽  
Liang Yu Yang ◽  
Ho Chang

The purpose of this study is testing the force of green energy lift mechanism and analyzes its result to get the key technology for green energy (saving force and energy). At first, the green energy lift mechanisms on the market are surveyed, then the mechanism are analyzed in this study. The force balance system of the mechanism is used to save force and energy. The position limitation of saving force and energy for the force balance system will be investigated. Universal testing machine is used to test the driving force by the different loads during the lift mechanism moving downward. The tested results of the driving force will be estimated. The study results show that the loads influence significantly the driving force. The angle between pulley and wire is the key factor of the driving force.


Drones ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 42
Author(s):  
Balram Panjwani ◽  
Cecile Quinsard ◽  
Dominik Gacia Przemysław ◽  
Jostein Furseth

Propellers are a vital component to achieve successful and reliable operation of drones. However, the drone developer faces many challenges while selecting a propeller and a common approach is to perform static thrust measurement. However, the selection of a propeller using a static thrust measurement system is time-consuming. To overcome a need for the static thrust system a virtual model has been developed for measuring both the static and dynamic thrust of a single and coaxial propeller. The virtual model is reliable enough to minimize the need for full-scale tests. The virtual model has been built using two open-source software Qblade and OpenFoam. Qblade is employed to obtain the lift and drag coefficients of the propeller’s airfoil section. OpenFoam is utilized to perform the flow simulations of propellers and for obtaining the thrust and torque data of the propeller. The developed virtual model is validated with experimental data and the experimental data are obtained by developing a multi-force balance system for measuring thrusts and torques of a single and a pair of coaxial contra-rotating propellers. The data obtained from the propeller virtual model are compared with the measurement data. For a single propeller, the virtual model shows that the estimated forces are close to the experiment at lower rotational speeds. For coaxial propellers, there are some deviations at the rear propeller due to the turbulence and flow disturbance caused by the front propeller. However, the computed thrust data are still accurate enough to be used in selecting the propeller. The studies indicate that in the future, these virtual models will minimize a need for experimental testing.


Author(s):  
C.U. Ebuzeme ◽  
Z.A. Quadri ◽  
Olugbenga Noah ◽  
Emmanuel O. Ogedengbe ◽  
Charles Eguma

2020 ◽  
Vol 42 (4) ◽  
pp. 880-889
Author(s):  
Sushmita Deka ◽  
Pallekonda Ramesh Babu ◽  
Maneswar Rahang

The accurate prediction of force is very important in the present scenario of aerodynamic force measurement. The high accuracy of force prediction during calibration facilitates a better accuracy of force measurement in aerodynamic facilities like shock tunnels and wind tunnels. The present study describes the force prediction in an accelerometer force balance system using support vector regression (SVR). The comparison of SVR with the existing force prediction techniques namely, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) has also been carried out. The accelerometer force balance used in the current experimentation consists of a tri-axial accelerometer to measure the response on an aluminium hemispherical model on the application of force. The impulse forces were applied along the axial, normal and azimuthal directions. The forces were predicted using the accelerations obtained from the tri-axial accelerometer. SVR method was able to predict the forces quite accurately as compared to ANFIS and ANN. However, SVR has the advantage over ANFIS and ANN in that it is independent of the magnitude of the training and testing data. It is capable of an accurate prediction of forces with any magnitude of training and testing data, unlike ANFIS and ANN.


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