Hazard maps and global probability as a way to transfer standard fracture results to reliable design of real components. (November 2016) - Muñiz-Calvente, M.
Abstract: Design and lifetime prediction of structural and mechanical components require the assessment of the global probability of failure to be determined from stress and strain distributions obtained by FEM, as well as calculation of hazard maps in order to facilitate redesign and recognition of critical parts to be inspected regularly. The so-called generalized probabilistic local approach (GPLA), developed by the authors, allows the primary failure cumulative distribution function (PFCDF) owning to a certain failure type to be determined for a given material from experimental data and used subsequently for probabilistic design. The approach ensures a realistic safety margin provided that the failure criterion represented by an adequate generalized parameter (GP) and the corresponding failure criterion is properly recognized as a reference variable to be considered in the failure assessment. The way in which the results of such a reliability analysis are interpreted encompasses a variety of concepts under which failure can be understood and may be classified as global probability of failure and hazard maps, the former providing the conclusive failure probability for definitive design, and the latter representing, presumably, a risk of local failure that facilitates the possible component redesign but without providing the global probability of failure. In order to promote the implementation of the methodology proposed, an application is exemplary presented for the particular case of experimental results of glass plates. A finite element subroutine is developed for calculation of hazard maps and global probabilities of failure. Highlights: A methodology to validate a failure criterion based on the GP approach Global probability versus hazard maps as a failure criterion Failure characterization using Weibull distributions Probabilistic safe design request global probability estimation Validation of the failure reference parameter chosen