The limitations of the established and existing creep failure models have inspired the development of a new creep prediction model. Models like Norton–Bailey and Omega are unable to model the tertiary creep curve for engineering materials. Kachanov–Rabotnov, Theta Projection, and Sine hyperbolic models rely on specific material properties for accurate damage predictions. In order to overcome these weaknesses, a new creep model combining the Norton–Bailey and Kachanov–Rabotnov models has been further devised for the creep life prediction of metallic materials. The model combination helps in covering the limitations of one model over another and to benefit from each other’s strengths. A technique of user subroutine scripting was adapted to implement the new creep model in finite element (FE) software of ABAQUS, manufactured by Dassault Systemes, version 2020. The new model was tested on an FE dog bone stainless steel 304 specimen; the analysis showed excellent agreement with the experimental creep deformation data at 600 °C to 700 °C. The creep strain rate curves obtained by the method of user subroutine scripting were found to be 90.69% accurate to the 1000 h experimental creep strain rate curve. Similarly, while comparing with the 336 h experimental creep test, the new model accuracy was found to be 92.66% for the creep strain rate curve. The new model’s precision was 91.56% when compared with the Omega and Norton–Bailey models for creep strain rate for the same conditions. The quantitative accuracy of the new creep model is better as compared to the existing creep models and can be an improved source of alternatives to existing creep models for the deformation predictions.
Bibliographical note© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
FunderThe authors would like to acknowledge the financial support through Deanship of Scientific Research at Taif University, Kingdom of Saudi Arabia and technical support through Digital Analytics Structural Integrity Technology Group (DASIT), Universiti Teknologi PETRONAS, Malaysia which are greatly appreciated. Funding Information: The research work was funded by the Deanship of Scientific Research at Taif University, Kingdom of Saudi Arabia and PETRONAS, Malaysia Industrial Grant; Grant No: 015MD0-156. Publisher Copyright: © 2023 by the authors.
- General Materials Science
- Metals and Alloys