Cracow University of Technology, Faculty of Electrical and Computer Engineering, Cracow, Poland
Submission date: 2019-11-04
Acceptance date: 2020-01-16
Online publication date: 2020-04-15
Publication date: 2020-04-15
Corresponding author
Marek Dudzik
Faculty of Electrical and Computer Engineering, Department of Traction and Traffic Control, Cracow University of Technology, Warszawska 24, 31-155, Kraków, Poland
Journal of Theoretical and Applied Mechanics 2020;58(2):385-390
In this article, we present a proposition of a model of the compressive behaviour of open-
-cell aluminium with relation to the material apparent density. The research was based on
experimental data from uniaxial compression tests conducted for two sample lots. These
results were analysed with the use of neural networks in a specially designed algorithm.
The main criterion for choosing a satisfactory approximation was mean absolute relative
error MARE<5%. As a result of the analysis, the sought relation was extracted and is
presented as a proposition of a new ANN model of the compressive stress-strain relationship
for aluminium sponge.
REFERENCES(13)
1.
Demuth H., Beale M., Hagan M., 2009, Neural Network Toolbox 6 User’s Guide, MathWorks Inc.
Dudzik M., Stręk A.M., 2020, ANN architecture specifications for modelling of open-cell aluminium under compression, Mathematical Problems in Engineering, in press.
Kränzlin N., Niederberger M., 2015, Controlled fabrication of porous metalsfrom the nanometer to the macroscopic scale, Materials Horizons, 2, 4, 359-377, DOI: 10.1039/C4MH00244J.
Madsen K., Nielsen H.B., Tingleff O., 2004, Methods for non-linear least squares problems, [In:] Informatics and Mathematical Modelling Technical University of Denmark, available online: http://www2.i mm.dtu.dk/pubdb/views/edoc download.php/3215/pdf/imm3215.pdf (accessed on 15th Oct 2018).
Stręk A.M., Dudzik M., Kwiecień A., Wańczyk K., Lipowska B., 2019a, Verification of application of ANN modelling for compressive behaviour of metal sponges, Engineering Transactions, 67, 271-288.
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