The effectiveness of a Metamodel-Embedded Evolution Framework for model parameter identification of a Smoothed Particles Hydrodynamic (SPH) solver, called DualSPHysics, is demonstrated when applied to the generation and propagation of progressive ocean waves. DualSPHysics is an open-source code that provides GP-GPU acceleration, allowing for highly refined simulations. The automatic optimization framework combines the global-convergence capabilities of a Multi-Objective Genetic Algorithm (MOGA) with Response Surface Method (RSM) based on a Kriging approximation. The proposed Metamodel-Embedded Evolutionary framework is used to find the set of SPH model parameters that ensures an accurate reproduction of a 2nd order Stokes wave propagating in a numeric flume tank. In order to demonstrate the consistency of the obtained results, the optimum set of parameters found by the framework is finally used to reproduce other 2nd and 3rd order Stokes waves propagating over the same flume tank.

Ensuring numerical stability of wave propagation by tuning model parameters using genetic algorithms and response surface methods / Angelini Rota Roselli, Riccardo; Vernengo, Giuliano; Altomare, Corrado; Brizzolara, Stefano; Bonfiglio, Luca; Guercio, Roberto. - In: ENVIRONMENTAL MODELLING & SOFTWARE. - ISSN 1364-8152. - 103:(2018), pp. 62-73. [10.1016/j.envsoft.2018.02.003]

Ensuring numerical stability of wave propagation by tuning model parameters using genetic algorithms and response surface methods

Angelini Rota Roselli , Riccardo;Guercio, Roberto
2018

Abstract

The effectiveness of a Metamodel-Embedded Evolution Framework for model parameter identification of a Smoothed Particles Hydrodynamic (SPH) solver, called DualSPHysics, is demonstrated when applied to the generation and propagation of progressive ocean waves. DualSPHysics is an open-source code that provides GP-GPU acceleration, allowing for highly refined simulations. The automatic optimization framework combines the global-convergence capabilities of a Multi-Objective Genetic Algorithm (MOGA) with Response Surface Method (RSM) based on a Kriging approximation. The proposed Metamodel-Embedded Evolutionary framework is used to find the set of SPH model parameters that ensures an accurate reproduction of a 2nd order Stokes wave propagating in a numeric flume tank. In order to demonstrate the consistency of the obtained results, the optimum set of parameters found by the framework is finally used to reproduce other 2nd and 3rd order Stokes waves propagating over the same flume tank.
2018
Non-dominated sorting genetic algorithm (NSGA-II); parameter identification.; response surface method (RSM); smoothed particle hydrodynamics (SPH); wave propagation; software; environmental engineering; ecological modeling
01 Pubblicazione su rivista::01a Articolo in rivista
Ensuring numerical stability of wave propagation by tuning model parameters using genetic algorithms and response surface methods / Angelini Rota Roselli, Riccardo; Vernengo, Giuliano; Altomare, Corrado; Brizzolara, Stefano; Bonfiglio, Luca; Guercio, Roberto. - In: ENVIRONMENTAL MODELLING & SOFTWARE. - ISSN 1364-8152. - 103:(2018), pp. 62-73. [10.1016/j.envsoft.2018.02.003]
File allegati a questo prodotto
File Dimensione Formato  
Angelini_pre-print_Ensuring-numerical_2018.pdf

accesso aperto

Tipologia: Documento in Pre-print (manoscritto inviato all'editore, precedente alla peer review)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.6 MB
Formato Adobe PDF
1.6 MB Adobe PDF
Angelini_Ensuring-numerical_2018.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.41 MB
Formato Adobe PDF
1.41 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1254505
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 47
  • ???jsp.display-item.citation.isi??? 37
social impact