TY - JOUR
T1 - The stability and convergence analysis of finite difference methods for the fractional neutron diffusion equation
AU - Yin, Daopeng
AU - Xie, Yingying
AU - Mei, Liquan
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2023/10
Y1 - 2023/10
N2 - For the time-fractional neutron diffusion equation with a Caputo derivative of order α∈(0,12) , we give the optimal error bounds of L1-type schemes under the spatial L∞ -norm with lower regularity solution than typical |∂tlu(x,t)|≤C(1+t2α-l),l=0,1,2 , where 2α is the highest order of the time-fractional derivative. The unique solvability and the numerical stability of schemes will be exported via a simple restriction of coefficients with non-uniform time steps τn<π4 . The truncation error of term D0,t2α with low regularity |∂tlu(x,t)|≤C(1+tα-l),l=0,1,2 , and the global error of full discretizations will be given. In addition, several numerical examples will be shown to test our theoretical results.
AB - For the time-fractional neutron diffusion equation with a Caputo derivative of order α∈(0,12) , we give the optimal error bounds of L1-type schemes under the spatial L∞ -norm with lower regularity solution than typical |∂tlu(x,t)|≤C(1+t2α-l),l=0,1,2 , where 2α is the highest order of the time-fractional derivative. The unique solvability and the numerical stability of schemes will be exported via a simple restriction of coefficients with non-uniform time steps τn<π4 . The truncation error of term D0,t2α with low regularity |∂tlu(x,t)|≤C(1+tα-l),l=0,1,2 , and the global error of full discretizations will be given. In addition, several numerical examples will be shown to test our theoretical results.
KW - Conditional stability
KW - Graded mesh
KW - L-norm error
KW - Lower regularity
UR - https://www.scopus.com/pages/publications/85171379333
U2 - 10.1007/s10444-023-10070-y
DO - 10.1007/s10444-023-10070-y
M3 - 文章
AN - SCOPUS:85171379333
SN - 1019-7168
VL - 49
JO - Advances in Computational Mathematics
JF - Advances in Computational Mathematics
IS - 5
M1 - 72
ER -