Szczegóły publikacji
Opis bibliograficzny
Physics Informed Neural Network code for 2D transient problems (PINN-2DT) compatible with Google Colab / Paweł MACZUGA, Maciej SIKORA, Tomasz SŁUŻALEC, Marcin Szubert, Łukasz SZTANGRET, Danuta SZELIGA, Marcin ŁOŚ, Witold DZWINEL, Keshav Pingali, Maciej PASZYŃSKI // W: Computational Science – ICCS 2025 : 25th international conference : Singapore, Singapore, July 7–9, 2025 : proceedings , Pt. 2 / eds. Michael H. Lees [et al.]. — Cham : Springer Nature Switzerland, cop. 2025. — ( Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 15904 ). — ISBN: 978-3-031-97628-5; e-ISBN: 978-3-031-97629-2. — S. 177–191. — Bibliogr., Abstr. — Publikacja dostępna online od: 2025-07-05
Autorzy (10)
Dane bibliometryczne
| ID BaDAP | 161038 |
|---|---|
| Data dodania do BaDAP | 2025-07-10 |
| DOI | 10.1007/978-3-031-97629-2_13 |
| Rok publikacji | 2025 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Computational Science 2025 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
We present an open-source Physics Informed Neural Network environment for simulations of transient phenomena on two-dimensional rectangular domains, with the following features: (1) it is compatible with Google Colab which allows automatic execution on cloud environment; (2) it supports 2D linear or non-linear time-dependent PDEs; (3) it provides simple interface for definition of the residual loss, boundary condition and initial loss, together with their weights; (4) it support Neumann and Dirichlet boundary conditions; (5) it allows for customizing the number of layers and neurons per layer, as well as for arbitrary activation function; (6) the learning rate and number of epochs are available as parameters; (7) it automatically differentiates PINN with respect to spatial and temporal variables; (8) it provides routines for plotting the convergence (with running average), initial conditions learnt, 2D and 3D snapshots from the simulation and movies (9) it includes a library of problems: (a) non-stationary heat transfer; (b) atmospheric simulations including thermal inversion; (c) tumor growth simulations; and (d) the Stokes problem.
