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Mean stress effects on low‐cycle fatigue for a precipitation‐hardening martensitic stainless steel in different tempers
Author(s) -
Kun-You Lin,
Xiaowen Chu
Publication year - 2000
Publication title -
fatigue and fracture of engineering materials and structures
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.887
H-Index - 84
eISSN - 1460-2695
pISSN - 8756-758X
DOI - 10.1046/j.1460-2695.2000.00324.x
Subject(s) - low cycle fatigue , materials science , martensitic stainless steel , metallurgy , martensite , precipitation hardening , hardening (computing) , fatigue testing , precipitation , stress (linguistics) , composite material , microstructure , linguistics , physics , philosophy , layer (electronics) , meteorology
The objective of this study is to investigate the effects of mean stress and ageing treatment on the low‐cycle fatigue (LCF) behaviour of a precipitation‐hardening martensitic stainless steel (PHMSS). Uniaxial LCF tests were conducted under strain control with three strain ratios, R = −1, 0 and 0.5 on specimens heat‐treated to three different tempers, i.e. solution‐annealed (SA), peak‐aged (H900) and overaged (H1150) conditions. Experimental results indicated that under a strain ratio of R = −1, specimens in H900 temper exhibited longer LCF lifetimes than those in SA and H1150 tempers. However, this advantage for H900 over SA and H1150 tempers disappeared at higher strain ratios ( R = 0 and 0.5) due to the greater sensitivity to mean stress effects in H900 temper. For a given temper at high strain amplitudes, the LCF lifetimes under the three applied strain ratios did not show significant differences as a result of the mean stress relaxation effect. However, at low strain amplitudes, cyclic loading at R = −1 generated longer LCF lifetimes in comparison to R = 0 and 0.5 due to the absence of detrimental tensile mean stress. LCF lifetime data obtained for the given PHMSSs under various combinations of strain ratio and heat treatment were well correlated with a strength‐normalized Smith–Watson–Topper (SWT) parameter in a log–log linear model.