Set-up of a Generalized Dataset for Crack-Closure-Mechanisms of Cast Steel
DOI:
https://doi.org/10.7494/jcme.2021.5.4.84Abstract
In components, crack propagation is subjected to crack-closure-mechanisms which affect the build-up of the relevant threshold stress intensity factor range during cyclic loading. As structural parts are exposed to service loads incorporating a variety of load ratios, a significant change of the long-crack threshold value occurs, leading to a severe stress ratio dependency of crack-closure-mechanisms. Thus, an extensive number of crack propagation experiments is required to gain statistically proven fracture mechanical parameters describing the build-up of closure effects as crack growth resistance curves.
The article presents a generalized dataset to assess the formation of crack-closure-mechanisms of cast steel G21Mn5+N. Numerous crack propagation experiments utilizing single edge notched bending (SENB) sample geometries are conducted, incorporating alternate to tumescent stress ratios. The statistically derived, generalized crack growth resistance curve features the impact of closure effects on the crack propagation rate in a uniform manner. To extend the dataset to arbitrary load ratios, the long-crack threshold approach according to Newman is invoked. The generalized dataset for the cast steel G21Mn5+N is validated by analytical fracture mechanical calculations for the utilized SENB-sample geometries. Incorporating a modified NASGRO equation, a sound correlation of analytical and experimental crack propagation rates is observed. Moreover, the derived master crack propagation resistance curve is implemented as a user-defined script into a numerical crack growth calculation tool and supports a local, node--based numerical crack propagation study as demonstrated for a representative SENB-sample. Concluding, the derived dataset facilitates the calculation of fatigue life of crack-affected cast steel components subjected to arbitrary stress ratios.
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Copyright (c) 2021 Michael Horvath, Matthias Oberreiter, Michael Stoschka, Martin Leitner
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