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Creep is defined as the permanent deformation of materials under the effect of sustained stress and elevated temperature for long periods of time, which can essentially lead to fracture. Due to very time-consuming and expensive testing requirements, existing experimental creep data are often analyzed using derived engineering parameters and models to predict and find the correlations between creep life (time to rupture), temperature and stress. The objective of this study was to analyze and compare different numerical algorithms by using the Larson-Miller parameter (LMP) extrapolation model. Calculations were performed using the classical LMP equation where different values of parameter C were selected, as well as using a modified LMP equation in which parameter C was stress dependent C(σ). The impact of two different approaches of extrapolation and correlation functions (linear and polynomial) applied to fit the LMP model was also investigated. A detailed analysis was performed to choose the best extrapolation fit function and error tolerance. The numerical algorithm implemented was validated through creep rupture testing performed on 10CrMo9-10 steel at 600 °C (873 K) and 80 MPa. Creep model behavior analysis proved that different values of C can significantly change the estimated time to rupture. An excellent response of the LMP model was obtained by considering polynomial dependency when parameter C was assumed to be 18, especially for the temperature range from 773 to 873 K. Promising results were also achieved when parameter C was taken as stress-dependent, but only for linear fitting, which requires further analysis. However, at validation stage it turned out that only the linear extrapolation function and C taken as a constant value provided adequate time-to-rupture prediction. In the case of C = 18, estimated time was slightly overestimated (~8%) and for C = 20 it was underestimated by 27%. In all other cases error largely exceeded 50%.

Creep Life Prediction of 10CrMo9–10 Steel by Larson–Miller Model