Javascript must be enabled for the correct page display

Design and optimization of an artificial neural network for constitutive modelling to determine stress under hot work

Lindemann, Adrian (2019) Design and optimization of an artificial neural network for constitutive modelling to determine stress under hot work. Integration Project, Industrial Engineering and Management.

[img]
Preview
Text
Bachelor_Industrial engineering and Management_ 2019_Adrian Lindemann.pdf

Download (3MB) | Preview
[img] Text
toestemming.pdf
Restricted to Registered users only

Download (129kB)

Abstract

This thesis is aimed to provide a clear guide to modelling flow stress during hot work using artificial neural networks (ANNs). This is done, by briefly summarizing which constitutive models exist to approximate these material properties, in order to determine when it is useful to use an ANN for constitutive modelling. Then, the process of training and optimizing several ANNs is explained. These ANNs are designed in varying levels of complexity ranging from single input ANNs to those using strain, strain rate and temperature as inputs. The thesis concludes by providing an optimal ANN structure for each of the individual scenarios, and by reflecting upon the main challenges faced throughout the project.

Item Type: Thesis (Integration Project)
Supervisor name: Vakis, A.
Degree programme: Industrial Engineering and Management
Thesis type: Integration Project
Language: English
Date Deposited: 08 Feb 2019
Last Modified: 04 Mar 2019 12:02
URI: https://fse.studenttheses.ub.rug.nl/id/eprint/19134

Actions (login required)

View Item View Item