Neural network optimization of material composition of a functionally graded material plate at arbitrary temperature range and temperature rise
type: Item
instance of: scholarly article
title: Neural network optimization of material composition of a functionally graded material plate at arbitrary temperature range and temperature rise
zbMATH Open document ID: 0947.74045
author: K. Appert
published in: Archive of Applied Mechanics
publication date: 2000-11-02T00:00:00Z
review text: The authors apply a neural network model to the optimization of material compositions for a functionally graded material plate with arbitrarily distributed and continuously varied in the thickness direction material properties. The unsteady temperature distribution is evaluated by taking into account the bounds on the number of layers. The authors obtain thermal stresses for an infinite plate under traction-free conditions. The optimal material composition is determined for temperature-dependent material properties, and the results obtained by the neural network method are compared with the results from the nonlinear programming method.
Mathematics Subject Classification ID: 74P10
Mathematics Subject Classification ID: 74K20
Mathematics Subject Classification ID: 74F05
zbMATH DE Number: 1300242
zbMATH Keywords: functionally graded material plate
zbMATH Keywords: thermal stresses
zbMATH Keywords: traction-free conditions
zbMATH Keywords: optimal material composition
zbMATH Keywords: temperature-dependent material properties
MaRDI profile type: Publication
full work available at URL: s004190050195
OpenAlex ID: W1992442369
DOI: 10.1007/S004190050195
description: scientific article; zbMATH DE number 1300242