Issue 38

C. Xianmin et alii, Frattura ed Integrità Strutturale, 38 (2016) 319-330; DOI: 10.3221/IGF-ESIS.38.42 329 the R 0 under which p-S-N curve is available using the constant life diagram [21]. C ONCLUSIONS atigue damage and fatigue life prediction for structures under variable amplitude loading are discussed in this paper. Several conclusions are made and listed as follows. The statistical damage accumulation model is based on Palmgren-Miner’s linear rule. However, the critical damage is considered as a variable depending on fatigue life distribution rather than a constant. Its mean value equals to unit. Therefore, the model is made self-consistent by introducing a consistent index b determined by numerical simulation and a random disturbance Δ. The load sequence effects are properly accounted in this model to accurately predict the fatigue life under variable amplitude loading. An exponential function exp (-f j ) is used to slow down the fatigue damage accumulation rate of materials under the low stress levels . This function is dependent on the stress ratio, i.e. 1 max / j j S S  and the multiplier v . This fatigue damage accumulation model provides a quantitative approach to statistically calculate the fatigue damage and fatigue life by considering the load sequence effects. The predictions by the present model coincide quite well with experimental results, indicating that it can well demonstrate the probabilistic nature of fatigue behavior. A CKNOWLEDGEMENT he support from the National Natural Science Foundation of China (Project No. 51601175) is greatly acknowledged. R EFERENCES [1] Miner, M.A., Cumulative damage in fatigue, J. Appl. Mech., 67 (1945) A159-164. [2] Marco, S.M., Starkey, W. L., A concept of fatigue damage, Transaction of the ASME, 76 (1954) 627-632. [3] Guangxu, C., Plumtree, A., A fatigue damage accumulation model based on continuum damage mechanics and ductility exhaustion, Int. J. Fatigue, 20(7) (1998) 495-501. [4] Oller, S., Salomón, O., Oñate, E., A Continuum Mechanics Model for Mechanical Fatigue Analysis, Comput. Mater. Sci., 32 (2005)175-195. DOI: 10.1016/j.commatsci.2004.08.001. [5] Scott-Emuakpor, O., An Energy-Based Uniaxial Fatigue Life Prediction Method for Commonly Used Turbine Engine Materials, ASME, J. Eng. Gas Turbines Power, 130 (2005) 062504. [6] Shen, H., Lin, J., Mu, E., Probabilistic model on stochastic fatigue damage, Int. J. Fatigue, 22(7) (2000) 569–572. [7] Nagode, M., Fajdiga, M., On a new method for prediction of the scatter of loading spectra, Int. J. Fatigue, 20(4) (1998) 271–277. [8] Wu, W.-F., Huang, T.-H., Prediction of fatigue damage and fatigue life under random loading, Int. J. Pres. Ves. Pip., 53(2) (1993) 273–298. [9] Wang, P., Coit, D. W., Reliability and degradation modeling with random or uncertain failure threshold, Reliability and Maintainability Symposium, (2007) 392–397. [10] Tovo, R., A damage-based evaluation of probability density distribution for rain-flow ranges from random processes, Int. J. Fatigue, 22 (2000) 425–429. [11] Castillo, E., Fernández-Canteli, A., Ruiz-Ripoll, M. L., A general model for fatigue damage due to any stress history, Int. J. Fatigue, 30(1) (2008) 150–164. DOI: doi:10.1016/j.ijfatigue.2007.02.011. [12] Rathod, V., Probabilistic Modeling of Fatigue Damage Accumulation for Reliability Prediction, Int. J. Qual. Stat. Reliab., (2011) 718901. [13] Xiasheng, S., et al, Guidelines for the Analysis and Design of Durability Aircraft Structures, Xi’an PR China, (2007). [14] Luc, D., Non-uniform random variate generation, Springer-Verlag, New York, (1986). [15] Yanbin, L., Study on the aircraft structure fatigue acceleration spectrum and the wide spread damage probabilistic model, Chinese aeronautical research institute, (2011). F T