A comparative study of uncertainty propagation methods in structural problems

Several uncertainty propagation algorithms are available in literature: (i) MonteCarlo simulations based on response surfaces, (ii) approximate uncertainty propagation algorithms and (iii) non probabilistic algorithms. All of these approaches are based on some a priori assumptions about the nature of design variables uncertainty and on the models and systems behavior. Some of these assumptions could misrepresent the original problem and, con-sequently, could yield to erroneous design solutions, in particular where the prior information is poor or inexistent (complete ignorance). Therefore, when selecting a method to solve an uncertainty based design problem, several aspects should be considered: prior assumptions, non-linearity of the performance function, number of input random variables and required ac-curacy. It could be useful to develop some guidelines to choose an appropriate method for a specific situation.