Predictive models for fatigue property of laser powder bed fusion stainless steel 316L

Meng Zhang; Chen-Nan Sun; Xiang Zhang; Jun Wei; David Hardacre; Hua Li

doi:10.1016/j.matdes.2018.02.054

Predictive models for fatigue property of laser powder bed fusion stainless steel 316L

Meng Zhang, Chen-Nan Sun, Xiang Zhang, Jun Wei, David Hardacre, Hua Li

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Abstract

The selection of appropriate processing parameters is crucial for producing parts with target properties via the laser powder bed fusion (L-PBF) process. In this work, the fatigue properties of L-PBF stainless steel 316L under controlled changes in laser power and scan speed were studied by employing the statistical response surface method. Processing regions corresponding to different fatigue failure mechanisms were identified. The optimum fatigue properties are associated with crack initiation from microstructure defect, which, by acting as the weakest link, creates enhanced porosity-tolerance at applied stress approaching the fatigue limit. Deviations from the optimum processing condition lead to strength degradation and porosity-driven cracking. Based on the observed relations between microstructural features and failure behaviour, a processing-independent fatigue prediction model was proposed. The microstructure-driven failure was modelled by a reference S-N curve where the intrinsic effect of microstructure inhomogeneity was accounted for by applying a reduction factor on fatigue life. For the porosity-driven failure, high cycle fatigue life follows an inverse-square-root relation with porosity fraction. This relation was incorporated into the Basquin equation for predicting the fatigue strength parameters.

Original language	English
Pages (from-to)	42-54
Number of pages	13
Journal	Materials & Design
Volume	145
Early online date	19 Feb 2018
DOIs	https://doi.org/10.1016/j.matdes.2018.02.054
Publication status	Published - 5 May 2018

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in Materials & Design. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Materials & Design, [145, (2018)] DOI: 10.1016/j.matdes.2018.02.054

© 2018, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

fatigue
selective laser melting
stainless steel 316L
Basquin equation
predictive model
porosity

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10.1016/j.matdes.2018.02.054

Post-PrintAccepted author manuscript, 3.07 MBLicence: CC BY-NC-ND

Xiang Zhang
- Centre for Manufacturing and Materials - Professor in Structural Integrity
Person: Teaching and Research

Cite this

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title = "Predictive models for fatigue property of laser powder bed fusion stainless steel 316L",

abstract = "The selection of appropriate processing parameters is crucial for producing parts with target properties via the laser powder bed fusion (L-PBF) process. In this work, the fatigue properties of L-PBF stainless steel 316L under controlled changes in laser power and scan speed were studied by employing the statistical response surface method. Processing regions corresponding to different fatigue failure mechanisms were identified. The optimum fatigue properties are associated with crack initiation from microstructure defect, which, by acting as the weakest link, creates enhanced porosity-tolerance at applied stress approaching the fatigue limit. Deviations from the optimum processing condition lead to strength degradation and porosity-driven cracking. Based on the observed relations between microstructural features and failure behaviour, a processing-independent fatigue prediction model was proposed. The microstructure-driven failure was modelled by a reference S-N curve where the intrinsic effect of microstructure inhomogeneity was accounted for by applying a reduction factor on fatigue life. For the porosity-driven failure, high cycle fatigue life follows an inverse-square-root relation with porosity fraction. This relation was incorporated into the Basquin equation for predicting the fatigue strength parameters.",

keywords = "fatigue, selective laser melting, stainless steel 316L, Basquin equation, predictive model, porosity",

author = "Meng Zhang and Chen-Nan Sun and Xiang Zhang and Jun Wei and David Hardacre and Hua Li",

note = "NOTICE: this is the author{\textquoteright}s version of a work that was accepted for publication in Materials & Design. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Materials & Design, [145, (2018)] DOI: 10.1016/j.matdes.2018.02.054 {\textcopyright} 2018, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/",

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doi = "10.1016/j.matdes.2018.02.054",

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AU - Zhang, Meng

AU - Sun, Chen-Nan

AU - Zhang, Xiang

AU - Wei, Jun

AU - Hardacre, David

AU - Li, Hua

N1 - NOTICE: this is the author’s version of a work that was accepted for publication in Materials & Design. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Materials & Design, [145, (2018)] DOI: 10.1016/j.matdes.2018.02.054 © 2018, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

PY - 2018/5/5

Y1 - 2018/5/5

N2 - The selection of appropriate processing parameters is crucial for producing parts with target properties via the laser powder bed fusion (L-PBF) process. In this work, the fatigue properties of L-PBF stainless steel 316L under controlled changes in laser power and scan speed were studied by employing the statistical response surface method. Processing regions corresponding to different fatigue failure mechanisms were identified. The optimum fatigue properties are associated with crack initiation from microstructure defect, which, by acting as the weakest link, creates enhanced porosity-tolerance at applied stress approaching the fatigue limit. Deviations from the optimum processing condition lead to strength degradation and porosity-driven cracking. Based on the observed relations between microstructural features and failure behaviour, a processing-independent fatigue prediction model was proposed. The microstructure-driven failure was modelled by a reference S-N curve where the intrinsic effect of microstructure inhomogeneity was accounted for by applying a reduction factor on fatigue life. For the porosity-driven failure, high cycle fatigue life follows an inverse-square-root relation with porosity fraction. This relation was incorporated into the Basquin equation for predicting the fatigue strength parameters.

AB - The selection of appropriate processing parameters is crucial for producing parts with target properties via the laser powder bed fusion (L-PBF) process. In this work, the fatigue properties of L-PBF stainless steel 316L under controlled changes in laser power and scan speed were studied by employing the statistical response surface method. Processing regions corresponding to different fatigue failure mechanisms were identified. The optimum fatigue properties are associated with crack initiation from microstructure defect, which, by acting as the weakest link, creates enhanced porosity-tolerance at applied stress approaching the fatigue limit. Deviations from the optimum processing condition lead to strength degradation and porosity-driven cracking. Based on the observed relations between microstructural features and failure behaviour, a processing-independent fatigue prediction model was proposed. The microstructure-driven failure was modelled by a reference S-N curve where the intrinsic effect of microstructure inhomogeneity was accounted for by applying a reduction factor on fatigue life. For the porosity-driven failure, high cycle fatigue life follows an inverse-square-root relation with porosity fraction. This relation was incorporated into the Basquin equation for predicting the fatigue strength parameters.

KW - fatigue

KW - selective laser melting

KW - stainless steel 316L

KW - Basquin equation

KW - predictive model

KW - porosity

U2 - 10.1016/j.matdes.2018.02.054

DO - 10.1016/j.matdes.2018.02.054

M3 - Article

SN - 0264-1275

VL - 145

SP - 42

EP - 54

JO - Materials & Design

JF - Materials & Design

ER -

Predictive models for fatigue property of laser powder bed fusion stainless steel 316L

Abstract

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