Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/142403
Title: Predictive models for fatigue property of laser powder bed fusion stainless steel 316L
Authors: Zhang, Meng
Sun, Chen-Nan
Zhang, Xiang
Wei, Jun
Hardacre, David
Li, Hua
Keywords: Engineering::Mechanical engineering
Issue Date: 2018
Source: Zhang, M., Sun, C.-N., Zhang, X., Wei, J., Hardacre, D., & Li, H. (2018). Predictive models for fatigue property of laser powder bed fusion stainless steel 316L. Materials and Design, 145, 42-54. doi:10.1016/j.matdes.2018.02.054
Journal: Materials and Design
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.
URI: https://hdl.handle.net/10356/142403
ISSN: 0261-3069
DOI: 10.1016/j.matdes.2018.02.054
Rights: © 2018 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SC3DP Journal Articles

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.