The optimal handling of level sets associated to the solution of Hamilton-Jacobi equations such as the normal flow equation is investigated. The goal is to find the normal velocity minimizing a suitable cost functional that accounts for a desired behavior of level sets over time. Sufficient conditions of optimality are derived that require the solution of a system of nonlinear Hamilton-Jacobi equations. Since finding analytic solutions is difficult in general, the use of numerical methods to obtain approximate solutions is addressed by dealing with some case studies in two and three dimensions.

Optimal propagating fronts using Hamilton-Jacobi equations

M Gaggero
2019

Abstract

The optimal handling of level sets associated to the solution of Hamilton-Jacobi equations such as the normal flow equation is investigated. The goal is to find the normal velocity minimizing a suitable cost functional that accounts for a desired behavior of level sets over time. Sufficient conditions of optimality are derived that require the solution of a system of nonlinear Hamilton-Jacobi equations. Since finding analytic solutions is difficult in general, the use of numerical methods to obtain approximate solutions is addressed by dealing with some case studies in two and three dimensions.
2019
Istituto di iNgegneria del Mare - INM (ex INSEAN)
Inglese
7
11
1
10
10
Sì, ma tipo non specificato
Hamliton-Jacobi equation
normal flow equation
level set methods
optimization
art. no. 1122 OPEN ACCESS - This is an open access article distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited - https://creativecommons.org/licenses/by/4.0/
4
info:eu-repo/semantics/article
262
Alessandri, A; Bagnerini, P; Cianci, R; Gaggero, M
01 Contributo su Rivista::01.01 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/371448
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