17.10. Importance of Statistical and Uncertainty Analysis

Rizwanul Fattah et al. [96] indicated that a statistical analysis can be carried out by applying two-sided Student's t-test for independent variables to test for significant differences between samples set using Microsoft Excel 2013. Differences between mean values at a level of p = 0.05 (95% confidence level) were considered statistically significant.
On the other hand, errors and uncertainties in the experiments can arise from instrument selection, experimental condition, equipment calibration, ambient environment, observation, reading, and test planning. Uncertainty analysis in engine performance tests is required to prove the accuracy of the experiments. Percentage uncertainties of various parameters such as total fuel consumption, brake power, brake-specific fuel consumption, and brake thermal efficiency can be calculated using the percentage uncertainties of various instruments used in the experiment [97].
The relative uncertainty can be determined using the linearized approximation method of uncertainty using the following equation [96,98,99]:

Δzz1zi=1pzxixi

image (17.9)

Using the principle of propagation of errors, the total percentage uncertainty of an experimental trial can be computed as [97]:

=Squarerootof(uncertaintyoftfc)2+(uncertaintyofbrakepower)2+(uncertaintyofspecificfuelconsumption)2+(uncertaintyofbrakethermalefficiency)2+(uncertaintyofCo)2+(uncertaintyofHc)2+(uncertaintyofNo)2+(uncertaintyofsmoke)2+(uncertaintyofEGTindicator)2

image (17.10)

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