Probabilistic assessment of fatigue life for components under varying cyclic load

Fatigue lives of components subjected to varying cyclic load requires meeting certain level of reliability (vice versa probability of failure). To estimate reliability of such component different approaches like factor of safety approach, damage accumulation theories viz. Miner´s rule etc. have been proposed but are deterministic in nature. These approaches worked in practice but tend to be conservative in estimating component reliability. An alternate approach to have an accurate risk assessment and with intent to move from a deterministic approach to probabilistic approach is proposed here. This approach combines the stochastic nature of material strength & Miner´s rule of linear cumulative damage to estimate probability of failure. The approach uses finite element methods for stress estimation, historical data for accounting stochastic nature of material property, Monte-Carlo simulation for probability of failure assessment. This approach would be helpful during the predictive reliability assessment phase of DFR, before testing actual components.