S
Shengchuan Wu
Researcher at Southwest Jiaotong University
Publications - 125
Citations - 3174
Shengchuan Wu is an academic researcher from Southwest Jiaotong University. The author has contributed to research in topics: Engineering & Fatigue limit. The author has an hindex of 24, co-authored 84 publications receiving 1758 citations. Previous affiliations of Shengchuan Wu include Xi'an Jiaotong University & Huazhong University of Science and Technology.
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Journal ArticleDOI
The effect of manufacturing defects on the fatigue life of selective laser melted Ti-6Al-4V structures
Yanan Hu,Shengchuan Wu,Shengchuan Wu,Philip J. Withers,J. Zhang,H.Y.X. Bao,Y.N. Fu,Guozheng Kang +7 more
TL;DR: In this paper, an eXtended defect zone (XDZ) describing the propensity for local plasticity during fatigue around a defect has been shown through numerical analysis to be a good indicator of the ranking of the threat to fatigue caused by differently located manufacturing defects.
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The imaging of failure in structural materials by synchrotron radiation X-ray microtomography
TL;DR: A review of the application of synchrotron radiation X-ray computed microtomography (SR-μCT) to the study of internal damage accumulation and evolution in structural materials including cast irons and steel, nickel superalloys, lightweight titanium and aluminum alloys as well as metallic, ceramic and polymer composite materials together with additatively manufactured or three-dimensional (3D) printed metallic materials can be found in this paper.
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An edge-based smoothed finite element method (ES-FEM) for analyzing three-dimensional acoustic problems
Zhicheng He,Zhicheng He,Gui-Rong Liu,Gui-Rong Liu,Z.H. Zhong,Shengchuan Wu,Guiyong Zhang,A.G. Cheng +7 more
TL;DR: In this article, an edge-based smoothed finite element method (ES-FEM) is proposed for analyzing acoustic problems using linear triangular and tetrahedron elements that can be generated automatically, respectively, for complicated two-dimensional and three-dimensional domains.
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A new approach to correlate the defect population with the fatigue life of selective laser melted Ti-6Al-4V alloy
Yanan Hu,Shengchuan Wu,Shengchuan Wu,Zhengkai Wu,X.L. Zhong,Saad Ahmed,S. Karabal,Xianghui Xiao,Hui-Lan Zhang,Philip J. Withers +9 more
TL;DR: In this article, the defect-tolerant design of SLM Ti-6Al-4V alloy was evaluated in terms of the defect population using a combination of the statistics of extremes and the Murakami model.
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A machine-learning fatigue life prediction approach of additively manufactured metals
Bao Hongyixi,Shengchuan Wu,Shengchuan Wu,Zhengkai Wu,Guozheng Kang,Xin Peng,Philip J. Withers +6 more
TL;DR: In this paper, a machine learning method was adopted to explore the influence of defect location, size, and morphology on the fatigue life of a selective laser melted Ti-6Al-4V alloy.