Global optimization for data assimilation in landslide tsunamis models
Geophysics
2024-08-23 v1 Numerical Analysis
Numerical Analysis
Abstract
The goal of this article is to make automatic data assimilation for a landslide tsunami model, given by the coupling between a non-hydrostatic multi-layer shallow-water and a Savage-Hutter granular landslide model for submarine avalanches. The coupled model is discretized using a positivity-preserving second-order path-conservative finite volume scheme. The data assimilation problem is posed in a global optimization framework and we develop and compare parallel metaheuristic stochastic global optimization algorithms, more precisely multi-path versions of the Simulated Annealing algorithm, with hybrid global optimization algorithms based on hybridizing Simulated Annealing with gradient local searchers, like L-BGFS-B.
Cite
@article{arxiv.2408.11819,
title = {Global optimization for data assimilation in landslide tsunamis models},
author = {A. M. Ferreiro-Ferreiro and J. A. García-Rodríguez and J. G. López-Salas and C. Escalante and M. J. Castro},
journal= {arXiv preprint arXiv:2408.11819},
year = {2024}
}