| Literature DB >> 29088707 |
Qingsong Pan1, Haofei Zhou2, Qiuhong Lu1, Huajian Gao2, Lei Lu1.
Abstract
Nearly 90 per cent of service failures of metallic components and structures are caused by fatigue at cyclic stress amplitudes much lower than the tensile strength of the materials involved. Metals typically suffer from large amounts of cumulative, irreversible damage to microstructure during cyclic deformation, leading to cyclic responses that are unstable (hardening or softening) and history-dependent. Existing rules for fatigue life prediction, such as the linear cumulative damage rule, cannot account for the effect of loading history, and engineering components are often loaded by complex cyclic stresses with variable amplitudes, mean values and frequencies, such as aircraft wings in turbulent air. It is therefore usually extremely challenging to predict cyclic behaviour and fatigue life under a realistic load spectrum. Here, through both atomistic simulations and variable-strain-amplitude cyclic loading experiments at stress amplitudes lower than the tensile strength of the metal, we report a history-independent and stable cyclic response in bulk copper samples that contain highly oriented nanoscale twins. We demonstrate that this unusual cyclic behaviour is governed by a type of correlated 'necklace' dislocation consisting of multiple short component dislocations in adjacent twins, connected like the links of a necklace. Such dislocations are formed in the highly oriented nanotwinned structure under cyclic loading and help to maintain the stability of twin boundaries and the reversible damage, provided that the nanotwins are tilted within about 15 degrees of the loading axis. This cyclic deformation mechanism is distinct from the conventional strain localizing mechanisms associated with irreversible microstructural damage in single-crystal, coarse-grained, ultrafine-grained and nanograined metals.Entities:
Year: 2017 PMID: 29088707 DOI: 10.1038/nature24266
Source DB: PubMed Journal: Nature ISSN: 0028-0836 Impact factor: 49.962