Fundamentals of Physics-Informed Neural Networks Applied to Solve the Reynolds Boundary Value Problem

This paper presents a complete derivation and design of a physics-informed neural network (PINN) applicable to solve initial and boundary value problems described by linear ordinary differential equations. The objective with this technical note is not to develop a numerical solution procedure which...

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Bibliographic Details
Published in:	Lubricants Vol. 9; no. 8; p. 82
Main Author:	Almqvist, Andreas
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.08.2021
Subjects:	Bias Boundary value problems Differential equations Finite difference method Finite element method Fluid mechanics Machine Elements Machine learning Maskinelement Meshless methods Neural networks Ordinary differential equations Partial differential equations Physics PINN reynolds equation
ISSN:	2075-4442, 2075-4442
Online Access:	Get full text
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