Influencing Factors Identification And Monte Carlo Simulation Of Static Test Results

The object of static test for the aircraft structure is to determine the characteristics on strength of the aircraft under static load.The verification by experimental tests for determination of compliance of static strength is one of the important procedures in aircraft design,manufacturing and design stereotype.The change of many influencing factors during the static test can affect the experimental test results.The thesis focuses on the identification of the most important factors which can influence the static test data.Meanwhile,the statistical characteristics of static test results are studied,which are realized by programming.It provides a new way for analysis on the randomness of civil aircraft static test results.Based on the existing experimental text data,the influencing factors of the static test results,the relationship among the influencing factors and the relationship between the influencing factors and the test results are analyzed.The result shows that the applied load is the most important factor on the results of displacement and strain,regardless of progressive loading or one-time loading.The grey relation analysis can be used to investigate the degree of association between each independent variables and the test results.While the principal component analysis can be used to analyze the correlation between variables.The analysis can be simplified by dimensionality reduction.The functional relationship between the static test results of typical structures in R-region on winglet of aircraft and the new variables after dimensionality reduction is established.The Monte Carlo method is used to find the sample capacity in case of stable average of random samplings.The characteristics of sample average and standard deviation shows the data comforts to lognormal distribution.The distribution type can be tested and the statistical characteristics can be found.In case of different small sample sizes,different confidence intervals can be found.The length of the confidence interval decreases with the increase of the sample capacity.The reasonability of interval estimates can be increased by controlling of sampling capacity in analysis of static test data.