Comparison of Calibration Functions for Short Edge Cracks under Selected Loads

Abstract

Attention to the fatigue cracks in steel structures and bridges has been paid for long time. In spite to efforts to eliminate the creation and propagation of fatigue cracks throughout the designed service life, cracks are still revealed during inspections. Note, that depending on location of initial crack, the crack may propagate from the edge or from the surface. The theoretical model of fatigue crack progression is based on linear fracture mechanics. Steel specimens are subjected to various load (tension, three-and four-point bending, pure bending etc.). The calibration functions for short edge cracks are compared for various load and the discrepancies are discussed.

Geometry Functions for Edge Cracks in Steel Bridge under Three- and Four- Point Bending with Various Span

“…2, the analytical results does not differ fundamentally only with small error from the numerical calculations presented in this work. The same conclusion was also reached by the team of authors in work [15].…”

“…Fatigue progression of the cracks from the edge and from the surface is used as a basis for proposing a system of inspections of details, which tend to be damaged by fatigue [2], [3], [4], sensitivity analysis [5] [6], probabilistic analysis of the S-N field [7], [8] and crack propagation rate [9] etc. The input data are usually material properties [10], [11], [12], [13], [14] and information about boundary conditions-calibration curves [15].…”

“…In analysis by Seitl et al 2017 [15], numerical solution for relatively short cracks (a/W varies from 0.05 to 0.3) is presented.…”

Stochastic modelling of fatigue crack growth

“…Kala, 2012;Kala, Valeš, & Jönsson, 2017;Jönsson, Müller, Gamst, Valeš, & Kala, 2019;Chalmovský et al, 2017) and sensitivity analysis (Kala & Valeš, 2018;Štefaňák, Kala, Miča, & Norkus, 2018). Stochastic modelling of fatigue processes is preceded by experimental research (Seitl, Miarka, Malíková, & Krejsa, 2017). Probabilistic methods along with linear fracture mechanics (Kala, 2008;Krejsa, Kala, & Seitl, 2016) and experimentally obtained data (Seitl et al, 2017) provide a widely usable platform for the analysis of basic and higher statistical characteristics of fatigue resistance.…”

“…Stochastic modelling of fatigue processes is preceded by experimental research (Seitl, Miarka, Malíková, & Krejsa, 2017). Probabilistic methods along with linear fracture mechanics (Kala, 2008;Krejsa, Kala, & Seitl, 2016) and experimentally obtained data (Seitl et al, 2017) provide a widely usable platform for the analysis of basic and higher statistical characteristics of fatigue resistance. The outputs of stochastic models provide information for decision-making methods, which results in the optimal selection of a procedure among several alternative options (Antucheviciene, Kala, Marzouk, & Vaidogas, 2015).…”