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Research Papers: Design and Analysis

Probabilistic Fatigue Assessment of a Notched Detail Taking Into Account Mean Stress Effects

[+] Author and Article Information
Abílio M. P. De Jesus

Engineering Department, School of Sciences and Technology,  University of Trás-os-Montes and Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugalajesus@utad.pt

M. Luisa Ruiz Ripoll

Lifetime Concepts, Thermomechanics,  Business Unit Component Safety, Fraunhofer Institut—IWM, Woehlerstr. 11, 79108 Freiburg, Germanym.luisa.ruiz.ripoll@iwm.fraunhofer.de

Alfonso Fernández-Canteli

Department of Construction and Manufacturing Engineering,  University of Oviedo, Campus Viesques, 33203 Gijón, Spainafc@uniovi.es

Enrique Castillo

Department of Applied Mathematics and Computational Sciences,  University of Cantabria, 39005 Santander, Spaincastie@unican.es

Hélder F. S. G. Pereira

UCVE, IDMEC—Pólo FEUP, Campus FEUP, Rua Dr. Roberto Frias, 404, 4200-465 Porto, Portugalhfpereira@portugalmail.pt

J. Pressure Vessel Technol 134(2), 021203 (Jan 13, 2012) (9 pages) doi:10.1115/1.4005392 History: Received December 12, 2010; Revised October 14, 2011; Published January 13, 2012; Online January 13, 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.

FIGURES IN THIS ARTICLE
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Copyright © 2012 by American Society of Mechanical Engineers
Topics: Fatigue , Stress , Steel
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References

Figures

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Figure 1

Schematic P–S–N fields for constant σM1* and σM2*, and constant σm1* and σm2*, illustrating the compatibility condition. Dashed lines refer to S–N curves for constant σm*, and continuous lines refer to S–N curves for constant σM* [5].

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Figure 2

Constant amplitude stress-life data for the P355NL1 steel [17]

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Figure 3

S–N curves according the log-Gumbel model for the P355NL1. Case A: all data.

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Figure 4

S–N curves according the log-Gumbel model for the P355NL1. Case B: data excluding plastic behavior.

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Figure 5

Comparison of the 50% percentile curves for cases A and B

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Figure 6

P–P plots for the P355NL1

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Figure 7

P–S–N fields for R = 0, R = −0.5, and R = −1.0. Percentiles 0.01, 0.05, 0.50, 0.95, and 0.99 are represented. Case A.

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Figure 13

Predicted P–S–N field of the notched plate (all experimental data; kf = 1.2; q = 0.17; Gumbel constants: Case A)

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Figure 14

Predicted P–S–N field of the notched plate (limited experimental data; kf = 1.4; q = 0.34; Gumbel constants: Case B)

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Figure 12

S–N data of the notched plate of P355NL1 steel

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Figure 11

Rectangular notched plate of P355NL1 steel

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Figure 10

P–S–N fields for R = 0, R = −0.5, and R = −1.0. Percentiles 0.01, 0.05, 0.50, 0.95, and 0.99 are represented. Case A*.

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Figure 9

S–N curves according the log-Gumbel model for the P355NL1. Case A*: extrapolation for R = −0.5.

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Figure 8

P–S–N fields for R = 0, R = −0.5, and R = −1.0. Percentiles 0.01, 0.05, 0.50, 0.95, and 0.99 are represented. Case B.

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