姓 名：杨云波
职 称：副教授
人才称号：云南省兴滇英才—青年人才
工作单位：云南师范大学数学学院
电子邮箱：ybyang13@126.com
研究方向及招生情况
l 研究领域：偏微分方程数值解；有限元方法及其应用；复杂耦合流体方程的新型高效数值方法；并行算法等
l 招生专业：计算（应用）数学
工作经历
n 2023.12—至今，云南师范大学，副教授
n 2018.04—2023.12，云南师范大学，讲师
教育经历
u 2013.09-2018.03，西安交通大学，数学博士
u 2010.09-2013.07，云南师范大学，应用数学硕士
u 2006.09-2010.07，云南师范大学，数学与应用数学学士
科研项目
v 2022.01-2025.12，国家自然科学基金地区项目12161095, 主持, 在研, 35万；
v 2022.06-2025.05，云南省科技厅基础研究专项--面上项目202101AT070106，主持，在研，10万；
v 2020.06-2023.05云南省科技厅基础研究专项--青年项目202001AU070068 ，主持，在研，5万；
v 2019.06-2020.05云南省教育厅基金2019J0076，主持，已结题，2万；
v 2019.01-2020.12云南师范大学博士科研启动经费2019BSQI01，主持，已结题，5万；
v 2019.01-2022.12国家自然科学基金面上项目11871393, 参与，已结题；
v 2022.01-2025.12国家自然科学基金地区项目12162032，参与，在研；
著作论文
1. Yang, Yun-Bo; Jiang, Yao-Lin Numerical analysis and computation of a type of IMEX method for the time-dependent natural convection problem. Comput. Methods Appl. Math. 16 (2016), no. 2, 321–344.
2.Kong, Qiong-Xiang; Yang, Yun-Bo A new two grid variational multiscale method for steady-state natural convection problem. Math. Methods Appl. Sci. 39 (2016), no. 14, 4007–4024.
3. Yang, Yun-Bo; Kong, Qiong-Xiang A new error correction method for the stationary Navier-Stokes equations based on two local Gauss integrations. Appl. Math. 62 (2017), no. 1, 75–100.
4. Yang, Yun-Bo; Jiang, Yao-Lin Analysis two decoupled time-stepping finite-element methods for incompressible fluids with microstructure. Int. J. Comput. Math. 95 (2018), no. 4, 686–709.
5. Jiang, Yao-Lin; Yang, Yun-Bo Semi-discrete Galerkin finite element method for the diffusive Peterlin viscoelastic model. Comput. Methods Appl. Math. 18 (2018), no. 2, 275–296.
6. Jiang, Yao-Lin; Yang, Yun-Bo Analysis of some projection methods for the incompressible fluids with microstructure. J. Korean Math. Soc. 55 (2018), no. 2, 471–506.
7. Yang, Yun-Bo; Jiang, Yao-Lin An explicitly uncoupled VMS stabilization finite element method for the time-dependent Darcy-Brinkman equations in double-diffusive convection. Numer. Algorithms 78 (2018), no. 2, 569–597.
8. Yang, Yun-Bo; Jiang, Yao-Lin; Kong, Qiong-Xiang The Arrow-Hurwicz iterative finite element method for the stationary magnetohydrodynamics flow. Appl. Math. Comput. 356 (2019), 347–361.
9. Miao, Zhen; Jiang, Yao-Lin; Yang, Yun-Bo Convergence analysis of a parareal-in-time algorithm for the incompressible non-isothermal flows. Int. J. Comput. Math. 96 (2019), no. 7, 1398–1415.
10. Yang, Yun-Bo; Jiang, Yao-Lin; Kong, Qiong-Xiang A higher order pressure segregation scheme for the time-dependent magnetohydrodynamics equations. Appl. Math. 64 (2019), no. 5, 531–556.
11. Yang, Yun-Bo; Jiang, Yao-Lin Error correction iterative method for the stationary incompressible MHD flow. Math. Methods Appl. Sci. 43 (2020), no. 2, 750–768.
12. Yang, Yunbo; Jiang, Yaolin; Kong, Qiongxiang Two-grid stabilized FEMs based on Newton type linearization for the steady-state natural convection problem. Adv. Appl. Math. Mech. 12 (2020), no. 2, 407–435.
13. Yang, Yun-Bo; Jiang, Yao-Lin Unconditional optimal error estimates of linearized second-order BDF Galerkin FEMs for the Landau-Lifshitz equation. Appl. Numer. Math. 159 (2021), 21–45.
14. Yang, Yun-Bo; Jiang, Yao-Lin Unconditional optimal error estimates of linearized backward Euler Galerkin FEMs for nonlinear Schrödinger-Helmholtz equations. Numer. Algorithms 86 (2021), no. 4, 1495–1522.
15. Yang, Yun-Bo; Jiang, Yao-Lin; Yu, Bo-Hao Unconditional optimal error estimates of linearized, decoupled and conservative Galerkin FEMs for the Klein-Gordon-Schrödinger equation. J. Sci. Comput. 87 (2021), no. 3, Paper No. 89, 32 pp.
16. Yang, Yun-Bo; Jiang, Yao-Lin Optimal error estimates of a lowest-order Galerkin-mixed FEM for the thermoviscoelastic Joule heating equations. Appl. Numer. Math. 183 (2023), 86–107.
17. Yang, Yun-Bo; Huang, Bin-Chao; Jiang, Yao-Lin Error estimates of an operator-splitting finite element method for the time-dependent natural convection problem. Numer. Methods Partial Differential Equations 39 (2023), no. 3, 2202–2226.
18. Yang, Yun-Bo Error estimates of a two-grid penalty finite element method for the Smagorinsky model, Math. Meth. Appl. Sci. (2023), 1-23, DOI 10.1002/mma.9574.
