4.7 Article

Scaled fatigue cracks under service loads

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DOI: 10.1016/j.tafmec.2023.103991

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Scaling; Fracture mechanics; Fatigue; Finite similitude; Size effects; Damage tolerance

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New similitude rules are explored in numerical experiments for industrially representative fatigue-crack growth scenarios, showing for the first time how geometric size effects in mixed mode fatigue tests can be eliminated through appropriately designed scaled experiments. The new rules accurately predict crack-path and have errors ranging from 1% to 9% in lifecycle predictions.
Scaled experimentation is a powerful engineering tool yet its application to fatigue is limited by significant changes in behaviour with scale. The recent discovery of new similitude rules however opens new possibilities that are explored in this work through numerical experimentation for industrially representative fatigue-crack growth scenarios. It is shown for the first time, how the geometric size effects present in mixed mode fatigue tests are eliminated by performing two appropriately designed scaled experiments. The first order finite simil-itude theory is applied to mixed mode (modes I and II) fatigue crack growth in three case studies, viz., compact tension shear (CTS) specimen, wing fuselage attachment lug, and a T-joint with an inclined semi elliptical crack. Both planar and non-planar crack growth feature, along with surface and through thickness cracks. Low and high cycle fatigue (up to circa 60,000 cycles) is examined for three different materials (Al-6061 T6 alloy, structural steel, and AISI 316 stainless steel) under a variety of load ratios. The new rules return near exact crack-path predictions whereas lifecycle predictions have errors ranging between 1 % and 9 %. Paris law constants C and m are predicted with up to 99.9 % accuracy supporting the theory that Paris law is a first order similitude rule. Geometric size effects afflicting industrial type scaled-fatigue studies employing a damage tolerant design approach are confirmed to be eliminated on combination of information from two appropriately designed scaled models.

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