Abstract
An efficient method is proposed for estimating from sparse data the parameters of the systematic variation of the Charpy impact energy in the ductile-brittle transition region of low-carbon weld steels. The parameter estimates are practically unbiased and with a very good precision even in the case of very large scatter of the absorbed impact energy. Furthermore, the parameter estimates determining the shape of the transition curve are not affected by its location along the temperature axis. The method is robust regarding the temperature corresponding to a specified impact energy level. Thus, for different type of scatter of the impact toughness and different lengths of the scatter intervals, the estimates of the temperature corresponding to a specified impact energy vary in narrow limits. The transition temperature corresponding to a specified impact energy level is estimated with a very good precision, which is important for quantifying the deterioration of properties due to embrittlement.
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References
Akselsen, O.M. and Grong, Ø (1992). Prediction of weld metal Charpy V-notch toughness. Materials Science and Engineering A159, 187–192.
Avrami, M. (1940). Kinetics of phase change.II: Transformation-time relations for random distribution of nuclei. J. Chem. Phys. 8, 212–224.
Barlow, R.J. (1996). Statistics, Wiley and Sons, New York.
DeGroot, M.H. (1986). Probability and Statistics 2nd ed., Addison-Wesley.
Downing, D.J., Haggag, F.M. and Nanstad, R.K. (1990). Estimating Charpy transition temperature shift using Weibull analysis. International Journal of Pressure Vessels and Piping,44, 241–254.
Draper, N.R. and Smith, H. (1981). Applied Regression Analysis, 2nd ed., John Wiley and Sons, New York.
Johnson, W.A. and Mehl, R.F. (1939). Reaction kinetics in processes of nucleation and growth. Trans. Am. Inst. Min. Metall. Engrs 135, 416–458.
Koistinen, D.P. and Marburger, R.E. (1959). A general equation prescribing the extent of the austenite-martensite transformation in pure iron-carbon alloys and plain carbon steels. Acta Metallurgica 7, 59–60.
Kolmogorov, A.N. (1937). Statistical theory of crystallization of metals. Bull. Acad. Sci. USSR Mat. Sci. 1, 355–359.
Moskovic, R., Windle, P.L. and Smith, A.F. (1997). Modelling Charpy impact energy property changes using a Bayesian method. Metallurgical and Materials Transactions A28, 111–113.
Neter, J., Kutner, M.H., Nachtsheim, C.J. and Wasserman, W. (1996). Applied Linear Regression Models, 3rd ed. McGraw-Hill, New York.
Oldfield, W. (1975). Curve fitting impact data. ASTM Standardisation News 24–29.
Seber, G.A.F. (1997). Linear regression analysis, John Wiley and Sons, New York.
Stephens, D.A., Smith, A.F.M. and Moskovic, R. (1997). Charpy impact energy data: a Markov chain Monte Carlo analysis. Applied Statistics 46, 477–492.
Todinov, M.T. (1999). Fitting impact fracture toughness data in the transition region. Materials Science and Engineering A265, 1–6.
Todinov, M.T., Novovic, M., Bowen, P. and Knott, J.F. (2000). Modelling the impact energy in the ductile-brittle transition region of C-Mn multi-run welds. Materials Science & Engineering A A287, 116–124.
Todinov, M.T. (2000). On some limitations of the Johnson–Mehl–Avrami–Kolmogorov equation. Acta Materialia 48, 4217–4224.
Windle, P.L., Moskovic, R. and Crowder, M.J. (1996). A statistical model for the analysis and prediction of the effect of neutron irradiation on Charpy impact energy curves. Nuclear Engineering Design 165, 43–56.
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Todinov, M. An efficient method for estimating from sparse data the parameters of the impact energy variation in the ductile-brittle transition region. International Journal of Fracture 111, 131–150 (2001). https://doi.org/10.1023/A:1012212610024
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DOI: https://doi.org/10.1023/A:1012212610024