Predicting surface deformation during mechanical attrition of metallic alloys

doi:10.1038/s41524-019-0171-6

CORC > 上海应用物理研究所 > 中国科学院上海应用物理研究所 > 中科院上海应用物理研究所2011-2017年

	Predicting surface deformation during mechanical attrition of metallic alloys
	Cao, SC ; Zhang, XC ; Lu, J ; Wang, YL ; Shi, SQ ; Ritchie, RO
刊名	NPJ COMPUTATIONAL MATERIALS
	2019
卷号	5 期号:-页码:—
关键词	STRENGTH NANOCRYSTALLIZATION LAYER SIMULATION ROUGHNESS TITANIUM
ISSN号	2057-3960
DOI	10.1038/s41524-019-0171-6
文献子类	期刊论文
英文摘要	Extensive efforts have been devoted in both the engineering and scientific domains to seek new designs and processing techniques capable of making stronger and tougher materials. One such method for enhancing such damage-tolerance in metallic alloys is a surface nano-crystallization technology that involves the use of hundreds of small hard balls which are vibrated using high-power ultrasound so that they impact onto the surface of a material at high speed (termed Surface Mechanical Attrition Treatment or SMAT). However, few studies have been devoted to the precise underlying mechanical mechanisms associated with this technology and the effect of processing parameters. As SMAT is dynamic plastic deformation process, here we use random impact deformation as a means to investigate the relationship between impact deformation and the parameters involved in the processing, specifically ball size, impact velocity, ball density and kinetic energy. Using analytical and numerical solutions, we examine the size of the indents and the depths of the associated plastic zones induced by random impacts, with results verified by experiment in austenitic stainless steels. In addition, global random impact and local impact frequency models are developed to analyze the statistical characteristics of random impact coverage, together with a description of the effect of random multiple impacts, which are more reflective of SMAT. We believe that these models will serve as a necessary foundation for further, and more energy-efficient, development of such surface nano-crystalline processing technologies for the strengthening of metallic materials.
语种	英语
内容类型	期刊论文
源URL	[http://ir.sinap.ac.cn/handle/331007/31765]
专题	上海应用物理研究所_中科院上海应用物理研究所2011-2017年
作者单位	1.Univ Calif Berkeley, Dept Mat Sci & Engn, Berkeley, CA 94720 USA; 2.Chinese Acad Sci, Shanghai Inst Appl Phys, Shanghai 201800, Peoples R China; 3.City Univ Hong Kong, Dept Mech Engn, Hong Kong, Peoples R China; 4.Hong Kong Polytech Univ, Dept Mech Engn, Hung Hom, Hong Kong, Peoples R China; 5.Lawrence Berkeley Natl Lab, Mat Sci Div, Berkeley, CA 94720 USA
推荐引用方式 GB/T 7714	Cao, SC,Zhang, XC,Lu, J,et al. Predicting surface deformation during mechanical attrition of metallic alloys[J]. NPJ COMPUTATIONAL MATERIALS,2019,5(-):—.
APA	Cao, SC,Zhang, XC,Lu, J,Wang, YL,Shi, SQ,&Ritchie, RO.(2019).Predicting surface deformation during mechanical attrition of metallic alloys.NPJ COMPUTATIONAL MATERIALS,5(-),—.
MLA	Cao, SC,et al."Predicting surface deformation during mechanical attrition of metallic alloys".NPJ COMPUTATIONAL MATERIALS 5.-(2019):—.