Yandong Wang
University of Science and Technology Beijing
315 Papers
1K Citations
Yandong Wang is an academic researcher from University of Science and Technology Beijing. The author has contributed to research in topics: Deformation (engineering) & Martensite. The author has an hindex of 38, co-authored 266 publications. Previous affiliations of Yandong Wang include China University of Mining and Technology & University of Tennessee.
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Papers
Analysis of Texture Formation and Microstructure Characteristics of Cold Rolled IF Steel Sheets
TL;DR: In this article, the relationship between the deformation microstructure and texture in cold-rolled interstitial free (IF) steel sheets was investigated, and the results were explained by the analysis of crystallographic gliding and are helpful to improve the prediction of cold rolling textures.
Deformation Induced Phase Seperation of Ni45Co5 Mn36.7In13.3 Alloy at High Temperature
TL;DR: In this article, the influence of hot deformation on the microstructure of Ni45Co5Mn36.7In13.3 alloy was studied and the experimental results showed that second phase was observed after deformation at high temperature between 800~900 °C and at strain rate lower than 4×10-3s-1.
A Nondestructive Study Using Lattice Plane Specific Analysis on a Nano-Precipitate Strengthened Alloy
E. Wen Huang,Yandong Wang,Bjørn Clausen,Michael L. Benson,Hahn Choo,Peter K. Liaw,Lee M. Pike +6 more
TL;DR: The HASTELLOY C-22HS alloy is a corrosion-resistant nickel-based alloy in a faced-center-cubic (FCC) crystal structure and the peak width of the hkl plane from both the nano-precipitates and the matrix were determined as a function of the applied stress.
A study of CuZr-based bulk metallic glass composite dispersed by in-situ Ta particles
Dongmei Wang,Juan Mu,Qingge Xie,Haijian Xu,Yandong Wang,Haifeng Zhang +5 more
- 17 May 2017
TL;DR: In this paper, the microstructure and mechanical behavior of a BMGC containing Ta-rich particles and B2 phase were investigated and the parabolic strain-hardening behavior was observed due to the martensitic transformation of B2 phases.
Multiple Kernel Clustering with Direct Consensus Graph Learning
Yandong Wang,Zhenwen Ren +1 more
TL;DR: Zhang et al. as discussed by the authors proposed to directly learn a consensus affinity graph rather than a consensus kernel from multiple base kernels, which can preserve the important graph information for graph-based clustering.