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De Jesus A.M.P.,Royal University | Ripoll M.L.R.,Technical University of Delft | Pereira H.F.S.G.,Royal University | Goncalves N.J.,UCVE
American Society of Mechanical Engineers, Pressure Vessels and Piping Division (Publication) PVP | Year: 2010

Probabilistic fatigue models are required to account conveniently for the several sources of uncertainty arising in the prediction procedures, such as the scatter in material behavior. In this paper, a recently proposed stress-based probabilistic model is assessed using fatigue data available for the P355NL1 steel (a pressure vessel steel). the referred probabilistic model is a log-Gumbel regression model, able to predict the probabilistic Wöhler field (P-S-N field), taking into account the mean stress (or stress R-ratio) effects. the parameters of the probabilistic model are identified using stress-life data derived for the P355NL1 steel, from smooth specimens, for three distinct stress R-ratios, namely R=-1, R=-0.5 and R=0. the model requires a minimum of two test series with distinct stress R-ratios. Since data from three test series is available, extrapolations are performed to test the adequacy of the model to make extrapolations for stress R-ratios other than those used in the model parameters assessment. Finally, the probabilistic model is used to model the fatigue behavior of a notched plate made of P355NL1 steel. In particular, the P-S-N field of the plate is modeled and compared with available experimental data. Cyclic elastoplastic analysis of the plate is performed since plasticity at the notch root is developed.Copyright © 2010 by ASME. Source


De Jesus A.M.P.,Royal University | Ripoll M.L.R.,Fraunhofer Institute for Mechanics of Materials | Fernandez-Canteli A.,University of Oviedo | Castillo E.,University of Cantabria | Pereira H.F.S.G.,UCVE
Journal of Pressure Vessel Technology, Transactions of the ASME | Year: 2012

Probabilistic fatigue models are required to account conveniently for the several sources of uncertainty arising in the prediction procedures, such as the scatter in material behavior. In this paper, a recently proposed stress-based probabilistic model is assessed using fatigue data available for the P355NL1 steel (a pressure vessel steel). The referred probabilistic model is a log-Gumbel regression model, able to predict the probabilistic Wöhler field (P-S-N field), taking into account the mean stress (or stress R-ratio) effects. The parameters of the probabilistic model are identified using stress-life data derived for the P355NL1 steel, from smooth specimens, for three distinct stress R-ratios, namely R-1, R-0.5, and R 0. The model requires a minimum of two test series with distinct stress R-ratios. Since data from three test series is available, extrapolations are performed to test the adequacy of the model to make extrapolations for stress R-ratios other than those used in the model parameters assessment. Finally, the probabilistic model is used to model the fatigue behavior of a notched plate made of P355NL1 steel. In particular, the P-S-N field of the plate is modeled and compared with available experimental data. Cyclic elastoplastic analysis of the plate is performed since plasticity at the notch root is developed. The probabilistic model correlated appropriately the stress-life data available for the P355NL1 steel and was able to perform extrapolations for stress ratios other than those used in the model identification. The P-S-N field identified using data from smooth specimens led to consistent predictions of the P-S-N field for a notched plate, demonstrating the adequacy of the probabilistic model also to predict the probabilistic Wöhler field for notched components. © 2012 American Society of Mechanical Engineers. Source


Pereira H.F.S.G.,UCVE | De Jesus A.M.P.,UCVE | Ribeiro A.S.,Royal University | Fernandes A.A.,University of Porto
Journal of Pressure Vessel Technology, Transactions of the ASME | Year: 2011

Although intensive research has been carried out to understand the fatigue behavior of steel notched components, under variable amplitude loading, no definite and general robust models have been derived so far. Therefore, every effort to augment the knowledge in this topic is welcomed. Within this context, existing variable amplitude data, derived by the authors for a notched low carbon pressure vessel steel (P355NL1) flat plate, is used to assess a local approach to fatigue. A linear damage summation framework, supported by elastoplastic finite element analyses, is used. Several variable amplitude loadings were selected and analyzed, using alternative configurations of kinematic hardening plasticity models (e.g., Chaboche's model with distinct constants superposition). The predictions are assessed using available experimental data and data derived with simplified empirical elastoplastic tools. This paper highlights the difficulties of performing such elastoplastic analysis and compares the obtained results with those obtained using more classical tools for elastoplastic analysis (Glinka and Seeger-Heuler). It was found that fatigue predictions based on an elastoplastic finite element analysis, made using the Chaboche's model, were significantly more accurate than predictions based on simplified elastoplastic analysis. These results have important practical relevance. © 2011 American Society of Mechanical Engineers. Source


Pinto H.,University of Massachusetts Amherst | De Jesus A.M.P.,Royal University | Fernandez-Canteli A.,University of Oviedo | Castillo E.,University of Cantabria | Pereira H.F.S.G.,UCVE
Journal of Pressure Vessel Technology, Transactions of the ASME | Year: 2010

The relation between the total strain amplitude and the fatigue life measured in cycles is usually given as strain-life curves based on the former proposals of Basquin, for the elastic strain-life, and Coffin-Manson, for the plastic strain-life. In this paper, a novel Weibull regression model, based on an existing well established Weibull model for the statistical assessment of stress-life fatigue data, is proposed for the probabilistic definition of the strain-life field. This approach arises from sound statistical and physical assumptions and not from an empirical proposal insufficiently supported. It provides an analytical probabilistic definition of the whole strain-life field as quantile curves, both in the low-cycle and high-cycle fatigue regions. The proposed model deals directly with the total strain, without the need of separating its elastic and plastic strain components, permit dealing with run-outs, and can be applied for probabilistic lifetime prediction using damage accumulation. The parameters of the model can be estimated using different well established methods proposed in the fatigue literature, in particular, the maximum likelihood and the two-stage methods. In this work, the proposed model is applied to analyze fatigue data, available for a pressure vessel material-the P355NL1 steel-consisting of constant amplitude, block, and spectrum loading, applied to smooth specimens, previously obtained and published by authors. A new scheme to deal with variable amplitude loading in the background of the proposed regression strain-life Weibull model is described. The possibility to identify the model constants using both constant amplitude and two-block loading data is discussed. It is demonstrated that the proposed probabilistic model is able to correlate the constant amplitude strain-life data. Furthermore, it can be used to correlate the variable amplitude fatigue data if the model constants are derived from two-block loading data. The proposed probabilistic regression model is suitable for reliability analysis of notched details in the framework of the local approaches. © 2010 American Society of Mechanical Engineers. Source

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