UID:
almahu_9949519841402882
Umfang:
X, 234 p. 86 illus., 80 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2023.
ISBN:
9783031298752
Serie:
SEMA SIMAI Springer Series, 32
Inhalt:
A broad range of phenomena in science and technology can be described by non-linear partial differential equations characterized by systems of conservation laws with source terms. Well known examples are hyperbolic systems with source terms, kinetic equations, and convection-reaction-diffusion equations. This book collects research advances in numerical methods for hyperbolic balance laws and kinetic equations together with related modelling aspects. All the contributions are based on the talks of the speakers of the Young Researchers' Conference "Numerical Aspects of Hyperbolic Balance Laws and Related Problems", hosted at the University of Verona, Italy, in December 2021.
Anmerkung:
Chapter 1. Alessandro Alla, Peter M. Dower, Vincent Liu. A Tree Structure Approach to Reachability Analysis -- Chapter 2. Giulia Bertaglia. Asymptotic-preserving neural networks for hyperbolic systems with diffusive scaling -- Chapter 3. Felisia Angela Chiarello, Paola Goatin. A non-local system modeling bi-directional traffic flows -- Chapter 4. Armando Coco, Santina Chiara Stissi. Semi-implicit finite-difference methods for compressible gas dynamics with curved boundaries: a ghost-point approach -- Chapter 5. Elena Gaburro, Simone Chiocchetti. High-order arbitrary-Lagrangian-Eulerian schemes on crazy moving Voronoi meshes -- Chapter 6. Elisa Iacomini. Overview on uncertainty quantification in traffic models via intrusive method -- Chapter 7. Liu Liu. A study of multiscale kinetic models with uncertainties -- Chapter 8. Fiammetta Conforto, Giorgio Martalò. On the shock wave discontinuities in Grad hierarchy for a binary mixture of inert gases -- Chapter 9. Giuseppe Visconti, Silvia Tozza, Matteo Semplice, Gabriella Puppo. A conservative a[1]posteriori time-limiting procedure in Quinpi schemes -- Chapter 10. Yuhua Zhu. Applications of Fokker Planck equations in machine learning algorithms.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031298745
Weitere Ausg.:
Printed edition: ISBN 9783031298769
Weitere Ausg.:
Printed edition: ISBN 9783031298776
Sprache:
Englisch
DOI:
10.1007/978-3-031-29875-2
URL:
https://doi.org/10.1007/978-3-031-29875-2
