A quantitative assessment of random field models in finite element buckling analyses of composite cylinders

Kurzfassung

Large scatter characterizes the collapse load of thin-walled structures due to their imperfection sensitivity. Random fields can be used to include imperfections in a finite element model. Principal component analysis and analytical covariance functions are matched to available correlation information of geometrical imperfection measurements. The random fields are realized by Karhunen-Loève expansion combined with Monte Carlo methods. The results of the different covariance models are compared with the deterministic collapse loads of the measured imperfections in the FE-model. This approach isolates the effect of the different covariance models from other inaccuracies such as boundary conditions, loading imperfections, etc. The results show that random fields models can improve predictions and the understanding of the structural behavior of thin-walled structures, especially by using data based PCA. Caution is recommended with regard to analytical covariance functions since they may fail to capture the complete behavior of the structure.