摘要
In the first paper,a Y-T-F model was proposed based on the restrictions of both strength and plasticity;the corresponding applications on the fatigue strength prediction have also been discussed.In this second paper,the emphasis will be put on the issues of fatigue strength improvement.Based on the primary form of the Y-T-F model,the parameters are further analyzed and quantified,to clarify the influences of various factors on fatigue strength.Firstly,the damage capacity C is proved to be sensitive to the elastic modulus E,which could change with the alloying components and nano-scaled grain boundaries;the increase of E would lead to the increasing C,thus increase the fatigue strength.Secondly,the microstructure characteristic coefficient a,as well as the yield strengthσ_(y) and tensile strengthσ_(b) in the crack initiation region could be influenced by the processing mode,grain size and microstructure uniformity of materials;the change of microstructure characteristics would affect the changing tendency of tensile strength--fatigue strength relation via varying the values of a,σ_(y) andσ_(b).Thirdly,the damage weight coefficientωis found to be a reflection of the fatigue strength declination induced by defects;the defect dimension D,the defect shape correlated stress concentration coefficient Kt,as well as the strengthening level of matrix materialsσ_(b) are all corresponding factors.Quantified correlations between the above parameters and corresponding factors are comprehensively built up,hence obtaining the influences of either a single factor or multiple factors on fatigue strength.This further developed Y-T-F model would be helpful to clarify the direction of fatigue strength improvement,and contribute to the anti-fatigue design optimization of metallic materials.
基金
financially supported by the National Key R&D Program of China under grant No.2017YFB0703002
the National Natural Science Foundation of China(NSFC)under grant Nos.U1664253,51901230,51871223,51790482,51501198,51771208,51331007
the Strategic Priority Research Program of the Chinese Academy of Sciences under grant No.XDB22020202
the Youth Innovation Promotion Association CAS under grant No.2018226
the National Science and Technology Major Project under grant No.2017-VI-0003-0073
the LiaoNing Revitalization Talents Program under Grant No.XLYC1808027。
