On the Accuracy of Probabilistic Bucking Load Prediction
The buckling strength of thin-walled stiffened or unstiffened, metallic or composite shells is of major concern in aeronautical and space applications. The difficulty to predict the behavior of axially compressed thin-walled cylindrical shells continues to worry design engineers as we enter the third millennium. Thanks to extensive research programs in the late sixties and early seventies and the contributions of many eminent scientists, it is known that buckling strength calculations are affected by the uncertainties in the definition of the parameters of the problem such as definition of loads, material properties, geometric variables, edge support conditions, and the accuracy of the engineering models and analysis tools used in the design phase. The NASA design criteria monographs from the late sixties account for these design uncertainties by the use of a lump sum safety factor. This so-called 'empirical knockdown factor gamma' usually results in overly conservative design. Recently new reliability based probabilistic design procedure for buckling critical imperfect shells have been proposed. It essentially consists of a stochastic approach which introduces an improved 'scientific knockdown factor lambda(sub a)', that is not as conservative as the traditional empirical one. In order to incorporate probabilistic methods into a High Fidelity Analysis Approach one must be able to assess the accuracy of the various steps that must be executed to complete a reliability calculation. In the present paper the effect of size of the experimental input sample on the predicted value of the scientific knockdown factor lambda(sub a) calculated by the First-Order, Second-Moment Method is investigated.