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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.

The persistent efforts among the researchers are being done to reduce emissions by the exploration of different alternative fuels. The application of alternative fuel is also found to influence engine vibration. The present study explores the potential connection between the change of the engine operating parameters and the engine vibration pattern. The objective is to analyze the effect of alternative fuel on engine vibration and performance. The experiments are performed on two different engines of single cylinder (SC) and twin-cylinder (TC) variants at the load range of 0–34 Nm, with steps of 6.8 Nm and at the constant speed of 1500 rpm. The single cylinder engine, fueled with only diesel mode, is tested at two compression ratios (CRs) of 16.5 and 17.5. However, the twin-cylinder engine with a constant compression ratio of 16.5 is tested at both diesel unifuel and diesel-compressed natural gas (CNG) dual-fuel modes. Further, in dual-fuel mode, tests are conducted with compressed natural gas substitutions of 40%, 60%, and 80% for given loads and speed. The engine vibration signatures are measured in terms of root mean square (RMS) acceleration, representing the amplitude of vibration. The combustion parameters considered are cylinder pressure, rate of pressure rise, heat release rate (HRR), and ignition delay. At higher loads, the vibration amplitude increases along with the cylinder pressure. The maximum peak cylinder pressure (PCP) of 95 bar is found in the case of the single cylinder engine at the highest load condition that also produced a peak vibration of 3219 m/s2.