Experimental investigation of random loading sequence effect on fatigue crack growth

Abstract An experimental study is proposed to investigate the effect of random loading sequence effect on the fatigue crack growth behavior of Al 7075-T6. The testing matrix includes different overload cycle percentage, overload ratios, and deterministic and random loading sequences in the current investigation. Multiple specimen tests and statistical data analysis are performed to show the effect of random loading sequence on the median and scatter behavior of fatigue crack growth. The proposed experimental study suggests that extreme value distribution is a good approximation of fatigue life distribution. It is observed that the effect of uncertain loading is different under different loading spectrums. For high overload cycle percentage spectrums, the random loading sequence has no major impact on the probabilistic crack growth behavior compared to the deterministic loading sequence with identical load cycle distributions. For low overload cycle percentage spectrums, the random loading sequence has huge impact on the probabilistic crack growth behavior compared to the deterministic loading sequence with identical load cycle distributions, for both the median and the scatter of the fatigue crack length curves. Finally, all experimental observations are reported in table format in Appendix A for future numerical model development and validation for interested readers.

[1]  Thomas Svensson.  Prediction uncertainties at variable amplitude fatigue , 1997 .

[2]  Tatsuo Sakai,et al.  Statistical analysis of fatigue crack growth behavior for grade B cast steel , 2011 .

[3]  Jung-Kyu Kim,et al.  A statistical approach for predicting the crack retardation due to a single tensile overload , 2003 .

[4]  Wen-Fang Wu,et al.  Statistical aspects of some fatigue crack growth data , 2007 .

[5]  Darrell F. Socie,et al.  Simple rainflow counting algorithms , 1982 .

[6]  Tadeusz Łagoda,et al.  Fatigue lifetime under uniaxial random loading with different mean values according to some selected models , 2007 .

[7]  R. J. Anthes,et al.  Modified rainflow counting keeping the load sequence , 1997 .

[8]  Yongming Liu,et al.  Probabilistic fatigue life prediction using an equivalent initial flaw size distribution , 2009 .

[9]  M. Skorupa.  Load interaction effects during fatigue crack growth under variable amplitude loading : A literature review. Part I : Empirical trends , 1998 .

[10]  Sankaran Mahadevan,et al.  Stochastic fatigue damage modeling under variable amplitude loading , 2007 .

[11]  Peter J. Laz,et al.  Probabilistic fatigue life prediction using AFGROW and accounting for material variability , 2010 .

[12]  Yongming Liu,et al.  Crack growth-based fatigue life prediction using an equivalent initial flaw model. Part I: Uniaxial loading , 2010 .

[13]  Sankaran Mahadevan,et al.  Uncertainty quantification and model validation of fatigue crack growth prediction , 2011 .

[14]  J. Knott,et al.  TRANSIENT RETARDATIONS IN FATIGUE CRACK GROWTH FOLLOWING A SINGLE PEAK OVERLOAD , 1991 .

[15]  Chung-De Chen,et al.  The effects of material variations on aircraft inspection schedules based on stochastic crack growth model , 2008 .

[16]  S. M. Beden,et al.  Fatigue crack growth simulation of aluminium alloy under spectrum loadings , 2010 .

[17]  A. K. Khosrovaneh,et al.  Fatigue loading history reconstruction based on the rainflow technique , 1990 .

[18]  Farid Taheri,et al.  Experimental and analytical investigation of fatigue characteristics of 350WT steel under constant and variable amplitude loadings , 2003 .

[19]  You Ling,et al.  Stochastic prediction of fatigue loading using real-time monitoring data , 2011 .

[20]  P. Goel,et al.  The Statistical Nature of Fatigue Crack Propagation , 1979 .

[21]  Jaime Domínguez,et al.  Effect of load histories on scatter of fatigue crack growth in aluminum alloy 2024-T351 , 1997 .