A Lagrangian–Eulerian procedure for the coupled solution of the Navier–Stokes and shallow water equations for landslide-generated waves
This work presents a partitioned method for landslide-generated wave events. The proposed strategy combines a Lagrangian Navier Stokes multi-fluid solver with an Eulerian method based on the Boussinesq shallow water equations. The Lagrangian solver uses the Particle Finite Element Method to model th...
Saved in:
Published in | Advanced modeling and simulation in engineering sciences Vol. 9; no. 1; pp. 1 - 22 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Cham
Springer International Publishing
30.07.2022
Springer Nature B.V Springer SpringerOpen |
Series | Recent Advances in hypercomplex disaster simulations |
Subjects | |
Online Access | Get full text |
ISSN | 2213-7467 2213-7467 |
DOI | 10.1186/s40323-022-00225-9 |
Cover
Summary: | This work presents a partitioned method for landslide-generated wave events. The proposed strategy combines a Lagrangian Navier Stokes multi-fluid solver with an Eulerian method based on the Boussinesq shallow water equations. The Lagrangian solver uses the Particle Finite Element Method to model the landslide runout, its impact against the water body and the consequent wave generation. The results of this fully-resolved analysis are stored at selected interfaces and then used as input for the shallow water solver to model the far-field wave propagation. This one-way coupling scheme reduces drastically the computational cost of the analyses while maintaining high accuracy in reproducing the key phenomena of the cascading natural hazard. Several numerical examples are presented to show the accuracy and robustness of the proposed coupling strategy and its applicability to large-scale landslide-generated wave events. The validation of the partitioned method is performed versus available results of other numerical methods, analytical solutions and experimental measures. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 2213-7467 2213-7467 |
DOI: | 10.1186/s40323-022-00225-9 |