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The mechanistic driver for fatigue crack nucleation in metals has remained controversial for decades. To address this, an in-situ digital image correlation technique combined with multi-scale modeling approaches is employed to assess the predictive capabilities of various fatigue indicator parameters (FIPs) for the microcrack nucleation in single crystals. While conventional stress- and strain-based FIPs show limited correlations with observed fatigue cracking sites, energy-based metrics, particularly dissipative energy density (DED) and stored energy density (SED), exhibit significant spatial alignment with nucleation locations. Compared with DED, SED is a more indicative and unambiguous indicator, owing to the incorporation of geometrically necessary dislocations (GNDs). We experimentally reveal a previously unrecognized cyclic-loading effect in low-cycle fatigue: competing strain growth across slip traces generates additional troughs in GND density and corresponding SED peaks, whereas this cyclic-loading effect is absent in high-cycle fatigue. By elucidating the critical role of GND-mediated damage localization, this work advances microstructure-sensitive fatigue damage prediction and provides a physics-based framework for more reliable fatigue life assessment in metallic systems.
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Guo et al. (2025) studied this question.
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