A Physics-Informed Surrogate Model for the Bi-Flux Bevilacqua–Galeão Anomalous Diffusion Equation

Accurate modeling of bi-flux anomalous diffusion presents significant computational challenges in engineering. This paper investigates the effectiveness of physics-informed neural networks as surrogate models for the bi-flux anomalous diffusion equation. We investigate one-dimensional linear and non...

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Principais autores:	Douglas Ferraz Corrêa, Cláudio Motta Toledo, David A. Pelta, Antônio Silva Neto
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-06-01
coleção:	Eng
Assuntos:	physics-informed neural networks bi-flux anomalous diffusion surrogate model fourth-order diffusion
Acesso em linha:	https://www.mdpi.com/2673-4117/7/6/293
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