In this paper, we show how to efficiently achieve thermal cloaking from a computational standpoint in several virtual scenarios by controlling a distribution of active heat sources. We frame this problem in the setting of PDE-constrained optimization, where the reference field is the solution of the time-dependent heat equation in the absence of the object to cloak. The optimal control problem then aims at actuating the space–time control field so that the thermal field outside the obstacle is indistinguishable from the reference field. In particular, we consider multiple scenarios where material’s thermal diffusivity, source intensity and obstacle’s temperature are allowed to vary within a user-defined range. To tackle the thermal cloaking problem in a rapid and reliable way, we rely on a parametrized reduced order model built through the reduced basismethod, thus entailing huge computational speedups compared with a highfidelity, full-order model exploiting the finite-element method while dealing both with complex target shapes and disconnected control domains.

Fast active thermal cloaking through PDE-constrained optimization and reduced-order modelling

Sinigaglia, Carlo;Quadrelli, Davide E.;Manzoni, Andrea;Braghin, Francesco
2022-01-01

Abstract

In this paper, we show how to efficiently achieve thermal cloaking from a computational standpoint in several virtual scenarios by controlling a distribution of active heat sources. We frame this problem in the setting of PDE-constrained optimization, where the reference field is the solution of the time-dependent heat equation in the absence of the object to cloak. The optimal control problem then aims at actuating the space–time control field so that the thermal field outside the obstacle is indistinguishable from the reference field. In particular, we consider multiple scenarios where material’s thermal diffusivity, source intensity and obstacle’s temperature are allowed to vary within a user-defined range. To tackle the thermal cloaking problem in a rapid and reliable way, we rely on a parametrized reduced order model built through the reduced basismethod, thus entailing huge computational speedups compared with a highfidelity, full-order model exploiting the finite-element method while dealing both with complex target shapes and disconnected control domains.
2022
active cloaking, PDE-constrained optimization, reduced order modelling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1203143
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