Ensemble of physics-informed neural networks for solving plane elasticity problems with examples

Two-dimensional (plane) elasticity equations in solid mechanics are solved numerically with the use of an ensemble of physics-informed neural networks (PINNs). The system of equations consists of the kinematic definitions, i.e. the strain–displacement relations, the equilibrium equations connecting...

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Bibliographic Details
Published in:	Acta mechanica Vol. 235; no. 11; pp. 6703 - 6722
Main Authors:	Mouratidou, Aliki D., Drosopoulos, Georgios A., Stavroulakis, Georgios E.
Format:	Journal Article
Language:	English
Published:	Vienna Springer Vienna 01.11.2024 Springer Springer Nature B.V
Subjects:	Analysis Application programming interface Applications programming Artificial intelligence Boundary conditions Classical and Continuum Physics Commercial aircraft Computer programs Constitutive equations Constitutive relationships Control Deep learning Dynamical Systems Elasticity Engineering Engineering Fluid Dynamics Engineering Thermodynamics Equilibrium equations Exact solutions Finite element method Heat and Mass Transfer Kinematics Machine learning Material properties Mathematical analysis Mathematical models Neural networks Original Paper Physics Plane stress Python Science Software Solid Mechanics Strain Tensors Theoretical and Applied Mechanics Vibration
ISSN:	0001-5970, 1619-6937
Online Access:	Get full text
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