An engineering methodology for constraint corrections of elastic–plastic fracture toughness – Part II: Effects of specimen geometry and plastic strain on cleavage fracture predictions

The microstructure, mechanical strength, and fatigue response of metal active gas (MAG) butt‐welded G20Mn5 cast steel was thoroughly investigated for exploring the service safety and reliability of new‐generation railway bogie frames. The fatigue properties of the matrix and welded joints were determined by both low‐ and high‐cycle service regimes. On the basis of nanoindentation testing, the fatigue crack growth (FCG) was derived by correlating with cyclic plastic response of microdomain materials across the MAG joint. The results show that the MAG induces considerable changes in microstructures and hardness of the G20Mn5 matrix and resultantly produces an overmatching welded joint but show comparatively low‐ and high‐cycle fatigue properties to as‐received material. The calculated threshold FCG range based on the Murakami model indicates that the maximum 1.5‐mm defect might be the cracking site subjected to fatigue loading from the structural integrity viewpoint.

Section: Resultsmentioning

confidence: 99%

Section: Fatigue Crack Resistancementioning

confidence: 99%

The microstructure, mechanical, and fatigue behaviours of MAG welded G20Mn5 cast steel

Qin

Branco

et al. 2020

“…The Beremin model has suffered from the ambiguity in model parameter calibration, ie, the variation of the model parameters with temperature and geometrical constraint. Many empirical modifications to the Beremin model have been proposed by either introducing a fixed‐value threshold stress (σ th ), eg, in the literature, or incorporating the plastic strain (ε p ) effect, eg, in Ruggieri et al As a result, different expressions of the Weibull stress σ W have been proposed to calculate the cumulative probability based on Equation . Here are 2 examples that used a fixed‐vale threshold stress σ th for modifications: Bakker and Koers redefined the Weibull stress σ W in Equation as

σ_{W} = {({normal\int}_{V_{p}} {((), σ_{1} - σ_{th})}^{m} \cdot dV / V_{0})}^{1 / m} .

…”

Section: Introductionmentioning

confidence: 99%

“…Recent studies have identified the fundamental defects of the Beremin model, which are summarized in Table . Note that some of the highlighted fundamental defects are inherited by those modifications to the Beremin model, such as the incompliance with the physical assumption of plastic yielding as a prerequisite to cleavage fracture due to the adoption of a fixed‐value threshold stress σ th (including the case of σ th = 0), and the violation to the normality axiom of probability owing to the adoption of Equation 6a as the basic formulation of cumulative probability P . An example was elaborated in detail in the commentary to the work in Ruggieri et al In Table , the necessary corrections to the Beremin model are also provided to ensure the mathematical rigorousness and the physical compliance with the 5 assumptions below: The uniform spatial distribution of microcracks The weakest‐link postulate of brittle fracture Plastic yielding as a prerequisite for cleavage fracture The maximum tensile principal stress criterion for cleavage fracture (Equation 8) The power‐law distribution of microcrack size (Equation 9) …”

Section: Introductionmentioning

confidence: 99%

Statistical assessment of notch toughness against cleavage fracture of ferritic steels

Qian

Lei

Liu³

et al. 2017

The work is an initial effort on adopting a statistical approach to correlate the fracture behavior between a notched and a fracture mechanics specimen. The random nature of cleavage fracture process determines that both the microscopic fracture stress and the macroscopic properties including fracture load, fracture toughness, and the ductile to brittle transition temperature are all stochastic parameters. This understanding leads to the proposal of statistical assessment of cleavage induced notch brittleness of ferritic steels according to a recently proposed local approach model of cleavage fracture. The temperature independence of the 2 Weibull parameters in the new model induces a master curve to correlate the fracture load at different temperatures. A normalized stress combining the 2 Weibull parameters and the yield stress is proposed as the deterministic index to measure notch toughness. This proposed index is applied to compare the notch toughness of a ferritic steel with 2 different microstructures.

“…18 The Weibull stress model predicates on the experimentally validated weakest-link assumption 19 and entails a unique relationship 20 between the local scalar Weibull stress (σ w ) and the global crack driving force (K J ), which allows successful estimations of the cleavage failure for both the highconstraint and low-constraint specimens. 21 Subsequent development of the local Weibull stress approach incorporates the plastic-strain dependent distribution of the microcrack distribution, 22,23 the effect of prior ductile tearing, 24,25 and the assessment of surface cracks 26 and mixed-mode fracture. 27,28 Wasiluk et al 21 have updated the calibration procedure for the Weibull stress parameters, which requires two sets of fracture specimens with contrast differences in the crack-front constraint to resolve the uniqueness issue in calibrating the Weibull stress parameters through a single set of specimens.…”

Section: Introductionmentioning

confidence: 99%

Effect of experimental sample size on local Weibull assessment of cleavage fracture for steel

Zhang

Qian

2016

This paper examines the sample size of the experimental datasets in calibrating the Weibull parameters for the modified three‐parameter Weibull stress framework, so as to enhance the experimental strategy for cleavage assessment of ferritic steels based on a local approach. The present work generates a large number of random and independent subsets from the ‘Euro steel’ fracture toughness database for the calibration procedure. The calibration of the Weibull parameters utilizes a subset of high‐constraint specimens and a subset of low‐constraint specimens from the Euro steel database to resolve the uniqueness issue in the calibration procedure reported in previous studies. This investigation reveals strong dependence of the calibrated Weibull modulus on both the constraint differences between the high‐constraint subset and the low‐constraint subset and the size of the selected subsets. The scale fracture toughness value, however, does not exhibit significant dependence on the constraint difference between the two subsets of specimens. The confidence level of the scale fracture toughness, nevertheless, still exhibits strong dependence on the sample size of the experimental data.