Yanli Lin
Harbin Institute of Technology
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Featured researches published by Yanli Lin.
Journal of Testing and Evaluation | 2017
Yanli Lin; Guannan Chu; Zhubin He; S.J. Yuan; Yongda Yan
Extruded aluminum alloy tubes present strong anisotropic properties, making its deformation very sensitive to stress states. To better characterize a proper constitutive relationship, the use of experimental stress-strain response with biaxial stress states would be more suitable than that of a common uniaxial test. To achieve this purpose, an attractive testing method and homologous experimental system (i.e., hydro-bulging system) were developed. Different proportional and non-proportional loading conditions could be performed with this experimental system. Hydro-bulging tests under three typical proportional loading paths were done. A fourth-order hardening model proposed by the authors was used to reproduce these experimental stress-strain relations and compared them with the results predicted using a power law relationship. Regression results predicted by the fourth-order hardening model had a good consistency with the distribution of experimental data. Deviations of the fourth-order hardening model are much less than that obtained by a power law. The maximum deviation introduced by the power function is at least 2.6 times greater than that introduced by the fourth-order function. Therefore, the use of a new regression model to treat experimental data would improve the predicting accuracy of a related constitutive relation efficiently and further ensure the predicting accuracy regarding a hydroforming simulation.
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science | 2018
Yanli Lin; Guannan Chu; Caiyuan Lin; Yongda Yan
Due to the strong anisotropic property of the advanced metal materials used in automobile, aviation, and aerospace, experimental flow stress–strain relations including different stress states are necessary to provide the information of anisotropic hardening and plastic flow for constructing a constitutive model. Therefore, reasonably reproducing the experimental stress–strain relations is the most fundamental work to substitute adequate flow stress–strain curves into the constitutive equation at the same time. However, accurate and stable regression results are difficult to obtain through the current regression models such as power exponent, second-order function model, fourth-order function model, and so forth. In this paper, an optimized model named as a least square quadratic regression model (ordinary least square model) was proposed based on the most useful second-order function model. The significant difference is that all experimental points are used to reproduce the experimental stress–strain relations in ordinary least square model in place of only three experimental points adopted in second-order function model, which results in good regression accuracy. Through comparison, it is found that the regression results by power function are poor with regard to some experimental results, and the results reproduced by second-order function model or fourth-order function model are very sensitive to the experimental points selected to do the regression. The sum of squares for error (SSE) increases sharply when the selected points are unreasonable. In addition, for second-order function and fourth-order function models, only limited experimental points are adopted to do the regression, the best regression accuracy cannot be obtained even if the selected points are reasonable. In contrast, SSE of the regression curve by ordinary least square model reduces to less than 50% of the best regressed result by second-order function model, the yielding behavior and variable strain increment ratio of the anisotropic materials can be reflected more accurately. This is very important for accurately describing the plastic flow behaviors of anisotropic materials.
International Journal of Mechanical Sciences | 2015
Weilong Hu; Yanli Lin; Shijian Yuan; Zhubin He
International Journal of Mechanical Sciences | 2014
Zhubin He; Shijian Yuan; Yanli Lin; Xiaosong Wang; Weilong Hu
International Journal of Mechanical Sciences | 2014
Zhubin He; Shijian Yuan; Yanli Lin; Xiaosong Wang; Weilong Hu
Journal of Materials Processing Technology | 2017
Z.B. Wang; Zhubin He; Xiaobo Fan; L. Zhou; Yanli Lin; S.J. Yuan
Archive | 2009
Shijian Yuan; Zhubin He; Yi Sun; Yanli Lin
Journal of Materials Engineering and Performance | 2017
Guannan Chu; Lei Sun; Caiyuan Lin; Yanli Lin
Journal of Materials Engineering and Performance | 2011
Zhubin He; Yanli Lin; Jia Wu; Shijian Yuan
Journal of Testing and Evaluation | 2019
Shijian Yuan; Wencai Xie; Yanli Lin; Zhubin He