TY - JOUR A1 - Fernádez-Canteli, A. A1 - Castillo, E. A1 - Blasón, Sergio A1 - Correia, J. A. F. O. A1 - de Jesus, A. M. P. T1 - Generalization of the Weibull probabilistic compatible model to assess fatigue data into three domains: LCF, HCF and VHCF JF - International Journal of Fatigue N2 - n this work, three classes of fatigue models are reviewed according to the fatigue regimes commonly considered in the current components design. Particular attention is devoted to the so-called Class III fatigue models, covering the three fatigue regimes, namely, LCF, HCF and VHCF. The applicability and limitations of the pro-posed analytical sigmoidal solutions are discussed from the viewpoint of practical design. The compatible Weibull S-N model by Castillo and Canteli is revisited and improved by considering a new reference parameter GP = E⋅σM ⋅(dε/dσ)|M as the driving force alternative to the conventional stress range. In this way, the requirement, σM ≤ σu, according to the real experimental conditions, is fulfilled and the parametric limit number of cycles, N0, recovers its meaning. The probabilistic definition of the model on the HCF and VHCF regimes is maintained and extended to the LCF regime. The strain gradients may be calculated from the monotonic or cyclic stress–strain curve of the material although a direct derivation from the hysteresis loop is recommended. Some Class III fatigue models from the literature and another one improved by the authors are applied to the assessment of one experimental campaign under different stress ratios conditions and the results compared accordingly. Finally, the new probabilistic GP-N field is evaluated. The results confirm the practical confluence of the stress- and the strain-based approaches into a single and advantageous unified methodology. KW - LCF region KW - S-N probabilistic field KW - Energetic reference parameter PY - 2022 DO - https://doi.org/10.1016/j.ijfatigue.2022.106771 SN - 0142-1123 VL - 159 SP - 1 EP - 18 PB - Elsevier Ltd. AN - OPUS4-55235 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Fernádez-Canteli, A. A1 - Castillo, E. A1 - Blasón, Sergio T1 - A methodology for phenomenological analysis of cumulative damage processes. Application to fatigue and fracture phenomena JF - International Journal of Fatigue N2 - Sample functions, i.e., stochastic process realizations, are used to define cumulative damage phenomena which end into an observable terminal state or failure. The complexity inherent to such phenomena justifies the use of phenomenological models associated with the evolution of a physical magnitude feasible to be monitored during the test. Sample functions representing the damage evolution may be identified, once normalized to the interval [0,1], with cumulative distribution functions (cdfs), generally, of the generalized extreme value (GEV) family. Though usually only a fraction of the whole damage evolution, according to the specific problem handled, is available from the test record, the phenomenological models proposed allow the whole damage process to be recovered. In this way, down- and upwards extrapolations of the whole damage process beyond the scope of the experimental program are provided as a fundamental tool for failure prediction in the practical design. The proposed methodology is detailed and its utility and generality confirmed by its successive application to representative well-known problems in fatigue and fracture characterization. The excellent fittings, the physical interpretation of the model parameters and the good expectations to achieve a complete probabilistic analysis of these phenomena justify the interest of the proposed phenomenological approach with possible applications to other cumulative damage processes. KW - Bayesian technique KW - Sample random results KW - Stochastic sample functions KW - Probabilistic assessment PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-552371 DO - https://doi.org/10.1016/j.ijfatigue.2021.106311 SN - 0142-1123 VL - 150 SP - 106311 PB - Elsevier Ltd. AN - OPUS4-55237 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -