Statistical Analysis of the ASME KIc Database

1998 ◽  
Vol 120 (1) ◽  
pp. 24-28 ◽  
Author(s):  
M. A. Sokolov
Keyword(s):  
Fracture Toughness ◽  
Distribution Function ◽  
Lower Bound ◽  
Weibull Distribution ◽  
Master Curve ◽  
Lower Boundary ◽  
Transition Range ◽  
Weibull Distribution Function ◽  
American Society ◽  
Function Models

The American Society of Mechanical Engineers (ASME) KIc curve is a function of test temperature (T) normalized to a reference nil-ductility temperature, RTNDT, namely, T – RTNDT. It was constructed as the lower boundary to the available KIc database. Being a lower bound to the unique but limited database, the ASME KIc curve concept does not discuss probability matters. However, a continuing evolution of fracture mechanics advances has led to employment of the Weibull distribution function to model the scatter of fracture toughness values in the transition range. The Weibull statistic/master curve approach was applied to analyze the current ASME KIc database. It is shown that the Weibull distribution function models the scatter in KIc data from different materials very well, while the temperature dependence is described by the master curve. Probabilistic-based tolerance-bound curves are suggested to describe lower-bound KIc values.

Comparison of Master Curve and Statistical Model Approach for Prediction of Fracture Toughness of ASTM A285 Steel

2004 ◽  
Author(s):  
Karthik Subramanian ◽  
Andrew J. Duncan
Keyword(s):  
Fracture Toughness ◽  
Statistical Models ◽  
Master Curve ◽  
Compact Tension ◽  
Standard Test ◽  
American Petroleum Institute ◽  
Test Method ◽  
Data Sets ◽  
Transition Range ◽  
American Society

The master curve approach was utilized to compare fracture toughness of American Society for Testing of Materials (ASTM) A285 as developed from Charpy v-notch (CVN) data and predictive statistical models. The master curves for each of the data sets were developed in accordance with American Society for Testing Materials Specification E 1921 (ASTM E1921, “Standard Test Method for Determination of Reference Temperature, T0, for Ferritic Steels in the Transition Range”), as prescribed by American Petroleum Institute Recommended Practice 579 (API-579, “Fitness for Service”). The results indicate that predictive statistical models developed from compact tension test results express a lower fracture toughness distribution when compared to CVN data.

Rational Determination of Lower-Bound Fracture Toughness Curves Using Master Curve Approach

2013 ◽  
Vol 135 (6) ◽  
Author(s):  
Naoki Miura ◽  
Naoki Soneda ◽  
Shu Sawai ◽  
Shinsuke Sakai
Keyword(s):  
Fracture Toughness ◽  
Lower Bound ◽  
Master Curve ◽  
Surveillance Program ◽  
Data Sets ◽  
Ductile Brittle Transition Temperature ◽  
Asme Code ◽  
American Society ◽  
Reactor Pressure

The Master Curve gives the relation between the median of fracture toughness of ferritic steels and the temperature in the ductile–brittle transition temperature region. The procedure used to determine the Master Curve is provided in the current American Society for Testing and Materials (ASTM) E1921 standard. By considering the substitution of the alternative lower-bound curves based on the Master Curve approach for the KIc curves based on reference data sets in the present codes such as ASME Code Cases N-629 and N-631, the statistical characteristic should be well incorporated in the determination of the lower-bound curves. Appendix X4 in the ASTM standard describes the procedure used to derive the lower-bound curves; however, it appears to be addressed without sufficient consideration of the statistical reliability. In this study, we propose a rational determination method of lower-bound fracture toughness curves using the Master Curve approach. The method considers the effect of sample size in the determination of the tolerance-bound curve. The adequacy of the proposed method was verified by comparing the tolerance-bound curve with the fracture toughness database for national reactor pressure vessel (RPV) steels including plate and forging obtained from 4 T to 0.4 T C(T) specimens and 0.4 T SE(B) specimens. The method allows the application of the Master Curve using fewer specimens, which can coexist with the present surveillance program.

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