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SUMMARY:Finite Volumes for Complex Applications 8
DTSTART;VALUE=DATE-TIME:20170612T060000Z
DTEND;VALUE=DATE-TIME:20170616T160000Z
DTSTAMP;VALUE=DATE-TIME:20180921T153104Z
UID:indico-event-1299@indico.math.cnrs.fr
DESCRIPTION:Objectives of the conference\n\nThe finite volume method in it
s numerous variants is a space discretization technique for partial differ
ential equations based on the fundamental physical principle of conservati
on. It has been used successfully in many applications including fluid dyn
amics\, magnetohydrodynamics\, structural analysis\, nuclear physics\, and
semiconductor theory. Recent decades have brought significant success in
the theoretical understanding of the method. Many finite volume methods pr
eserve further qualitative or asymptotic properties including maximum prin
ciples\, dissipativity\, monotone decay of the free energy\, or asymptotic
stability. Due to these properties\, finite volume methods belong to the
wider class of compatible discretization methods\, which preserve qualitat
ive properties of continuous problems at the discrete level. This structur
al approach to the discretization of partial differential equations become
s particularly important for multiphysics and multiscale applications.\n\n
The goal of the conference is to bring together mathematicians\, physicist
s\, and engineers interested in physically motivated discretizations. Cont
ributions to the further advancement of the theoretical understanding of s
uitable finite volume\, finite element\, discontinuous Galerkin and other
discretization schemes\, and the exploration of new application fields for
them are welcome.\n\n \n\nMain Focus\n\n\n Design and analysis of num
erical methods \n Preservation of physical properties on the disc
rete level \n Convergence\, stability\, a priori and a posteriori
error analysis \n Applications at the interface with other disci
plines \n HPC\, parallel computing \n Industrial applica
tions \n Model reduction and multiscale methods \n High-
order methods \n Uncertainty quantification and stochastic proble
ms\n\n\n \n\nPartners\n\n\n \n \n \n \n
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\n \n \n \n \n\n\nhttps://indico.math.cn
rs.fr/event/1299/
LOCATION:Université Lille 1
URL:https://indico.math.cnrs.fr/event/1299/
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