Effect of Void Nucleation on Fracture Toughness of High-Strength Austenitic Steels

Purtscher, P. T.; Reed, RP; Read, DT

doi:10.1520/stp18836s

Cited by 2 publications

(4 citation statements)

References 17 publications

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“…Besides the high number of calibration constants, the GTN model requires a quantification of the critical void volume f c , at which coalescence occurs. As opposed to observations in the literature for conventionally manufactured material [31], no global change in this void volume fraction could be observed in the experiments for additively manufactured IN718 specimens (see Figure A2a in Appendix A). This impedes a physically-based determination of f c .…”

Section: Model Descriptioncontrasting

confidence: 98%

Towards a Simulation-Assisted Prediction of Residual Stress-Induced Failure during Powder Bed Fusion of Metals Using a Laser Beam: Suitable Fracture Mechanics Models and Calibration Methods

Panzer,

Wolf,

Bachmann

et al. 2023

JMMP

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In recent years, Additive Manufacturing (AM) has emerged as a transformative technology, with the process of Powder Bed Fusion of Metals using a Laser Beam (PBF-LB/M) gaining substantial attention for its precision and versatility in fabricating metal components. A major challenge in PBF-LB/M is the failure of the component or the support structure during the production process. In order to locate a possible residual stress-induced failure prior to the fabrication of the component, a suitable failure criterion has to be identified and implemented in process simulation software. In the work leading to this paper, failure criteria based on the Rice-Tracey (RT) and Johnson-Cook (JC) fracture models were identified as potential models to reach this goal. The models were calibrated for the nickel-based superalloy Inconel 718. For the calibration process, a conventional experimental, a combined experimental and simulative, and an AM-adapted approach were applied and compared. The latter was devised to account for the particular phenomena that occur during PBF-LB/M. It was found that the JC model was able to capture the calibration data points more precisely than the RT model due to its higher number of calibration parameters. Only the JC model calibrated by the experimental and AM-adapted approach showed an increased equivalent plastic failure strain at high triaxialities, predicting a higher cracking resistance. The presented results can be integrated into a simulation tool with which the potential fracture location as well as the cracking susceptibility during the manufacturing process of PBF-LB/M parts can be predicted.

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Section: Model Descriptioncontrasting

confidence: 98%

Towards a Simulation-Assisted Prediction of Residual Stress-Induced Failure during Powder Bed Fusion of Metals Using a Laser Beam: Suitable Fracture Mechanics Models and Calibration Methods

Panzer,

Wolf,

Bachmann

et al. 2023

JMMP

View full text Add to dashboard Cite

show abstract

“…(4) was not determined independently, the model predictions are reasonable since the range of I* values is two to three times the mean SiC-particle spacing of 3 to 4 pm [ 1,9] Modelled E)! Previous studies of nucleation-controlled MNG in steels coupled expressions for the crack-tip strain field and void-nucleation strain to obtain predictions for the critical K at fracture initiation [4,22,23]. This approach is essentially followed here although the form of Eq.…”

Section: Experimental Efmentioning

confidence: 99%

“…Although Modelled E)! Previous studies of nucleation-controlled MNG in steels coupled expressions for the crack-tip strain field and void-nucleation strain to obtain predictions for the critical K at fracture initiation [4,22,23]. This approach is essentially followed here although the form of Eq.…”

Section: Experimental Efmentioning

confidence: 99%

“…In this model the stress concentration at the particle interface depends on the crack-tip strain field, particle interactions and constraint of matrix plastic flow. A model which considered the first factor, plus the remote mean stress, predicted the nucleation-controlled fracture toughness of high-strength ferritic and austenitic steels [ 4,22,23]. Otherwise, strain-based fracture-mechanics models of toughness have not been applied to nucleation-controlled MNG.…”

Section: Introductionmentioning

confidence: 99%

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Elevated Temperature Fracture of Particulate‐reinforced Aluminum Part Ii: Micromechanical Modelling

Somerday

Leng

Gangloff

1995

Fatigue Fract Eng Mat Struct

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Micromechanical fracture-toughness models are applied to experimental results for a metalmatrix composite (2009/SiC/20p-T6) to understand the temperature dependencies of toughness and fracture mechanisms, as well as to test quantitatively a continuum fracture-mechanics approach. Models which couple the crack-tip strain field, characteristic fracture-process distance and measured intrinsic microvoid-fracture resistance predict the temperature dependencies of fracture-initiation (KJla) and crackgrowth (&) toughnesses from 25°C to 316°C. The temperature dependencies of KJla and TR result from the interplay between the fracture resistance and the crack-tip strain field, each being temperaturedependent. Strain-based models are equally valid for void nucleation-or growth-controlled fracture. A scenario for fracture is nucleation-controlled damage within Sic-particle clusters, corresponding to KnCi, followed by cluster-damage growth to coalescence under increasing stress intensity. Void growth is stabilized increasingly at elevated temperatures. NOMENCLATURE a = crack length a* = Sic-particle flaw size C1 = curve-fitting constant for crack-tip HP distribution C2 = curve-fitting constant for crack-tip Bp distribution d, = variable in relationship between 3 and 6, D = average void-nucleating-particle diameter e = natural-logarithm base E = elastic modulus f, = average void-nucleating-particle volume fraction 3 = 3-integral J,, = standard value of critical 3 for initial crack extension K = stress-intensity factor Klc = standard value of critical K for initial crack extension Kna = lower-bound value of critical K for initial crack extension calculated from 3 K,,,-eps = K,,, predicted from strain-controlled model using experimental E;* K,,,-nuc = K,,, predicted from strain-controlled model using modelled E;* KjIa-RJ = K,,, predicted from Rice-Johnson model I* = characteristic fracture-process distance m = strain rate-hardening exponent n = strain-hardening exponent r = radial distance from crack tip r, = distance behind crack tip at which 6, is defined TR = tearing modulus Z = variable in expression for 6, a = constant which defines average stress elevation around particle a, = constant which defines ''local'' stress elevation near particle comer B = constant in expression for 6 , 6, = critical value of 6 , 6, = stationary-crack-tip opening displacement 103 1 1032 B. P. SOMERDAY et al. 6, = moving-crack-tip opening displacement 8 = effective plastic strain Ef = critical crack-tip process-zone effective plastic fracture strain K = Variable in expression for S , 1 = mean spacing of void-nucleating particles v = Poisson's ratio 62 = material-property parameter in model prediction for62 * = value of 62 at "brittle"-to-"ductile" fracture transition ufl = Bow stress ufnt = ootched-tensile fracture stress u, = local stress near particle u,,, = mean stress u,, = Rambergasgood reference stress us = stressconcentration component of u, bum = ultimate tensile stress uy, = 0.2%-offset yield stress ur = critical stress for particle frac...

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Effect of Void Nucleation on Fracture Toughness of High-Strength Austenitic Steels

Cited by 2 publications

References 17 publications

Towards a Simulation-Assisted Prediction of Residual Stress-Induced Failure during Powder Bed Fusion of Metals Using a Laser Beam: Suitable Fracture Mechanics Models and Calibration Methods

Towards a Simulation-Assisted Prediction of Residual Stress-Induced Failure during Powder Bed Fusion of Metals Using a Laser Beam: Suitable Fracture Mechanics Models and Calibration Methods

Elevated Temperature Fracture of Particulate‐reinforced Aluminum Part Ii: Micromechanical Modelling

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