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A model for fatigue crack growth, part I: phenomenology*
Author(s) -
T. J. Lang
Publication year - 2000
Publication title -
fatigue and fracture of engineering materials and structures
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.887
H-Index - 84
eISSN - 1460-2695
pISSN - 8756-758X
DOI - 10.1046/j.1460-2695.2000.00297.x
Subject(s) - crack closure , paris' law , materials science , crack growth resistance curve , structural engineering , residual stress , fracture mechanics , phenomenological model , stress intensity factor , ultimate tensile strength , mechanics , metallurgy , composite material , mathematics , engineering , physics , statistics
A fatigue crack growth model for metals is presented in this two part paper. The model is based on experimental evidence obtained on the aluminium alloy Al 7475‐T7351. In Part I of this paper, the physical basis of the model is discussed. The model accounts for residual compressive stresses ahead of the crack front and crack closure, which constitute an intrinsic and extrinsic effect, respectively. The centre of this model is the crack propagation stress intensity factor, K PR . There are two basic sequences involving a load step following constant amplitude loading which cause two different types of transitional processes that are fundamental to fatigue crack growth. An increase in the maximum load causes instant and ‘dynamic’ changes in K PR . This transition in K PR is cycle dependent. An example is a multiple overload sequence. A decrease in the maximum load causes a crack growth dependent transition. Crack growth retardation after a tensile overload is an example of this type of a transition. The general description of these two transitional processes constitutes the complete solution for the fatigue crack growth problem in metals for Mode 1 loading. Part I of this paper provides the general description of the two transitional processes in terms of K PR . In Part II, the results of Part I are generalised, which leads to a new fatigue crack growth prediction model for variable amplitude loading.