TY - JOUR
T1 - Partially explicit time discretization for nonlinear time fractional diffusion equations
AU - Li, Wenyuan
AU - Alikhanov, Anatoly
AU - Efendiev, Yalchin
AU - Leung, Wing Tat
PY - 2022/10
Y1 - 2022/10
N2 - Nonlinear time fractional partial differential equations are widely used in modeling and simulations. In many applications, there are high contrast changes in media properties. For solving these problems, one often uses a coarse spatial grid for spatial resolution. For temporal discretization, implicit methods are often used. For implicit methods, though the time step can be relatively large, the equations are difficult to compute due to the nonlinearity and the fact that one deals with large-scale systems. On the other hand, the discrete systems in explicit methods are easier to compute but it requires small time steps. In this work, we propose a partially explicit scheme following earlier works on developing partially explicit methods for nonlinear diffusion equations. In these schemes, the diffusion term is treated partially explicitly and the reaction term is treated fully explicitly. With the appropriate construction of spaces and stability analysis, we find that the required time step in our proposed scheme scales as the coarse mesh size, which creates a computational saving. The main novelty of this work is the extension of our earlier works for diffusion equations to time fractional diffusion equations. For the case of fractional diffusion equations, the constraints on time steps are more severe and the proposed methods alleviate this problem since the time step in the partially explicit method scales as the coarse mesh size. We present stability analysis. Numerical results are presented where we compare our proposed partially explicit methods with a fully implicit approach. We show that our proposed approach provides similar results while treating many degrees of freedom in nonlinear terms explicitly.
AB - Nonlinear time fractional partial differential equations are widely used in modeling and simulations. In many applications, there are high contrast changes in media properties. For solving these problems, one often uses a coarse spatial grid for spatial resolution. For temporal discretization, implicit methods are often used. For implicit methods, though the time step can be relatively large, the equations are difficult to compute due to the nonlinearity and the fact that one deals with large-scale systems. On the other hand, the discrete systems in explicit methods are easier to compute but it requires small time steps. In this work, we propose a partially explicit scheme following earlier works on developing partially explicit methods for nonlinear diffusion equations. In these schemes, the diffusion term is treated partially explicitly and the reaction term is treated fully explicitly. With the appropriate construction of spaces and stability analysis, we find that the required time step in our proposed scheme scales as the coarse mesh size, which creates a computational saving. The main novelty of this work is the extension of our earlier works for diffusion equations to time fractional diffusion equations. For the case of fractional diffusion equations, the constraints on time steps are more severe and the proposed methods alleviate this problem since the time step in the partially explicit method scales as the coarse mesh size. We present stability analysis. Numerical results are presented where we compare our proposed partially explicit methods with a fully implicit approach. We show that our proposed approach provides similar results while treating many degrees of freedom in nonlinear terms explicitly.
KW - Fractional differential equations
KW - Multiscale
KW - Nonlinear
KW - Splitting methods
UR - http://www.scopus.com/inward/record.url?scp=85131459772&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85131459772&origin=recordpage
U2 - 10.1016/j.cnsns.2022.106440
DO - 10.1016/j.cnsns.2022.106440
M3 - RGC 21 - Publication in refereed journal
SN - 1007-5704
VL - 113
JO - Communications in Nonlinear Science and Numerical Simulation
JF - Communications in Nonlinear Science and Numerical Simulation
M1 - 106440
ER -