Residual strength is usually used to characterize the degradation rule of material performance under
the cyclic load, which is critical to fatigue life prediction as well as reliability assessment of materials. In order to
reveal the probability characteristics of residual strength of material under uncertain cyclic load, the relationship
between external stress and fatigue life (i.e., the equation of S-N curve) is considered in this study. Firstly,
the probability density function of fatigue life under uncertain cyclic load is derived from the probability density
function of external stress. Then, a probability model of residual strength is proposed on the basis of a fundamental
assumption that the residual strength and the remaining life of material depend on the same damage state. Finally,
the validity of the proposed model is verified by an illustrative example. The results indicate that the probability
distribution of residual strength of material is affected by both the external factor (i.e., probability characteristics
of the load) and the internal factor (i.e., fatigue performance parameters of material).
GAO Jianxiong (高建雄), AN Zongwen (安宗文), MA Qiang (马强), ZHAO Shendan (赵申诞)
. Probability Model of Residual Strength of Materials Under Uncertain Cyclic Load[J]. Journal of Shanghai Jiaotong University(Science), 2020
, 25(2)
: 266
-272
.
DOI: 10.1007/s12204-020-2172-5
[1] LI B C, JIANG C, HAN X, et al. A new approach of fatigue life prediction for metallic materials under multiaxial loading [J]. International Journal of Fatigue, 2015, 78: 1-10.
[2] GAO H Y, ZUO F J, L¨U Z Q, et al. Residual life prediction based on nonlinear fatigue damage accumulation model [J]. Journal of Shanghai Jiao Tong University(Science), 2015, 20(4): 449-453.
[3] CHEN Y X, ZHANG Q, CAI Z Y, et al. Storage reliability assessment model based on competition failure of multi-components in missile [J]. Journal of Systems Engineering and Electronics, 2017, 28(3): 606-616.
[4] HUANG T T, LI Z Z. Accelerated proportional degradation hazards-odds model in accelerated degradation test [J]. Journal of Systems Engineering and Electronics,2015, 26(2): 397-406.
[5] GAO Y Y, SU Z X. Nonlinear fatigue damage model based on the residual strength degradation law [J].JSME International Journal Series A: Solid Mechanics and Material Engineering, 2002, 45(2): 305-308.
[6] WANG N, XIE L Y, SONG W L, et al. Residual strength degradation model for low-alloy steel in high cycle fatigue load [J]. Advanced Materials Research,2010, 118/119/120: 474-478.
[7] SLESAREV D A, VORONTSOV A N. The probabilistic characteristics of estimation of the residual strength and operation lifetime of steel wire rope based on the results of non-destructive testing [J]. Russian Journal of Nondestructive Testing, 2016, 52(2): 95-101.
[8] KIMJH, LEES P, JINJW, et al. Estimation for probabilistic distribution of residual strength of sandwich structure with impact-induced damage [J]. Renewable Energy, 2013, 54: 219-226.
[9] PARAMONOV Y, CIMANIS V, VARICKIS S, et al.Modeling the residual strength of a fibrous composite using the residual Daniels function [J]. Mechanics of Composite Materials, 2016, 52(4): 497-506.
[10] HUANG H Z, ZHU S P, WANG Z L, et al. Nonlinear fatigue damage cumulative rule based on strength degradation and its application to fatigue life reliability analysis [J]. Journal of Basic Science and Engineering,2011, 19(2): 323-334 (in Chinese).
[11] LI S H, CHEN J J, FANG Y F. Analysis of the fatigue reliability for structural element under multilevel loads based on the residual strength model [J].Mechanical Science and Technology for Aerospace Engineering,2013, 32(6): 791-795 (in Chinese).
[12] D’AMORE A, GIORGIO M, GRASSIA L. Modeling the residual strength of carbon fiber reinforced composites subjected to cyclic loading [J]. International Journal of Fatigue, 2015, 78: 31-37.
[13] AN Z W, GAO J X, LIU B. Stochastic model of strength degradation based on P-S-N curve [J].Chinese Journal of Computational Mechanics, 2015,32(1): 118-122 (in Chinese).
[14] STOJKOVI′C N, FOLI′C R, PASTERNAK H. Mathematical model for the prediction of strength degradation of composites subjected to constant amplitude fatigue [J]. International Journal of Fatigue, 2017, 103:478-487.
[15] ZHAI J M, LI X Y. A methodology to determine a conditional probability density distribution surface from S-N data [J]. International Journal of Fatigue, 2012,44: 107-115.
[16] XIE L Y, WANG Z. Dissimilar-dimension interference model of fatigue reliability under uncertain cyclic load [J]. Journal of Mechanical Engineering, 2008, 44(1):1-6 (in Chinese).
[17] ZUO F J, ZHU S P, GAO H Y, et al. Stochastic fatigue life and reliability prediction based on residual strength [J]. Journal of Shanghai Jiao Tong University (Science), 2015, 20(3): 331-337.
[18] XIE L Y, LIU J Z, WU N X, et al. Backwards statistical inference method for P-S-N curve fitting with small-sample experiment data [J]. International Journal of Fatigue, 2014, 63: 62-67.
[19] XIE W, HUANG Q Q, LI Y Z, et al. Study on the fatigue performance of 2524-T3 aluminum alloy with rivet-filled countersink hole [J]. Advances in Aeronautical Science and Engineering, 2012, 3(1): 82-86 (in Chinese).