Chao Liu

Prof. Dr. Chao Liu

Institute of Systems Science, Northeastern University, Shenyang, Liaoning, China
orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2016 in Applied Mathematics and Computation
Verified
Journal Article
Closed access
CLChao Liu
Chao Liu
NLNa Lu
Na Lu
QZQingling Zhang
Qingling Zhang
JLJinna Li
Jinna Li
PLPeiyong Liu
Peiyong Liu

7 June 2022 in Processes
Verified
Journal Article
Open access
PDF file
Tao LiuTao Liu
Tao Liu
KXKaiwen Xia
Kaiwen Xia
Yuanjin ZhengYuanjin Zheng
Yuanjin Zheng
YYYanxiong Yang
Yanxiong Yang
RQRuofeng Qiu
Ruofeng Qiu
CLChao Liu
Chao Liu
This paper considers the constrained inverse problem based on the nonlinear convection-diffusion equation in the multiphase porous media flow. To solve this problem, a widely convergent homotopy method is introduced and proposed. To evaluate the performance of the mentioned method, two numerical examples are presented. This method turns out to have wide convergence region and strong anti-noise ability.

26 March 2024 in Chaos, Solitons & Fractals
Verified
Journal Article
Closed access
CLChao Liu
Chao Liu
YTYilin Tian
Yilin Tian
PCPeng Chen
Peng Chen
LCLora Cheung
Lora Cheung

1 November 2019 in Communications in Nonlinear Science and Numerical Simulation
Verified
Journal Article
Closed access
CLChao Liu
Chao Liu
MLMing Liu
Ming Liu

27 June 2023 in Mathematics
Verified
Journal Article
Open access
PDF file
Tao LiuTao Liu
Tao Liu
DODi Ouyang
Di Ouyang
LGLianjun Guo
Lianjun Guo
RQRuofeng Qiu
Ruofeng Qiu
YQYunfei Qi
Yunfei Qi
CLChao Liu
Chao Liu
This paper delves into a rapid and accurate numerical solution for the inverse problem of the nonlinear diffusion equation in the context of multiphase porous media flow. For the realization of this, the combination of the multigrid method with constraint data is utilized and investigated. Additionally, to address the ill-posedness of the inverse problem, the Tikhonov regularization is incorporated. Numerical results demonstrate the computational performance of this method. The proposed combination strategy displays remarkable capabilities in reducing noise, avoiding local minima, and accelerating convergence. Moreover, this combination method performs better than any one method used alone.

1 May 2020 in Applied Mathematics Letters
Verified
Journal Article
Closed access
CLChao Liu
Chao Liu
HLHaichang Li
Haichang Li
LCLora Cheung
Lora Cheung