%A M. Sattar
%A A.R. Othman
%A M. Muzamil
%A S. Kamaruddin
%A M. Akhtar
%A R. Khan
%L scholars18827
%X To maintain safety and reliability in power plants, creep-life prediction models have received much attention over the years. This article was designed to focus on the conditions when a material structure is exposed to extremely high temperatures and pressures with the help of finite element analysis. A direct comparison of the feasibility of different models� fitness and suitability in predicting creep damage was presented in this article by simulating the damage evolution of a uniaxial SS-304 specimen under a pre-defined load, using established constitutive creep models. Comparative assessments of minimum creep strain rate, creep deformation, and stress rupture were demonstrated using the Norton�Bailey (NB), Kachanov�Rabotnov (KR), Theta projection (TP), and sine-hyperbolic (SH) models while standardizing them with the Omega model. The FE results of a dog-bone specimen, while implementing the models, were compared with the actual creep experiment results to check for the models� reliability and validation. Subsequently, sensitivity studies of the established creep models were conducted using the statistical tools RSM and ANOVA, with an analysis of how the parameters for operation, design, and material dependency came into effect. Thus, quantitative and qualitative correlation analyses of the FE creep response for these five established models were conducted together, resulting in finalizing the selection of the most suitable model, the sine-hyperbolic model, for the SS-304 material under the defined boundary conditions. The 0.84 R2 value of the sine-hyperbolic model proved the model�s selection for predicting the creep response of stainless steel 304. The method can be applied to select a suitable creep damage model as per the feasibility of the operating conditions. © 2023 by the authors.
%J Metals
%N 2
%R 10.3390/met13020197
%D 2023
%V 13
%T Correlation Analysis of Established Creep Failure Models through Computational Modelling for SS-304 Material
%O cited By 3