Revisiting Stress-Based Fatigue Life Prediction in the Low-Cycle Regime

Fatigue is recognized as dominant failure mechanism in metallic materials, especially when structural components are subjected to cyclic loading regimes that approach or exceed the elastic–plastic transition. Within this broad field, low-cycle fatigue occupies a distinctive position because plastic deformation becomes an intrinsic part of the damage process. For long time, this regime has been dominated by strain-based descriptions, most notably the Coffin–Manson framework, which explicitly partitions elastic and plastic strain contributions. While this approach has achieved wide acceptance, it is not without practical limitations, especially when applied to complex components or multiaxial loading states. One of the enduring challenges in low-cycle fatigue assessment is the tension between physical fidelity and analytical simplicity. Strain-based methods typically require elastic–plastic constitutive modeling, detailed material characterization, and iterative numerical procedures. These demands can be prohibitive in engineering practice, particularly when fatigue assessment must be integrated into early design stages or large-scale parametric studies. At the same time, stress-based methods—long associated with high-cycle fatigue—have been largely dismissed in the low-cycle regime, based on the assumption that linear-elastic stress measures cannot meaningfully capture damage when plasticity is dominant.

The separation concept between stress-based and strain-based fatigue regimes has shaped fatigue design philosophy for decades. However, it has also constrained the exploration of potentially simpler predictive routes. The Wöhler curve method, historically linked to high-cycle fatigue, offers an appealingly direct relationship between a stress intensity parameter and fatigue life. Its mathematical clarity and computational efficiency have made it indispensable for high-cycle applications. The question that naturally arises, but has rarely been examined in a systematic manner, is whether this framework can be extended into the low-cycle domain without sacrificing predictive credibility. To this end, new research paper published in Journal of Harbin Institute of Technology and led by Professor Xiangqiao Yan from the Harbin Institute of Technology, he demonstrated that the classical Wöhler curve method, traditionally restricted to high-cycle fatigue, can be reliably applied to low-cycle fatigue for a broad class of metallic materials. By systematically re-analyzing literature fatigue data, he showed that stress-based life prediction remains valid whenever elastic strain follows Basquin-type scaling.

Professor Xiangqiao Yan assessed the Wöhler curve method across a wide spectrum of materials, loading modes, and temperature conditions without bias toward a single experimental campaign. For each material system, reported strain-controlled fatigue data were first interpreted within the conventional Coffin–Manson framework to establish the presence or absence of a clear Basquin-type elastic strain–life relationship. Once this condition was verified, the corresponding stress amplitudes were evaluated using linear-elastic relations, intentionally avoiding elastic–plastic finite-element analysis. These stress amplitudes were then employed as intensity parameters in classical Wöhler equations, linking logarithmic stress measures to logarithmic fatigue life. The resulting stress–life curves were fitted using standard regression procedures, and predicted fatigue lives were directly compared with experimentally reported values over the low-cycle regime. The author found across aluminum alloys such as EN AW-2007 and EN AW-2024-T3, the agreement between predicted and experimental fatigue lives was consistently strong. Even under conditions involving multiaxial loading or elevated temperatures, the stress-based Wöhler predictions captured both slope and magnitude of fatigue life with mean errors typically within single-digit percentages. He also observed similar trends for steels spanning a wide strength range, including pressure vessel steels, martensitic alloys, and reduced-activation ferritic–martensitic steels. In these cases, despite significant plastic strain contributions, the stress-life relationships remained remarkably linear on logarithmic scales. Moreover, the performance of the method for materials traditionally viewed as strongly plasticity-dominated, such as Ti-6Al-4V and Inconel 718. For these alloys, one might expect linear-elastic stress measures to lose relevance. However, the results demonstrated that, provided the elastic strain component obeys a Basquin-type law, the Wöhler curve method remains capable of predicting low-cycle fatigue life with acceptable accuracy. Deviations do occur at very high plastic strain amplitudes, but these deviations are neither systematic nor severe enough to undermine the general applicability of the approach.

In conclusion, the work of Professor Xiangqiao Yan establishes clear conditions under which linear-elastic stress parameters can replace elastic–plastic strain measures without significant loss of accuracy. This offers a unified and computationally efficient route for fatigue life assessment across low, medium, and high cycle regimes. Additionally, the findings suggest that the success of the Wöhler curve method in low-cycle fatigue is not material-specific, but behavior-specific. Materials exhibiting linear elastic strain–life scaling inherently support stress-based life prediction, even when plastic deformation is non-negligible. This observation challenges the traditional dichotomy between stress-based and strain-based fatigue analysis and suggests a deeper continuity between fatigue regimes than is commonly acknowledged. The implications of Professor Xiangqiao Yan research are clear: stress-based fatigue analysis is inherently simpler, faster, and more compatible with linear-elastic finite-element simulations than strain-based approaches. If low-cycle fatigue life can be reliably estimated without recourse to elastic–plastic analysis, the computational burden associated with fatigue design can be substantially reduced. This is particularly relevant for large-scale structures, iterative optimization processes, and preliminary design stages, where efficiency often dictates methodological choices. Furthermore, the results suggest that low-cycle, medium-cycle, and high-cycle fatigue need not be treated as fundamentally distinct phenomena requiring separate analytical frameworks. Instead, they may be viewed as different manifestations of a unified stress–life relationship, provided the governing material response satisfies Basquin-type scaling. This perspective aligns fatigue analysis more closely with physical observation, where transitions between regimes are gradual rather than abrupt. The author also offered guidance on the limits of applicability and that the Wöhler curve method is not a universal replacement for strain-based approaches. Materials that do not exhibit linear elastic strain–life behavior, or loading conditions that induce severe cyclic softening or ratcheting, may still require full elastic–plastic treatment. However, by clearly identifying the class of “Basquin-type” materials, the work provides a rational criterion for method selection rather than reliance on convention. Furthermore, the success of the Wöhler curve method in low-cycle fatigue highlights the value of re-examining established tools with modern datasets and analytical clarity. It also opens the door to unified fatigue design methodologies that span the entire fatigue life spectrum without unnecessary complexity.