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Research Papers: Materials and Fabrication

Prediction of Long-Term Creep Rupture Life of Grade 122 Steel by Multiregion Analysis

[+] Author and Article Information
K. Maruyama

Graduate School of Engineering,
Tohoku University,
6-6-02 Aramaki-Aoba, Aoba-ku,
Sendai 980-8579, Japan
e-mail: maruyama@material.tohoku.ac.jp

J. Nakamura, K. Yoshimi

Graduate School of Engineering,
Tohoku University,
6-6-02 Aramaki-Aoba, Aoba-ku,
Sendai 980-8579, Japan

1Corresponding author.

Contributed by the Pressure Vessel and Piping Division of ASME for publication in the JOURNAL OF PRESSURE VESSEL TECHNOLOGY. Manuscript received April 14, 2014; final manuscript received July 29, 2014; published online October 15, 2014. Assoc. Editor: Marina Ruggles-Wrenn.

J. Pressure Vessel Technol 137(2), 021403 (Oct 15, 2014) (5 pages) Paper No: PVT-14-1066; doi: 10.1115/1.4028203 History: Received April 14, 2014; Revised July 29, 2014

Conventional time-temperature-parameter (TTP) methods often overestimate long-term rupture life of creep strength enhanced ferritic steels. Decrease in activation energy Q for rupture life in long-term creep is the cause of the overestimation, since the TTP methods cannot deal with the change in Q. Creep rupture data of a heat of Gr.122 steel (up to 26,200 h) were divided into several data sets so that Q was unique in each divided data set. Then a TTP method was applied to each divided data set for rupture life prediction. This is the procedure of multiregion analysis of creep rupture data. The predicted rupture lives have been reported in literature. Long-term rupture lives (up to 51,400 h) of the same heat of the steel have been published in 2013. The multiregion analysis of creep rupture life can predict properly the long-term lives reported. Stress and temperature dependences of rupture life show similar behavior among different heats. Therefore, database on results of the multiregion analyses of various heats of the steel is helpful for rupture life estimation of another heat.

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References

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Figures

Grahic Jump Location
Fig. 1

Correlation between data band (thick solid line) and its regression line (thin solid line) determined by the Orr–Sherby–Dorn analysis of creep rupture data

Grahic Jump Location
Fig. 2

(a) Stress and (b) temperature dependence of rupture life of heat RhA. The solid lines are regression curves determined by the multiregion analysis of the open marks taking account of the change in activation energy between Region L2 and the other regions. The dashed lines are regression curves determined by all the data points in Region L2. The dashed-dotted line is the boundary between Region L2 and the other regions. The solid marks represent new data reported after the regression analysis.

Grahic Jump Location
Fig. 3

Comparison of long-term rupture data (solid marks) of heat RhA to the regression curves (solid lines) determined from the data points selected by the σ0.2/2 criterion (double marks). (a) Stress and (b) temperature dependences. The thick dashed line is the boundary corresponding to σ0.2/2, and the dashed-dotted line is the boundary to Region L2.

Grahic Jump Location
Fig. 4

Stress-rupture data of heats (a) RhA and (b) RHQ together with their regression (solid) curves. The thick dashed curves are the boundary corresponding to σ0.2/2. The dotted lines are the boundaries between neighboring regions.

Grahic Jump Location
Fig. 5

Temperature dependence of rupture lives together with their regression curves: solid curves for heat RhA and dashed curves for heat RHQ. The upward and downward arrows indicate the boundaries to Region L2 in heats RhA and RHQ, respectively.

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