On the prediction of creep behaviour of alloy 617 using Kachanov-Rabotnov model coupled with multi-objective genetic algorithm optimisation

The accurate prediction of elevated-temperature creep behaviour of alloys is important for preventing catastrophic failure of systems operating under prolonged elevated temperature-stress conditions. Here, we couple the Kachanov-Rabotnov (K-R) creep model with a multi-objective genetic algorithm (MOGA) to predict the creep behaviour of Alloy 617 at 800 degrees C, 900 degrees C, and 1000 degrees C, under various stress conditions. It is shown that the MOGAoptimised K-R creep model can capture the overall elevated-temperature behaviour of the alloy at 800 degrees C under a wide range of stress conditions. However, at 900 degrees C and 1000 degrees C, oxidation leads to the atypical accumulation of creep plasticity, which the K-R model cannot account for. Nevertheless, it is shown that the proposed methodology of optimising the K-R model with a MOGA can consistently provide accurate results within the limits of the K-R model.

Automated summary

Accurate prediction of elevated-temperature creep behavior is crucial for preventing catastrophic failure in systems operating under prolonged elevated temperature-stress conditions. In this study, a multi-objective genetic algorithm was used to optimize the Kachanov-Rabotnov creep model to predict the behavior of Alloy 617 at different temperatures and stress conditions. The results showed that the optimized model accurately captured the overall elevated-temperature behavior of the alloy, but oxidation had an impact on the creep plasticity at higher temperatures.