Global optimization for data assimilation in landslide tsunami models

JOURNAL OF COMPUTATIONAL PHYSICS

卷:403

Article

Ferreiro-Ferreiro, A. M.^1,2  Garcia-Rodriguez, J. A.^1,2  Lopez-Salas, J. G.^1,2  Escalante, C.³  Castro, M. J.³ 

[1] Fac Informat, Dept Math, Campus Elvina S-N, La Coruna 15071, Spain

[2] Univ A Coruna, CITIC Res Ctr Informat & Commun Technol, La Coruna, Spain

[3] Univ Malaga, Dept Anal Matemat, Malaga, Spain

关键词: Tsunamis;    Submarine avalanches;    Finite volume methods;    Data assimilation;    Global optimization;    Parallel computing;   

DOI  :  10.1016/j.jcp.2019.109069

来源: Elsevier

【 摘 要 】

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. Then, the data assimilation problem is posed in a global optimization framework. Later, multi-path parallel metaheuristic stochastic global optimization algorithms are developed. More precisely, a multi-path Simulated Annealing algorithm is compared with a multi-path hybrid global optimization algorithm based on coupling Simulated Annealing with gradient local searchers. (C) 2019 Elsevier Inc. All rights reserved.

【 授权许可】

Free