Abstract
The enhancement of accuracy of force measurement is important for aerodynamic force measurements in high-speed facilities. It is essential to evaluate the sensitivity of a force recovery technique for different forces experienced by the body. Very few algorithms are available for accurate recovery of forces experienced by the model in the high-speed facilities. In regards to this, the sensitivity and accuracy of two force recovery algorithms, namely support vector regression (SVR) and genetic algorithm (GA), have been examined for the force recovery in shock tube experiments. The current study focuses on the use of GA for the very first time for dynamic calibration and prediction of transient short duration force in impulse facilities. Support vector regression is another technique that has been used for the first time for force recovery in impulse facilities. The available methods of force recovery like deconvolution and adaptive neuro fuzzy inference system (ANFIS) have certain limitations in regards to the accuracy of recovered forces and are not suitable for all experimental conditions and force magnitudes. It is essential to obtain a force recovery algorithm that can be used for all conditions of force magnitudes and experimental conditions. This is ensured by a sensitivity study and it is found that both support vector regression and genetic algorithm provide high accuracy in calibration as well as shock tube experiments. These techniques are found to be accurate and sensitive towards the changes in the measured force due to introduction of spikes of various lengths on the model.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call