Predicting stochastic behaviour of fatigue crack nucleation and small crack growth in ductile alloys based on stochastic behaviour of large crack growth

Statistical fatigue life of a ductile alloy specimen is traditionally divided into three phases, viz., crack nucleation, small crack growth and large crack growth. Crack nucleation and small crack growth shows a wide variation and hence a big spread on life in cycles versus crack length graph. Relatively, large crack growth shows a lesser variation. It is also easier to carry out crack length measurements of large cracks compared to nucleating cracks and small cracks. Thus, it is easier to collect statistical data for large crack growth compared to painstaking effort it would take to collect statistical data for crack nucleation and small crack growth. This paper presents a fracture mechanics based stochastic model of fatigue crack growth in ductile alloys that are commonly encountered in mechanical structures and machine components. This model has been validated [1] for crack propagation by various statistical fatigue data. Extending this model, this paper proposes a technique to predict statistical information of fatigue crack nucleation and small crack growth properties based on the statistical properties of large crack growth under constant amplitude stress excitation. The statistical properties of large crack growth under constant amplitude stress excitation can be obtained via experiments