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Journal of Pressure Vessel Technology | Volume 132 | Issue 6 | Research Paper
Research Papers: Design and Analysis

A New Approach of Reliability Design For Creep Rupture Property

[+] Author and Article Information
Jie Zhao1

 Dalian University of Technology, Dalian 116085, Chinajiezhao@dlut.edu.cn

Dong-ming Li, Yuan-yuan Fang

 Dalian University of Technology, Dalian 116085, China

Shi-jie Zhu

 Fukuoka Institute of Technology, Fukuoka 811-0295, Japan

1

Corresponding author.

J. Pressure Vessel Technol 132(6), 061209 (Oct 19, 2010) (6 pages) doi:10.1115/1.4001731 History: Received August 14, 2009; Revised February 21, 2010; Published October 19, 2010; Online October 19, 2010
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Citing Articles

Generally, creep rupture data of a heat-resistant steel can be compressed into a narrow band by using a temperature-time parametric method such as the Larson–Miller or Manson–Haferd method. In order to describe the scattering of the data, the current paper proposes a “Z parameter” method to represent the magnitude of the deviation of the rupture data to master curve. Statistical analysis shows that the scattering of the Z parameter for several types of steels is supported by normal distribution. Using this method, it is possible to achieve unified analysis of the creep rupture data in various temperature and stress conditions. Stress-time temperature parameter-reliability curves (σ-TTP-R curves), stress-rupture time-reliability curves (σ-tr-R curves), and allowable stress-temperature-reliability curves ([σ]-T-R curves) are proposed, which could embrace the reliability concept into creep rupture property design.
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References

1
Larson, F. R., and Miller, J. J., 1952, “A Time-Temperature Relationships for Rupture and Creep Stresses,” Trans ASTM, 74 , pp. 765–781.
2
Manson, S. S., and Haferd, A. M., 1953, “A Linear Time-Temperature Relation for Extrapolation of Creep and Stress-Rupture Data,” Paper No. NACA TN 2890.
3
Evans, M., 1995, “Statistical Properties of the Failure Time Distribution for 1/2Cr1/2Mo1/4V Steel,” J. Mater. Process. Technol., 54 , pp. 171–180.  [CrossRef]
4
Peralta-Duran, A., and Wirsching, P. H., 1984, “Creep-Rupture Reliability Analysis,” NASA Contractor Report No. 3790.
5
Xing, L., Zhao, J., Shen, F. Z., and Feng, W., 2006, “Reliability Analysis and Life Prediction of HK40 Steel During High-Temperature Exposure,” Int. J. Pressure Vessels Piping, 83 , pp. 730–735.  [CrossRef]
6
Zhao, J., Han, S. Q., Gao, H. B., and Wang, L., 2004, “Remaining Life Assessment of a CrMoV Steel Using the Z-Parameter Method,” Int. J. Pressure Vessels Piping, 81 , pp. 757–760.  [CrossRef]
7
Maruyama, K., and Yoshimi, K., 2007, “Influence of Data Analysis Method and Allowable Stress Criterion on Allowable Stress of Gr.122 Heat Resistant Steel,” ASME J. Pressure Vessel Technol., 129 , pp. 449–453.  [CrossRef]
8
Murty, A. S. R., Gupta, U. C., and Krishna, A. R., 1995, “A New Approach to Fatigue Strength Distribution for Fatigue Reliability Evaluation,” Int. J. Fatigue, 17 (2), pp. 85–89.  [CrossRef]
9
Zhao, J., Li, D. -M., Zhang, J. -S., Feng, W., and Fang, Y. -Y., 2009, “Introduction of SCRI Model for Creep Rupture Life Assessment,” Int. J. Pressure Vessels Piping, 86 , pp. 599–603.  [CrossRef]
10
National Research Institute for Metals, 1991, Data sheets on the elevated temperature properties of centrifugally cast tubes and cast block of 25Cr-35Ni-0.4C steel tubes for use in reformer furnaces, National Research Institute for Metals, Japan, 38A.
11
Zhang, J. Q., Zhao, H. Y., and Lu, A. L., 2004, “Statistical Characteristics of Endurance Strength of Heat Resistant Steel and Their Application in Life Evaluation,” Journal of Mechanical Strength, 26 (6), pp. 701–705.
12
National Research Institute for Metals, 1986, Data sheets on the elevated temperature properties of 2.25Cr-1Mo steel tubes for boilers and heat exchangers tubes, National Research Institute for Metals, Japan, 3B.

Figures

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+The schematic diagram of “stress-strength interference model” (SCRI model)
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The schematic diagram of “stress-strength interference model” (SCRI model)
Figure 8

The schematic diagram of “stress-strength interference model” (SCRI model)

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+The effect of temperature fluctuation on the area of the interference region for T91/P91 steel using SCRI model: (a) temperature fluctuation is 10°C, and (b) temperature fluctuation is 20°C
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The effect of temperature fluctuation on the area of the interference region for T91/P91 steel using SCRI model: (a) temperature fluctuation is 10°C, and (b) temperature fluctuation is 20°C
Figure 9

The effect of temperature fluctuation on the area of the interference region for T91/P91 steel using SCRI model: (a) temperature fluctuation is 10°C, and (b) temperature fluctuation is 20°C

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+The influence of temperature and stress fluctuations on the values of reliability in T91/P91 steel using SCRI model: (a) the influence of temperature fluctuations, and (b) the influence of stress fluctuations
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The influence of temperature and stress fluctuations on the values of reliability in T91/P91 steel using SCRI model: (a) the influence of temperature fluctuations, and (b) the influence of stress fluctuations
Figure 10

The influence of temperature and stress fluctuations on the values of reliability in T91/P91 steel using SCRI model: (a) the influence of temperature fluctuations, and (b) the influence of stress fluctuations

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+The correlation of creep rupture data with σ-TTP-R curves using the difference TTP parameter of Larson–Miller and Manson–Haferd for 4Cr25Ni35 alloy: (a) correlation with the Larson–Miller parameter, and (b) correlation with the Manson–Haferd parameter
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The correlation of creep rupture data with σ-TTP-R curves using the difference TTP parameter of Larson–Miller and Manson–Haferd for 4Cr25Ni35 alloy: (a) correlation with the Larson–Miller parameter, and (b) correlation with the Manson–Haferd parameter
Figure 11

The correlation of creep rupture data with σ-TTP-R curves using the difference TTP parameter of Larson–Miller and Manson–Haferd for 4Cr25Ni35 alloy: (a) correlation with the Larson–Miller parameter, and (b) correlation with the Manson–Haferd parameter

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+The scattering distribution of creep rupture data around the master curve in the σ-TTP plot
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The scattering distribution of creep rupture data around the master curve in the σ-TTP plot
Figure 1

The scattering distribution of creep rupture data around the master curve in the σ-TTP plot

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+Comparison of the predicted curves with different mathematic equations. (a) Stress σ is a function of the TTP parameter, larger deviation on the horizontal axe at lower stress level. (b) Log TTP is a function of stress, larger deviation on the horizontal axe at higher stress level.
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Comparison of the predicted curves with different mathematic equations. (a) Stress σ is a function of the TTP parameter, larger deviation on the horizontal axe at lower stress level. (b) Log TTP is a function of stress, larger deviation on the horizontal axe at higher stress level.
Figure 2

Comparison of the predicted curves with different mathematic equations. (a) Stress σ is a function of the TTP parameter, larger deviation on the horizontal axe at lower stress level. (b) Log TTP is a function of stress, larger deviation on the horizontal axe at higher stress level.

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+The distribution of Z parameter for 2.25Cr-1Mo steel
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The distribution of Z parameter for 2.25Cr-1Mo steel
Figure 3

The distribution of Z parameter for 2.25Cr-1Mo steel

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+An example of the stress-TTP parameter-reliability curves (σ-TTP-R curves) of 2.25Cr-1Mo steel
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An example of the stress-TTP parameter-reliability curves (σ-TTP-R curves) of 2.25Cr-1Mo steel
Figure 4

An example of the stress-TTP parameter-reliability curves (σ-TTP-R curves) of 2.25Cr-1Mo steel

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+An example of σ-tr-R curves at various temperatures for 9Cr-1Mo steel
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An example of σ-tr-R curves at various temperatures for 9Cr-1Mo steel
Figure 5

An example of σ-tr-R curves at various temperatures for 9Cr-1Mo steel

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+The allowable stress-temperature curve ([σ]-T) at 100,000 h using the safety coefficient method
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The allowable stress-temperature curve ([σ]-T) at 100,000 h using the safety coefficient method
Figure 6

The allowable stress-temperature curve ([σ]-T) at 100,000 h using the safety coefficient method

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+The allowable stress-temperature-reliability curves ([σ]-T-R curves) at 100,000 h based probability concept
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The allowable stress-temperature-reliability curves ([σ]-T-R curves) at 100,000 h based probability concept
Figure 7

The allowable stress-temperature-reliability curves ([σ]-T-R curves) at 100,000 h based probability concept

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+The comparison of the deduced σ-tr-R relationship using different TTP methods of Larson–Miller and Manson–Haferd parameters
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The comparison of the deduced σ-tr-R relationship using different TTP methods of Larson–Miller and Manson–Haferd parameters
Figure 12

The comparison of the deduced σ-tr-R relationship using different TTP methods of Larson–Miller and Manson–Haferd parameters

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+The comparison of the deduced allowable stress using different TTP methods of Larson–Miller and Manson–Haferd parameters
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The comparison of the deduced allowable stress using different TTP methods of Larson–Miller and Manson–Haferd parameters
Figure 13

The comparison of the deduced allowable stress using different TTP methods of Larson–Miller and Manson–Haferd parameters

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+Comparison of σ-TTP curves using the safety coefficient method and reliability methods in two typical steels: (a) 9Cr-1Mo steel, and (b) 25Cr-35Ni-0.4C alloy
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Comparison of σ-TTP curves using the safety coefficient method and reliability methods in two typical steels: (a) 9Cr-1Mo steel, and (b) 25Cr-35Ni-0.4C alloy
Figure 14

Comparison of σ-TTP curves using the safety coefficient method and reliability methods in two typical steels: (a) 9Cr-1Mo steel, and (b) 25Cr-35Ni-0.4C alloy

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