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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

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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Figures

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Figure 1

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

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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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Figure 3

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

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Figure 4

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

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Figure 5

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

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Figure 6

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

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Figure 7

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

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Figure 8

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

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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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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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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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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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Figure 13

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

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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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