Finite Volume Scheme for Multiple Fragmentation Equations
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@Article{IJNAMB-3-270,
author = {RAJESH KUMAR∗ AND JITENDRA KUMAR},
title = {Finite Volume Scheme for Multiple Fragmentation Equations},
journal = {International Journal of Numerical Analysis Modeling Series B},
year = {2012},
volume = {3},
number = {3},
pages = {270--284},
abstract = {In this paper we study a finite volume approximation for the conservative formulation of multiple fragmentation models. We investigate the convergence of the numerical solutions
towards a weak solution of the continuous problem by considering locally bounded kernels. The
proof is based on the Dunford-Pettis theorem by using the weak L^1 compactness method. The
analysis of the method allows us to prove the convergence of the discretized approximated solution
towards a weak solution to the continuous problem in a weighted L^1 space.},
issn = {},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/ijnamb/283.html}
}
TY - JOUR
T1 - Finite Volume Scheme for Multiple Fragmentation Equations
AU - RAJESH KUMAR∗ AND JITENDRA KUMAR
JO - International Journal of Numerical Analysis Modeling Series B
VL - 3
SP - 270
EP - 284
PY - 2012
DA - 2012/03
SN - 3
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/ijnamb/283.html
KW - Finite volume
KW - Fragmentation
KW - Convergence
KW - Particle
AB - In this paper we study a finite volume approximation for the conservative formulation of multiple fragmentation models. We investigate the convergence of the numerical solutions
towards a weak solution of the continuous problem by considering locally bounded kernels. The
proof is based on the Dunford-Pettis theorem by using the weak L^1 compactness method. The
analysis of the method allows us to prove the convergence of the discretized approximated solution
towards a weak solution to the continuous problem in a weighted L^1 space.
RAJESH KUMAR∗ AND JITENDRA KUMAR. (2012). Finite Volume Scheme for Multiple Fragmentation Equations.
International Journal of Numerical Analysis Modeling Series B. 3 (3).
270-284.
doi:
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