ANN model of stress-strain relationship for aluminium sponge in uniaxial compression

• Autorzy: Dudzik Marek , Stręk Anna Małgorzata

Identyfikatory

DOI

10.15632/jtam-pl/116804

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

artificial neural network design; compressive behaviour; open-cell aluminium; model equation

• Wydawca: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
• Czasopismo: Journal of Theoretical and Applied Mechanics
• Rocznik: 2020
• Tom: Vol. 58 nr 2
• Strony: 385--390
• Opis fizyczny: Bibliogr. 13 poz., rys., tab.

Twórcy

autor

Dudzik Marek

• Cracow University of Technology, Faculty of Electrical and Computer Engineering, Cracow, Poland

autor

Stręk Anna Małgorzata

• Cracow University of Technology, Faculty of Electrical and Computer Engineering, Cracow, Poland

Bibliografia

• 1. Demuth H., Beale M., Hagan M., 2009, Neural Network Toolbox 6 User’s Guide, MathWorks Inc.
• 2. Dudzik M., Stręk A.M., 2020, ANN architecture specifications for modelling of open-cell aluminium under compression, Mathematical Problems in Engineering, in press.
• 3. García-Moreno F., 2016, Commercial applications of metal foams: their properties and production, Materials, 9, 85, DOI:10.3390/ma9020085.
• 4. Gibson L.J., Ashby M.F., 1988, Cellular Solids. Structure and Properties, Pergamon Press.
• 5. Hagan M.T., Demuth H.B., Beale M.H., De Jesus O., 2014, Neural Network Design, eBook.
• 6. ISO 13314:2011 Mechanical testing of metals – Ductility testing – Compression test for porous and cellular metals.
• 7. Kasza P., Lipowska B., Pęcherski R.B., Stręk A.M., Wańczyk K., 2016, Compression of open-cell aluminium, Engineering Transactions, 64, 4, 629-634.
• 8. 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.
• 9. 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.... (accessed on 15th Oct 2018).
• 10. Potrzeszcz-Sut B., Pabisek E., 2014, ANN constitutive material model in the shakedown analysis of an aluminium structure, CAMES, 21, 49-58.
• 11. 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.
• 12. Stręk A.M., Lipowska B., Wańczyk K., 2019b, Selected aspects of manufacturing of aluminium sponge, Archives of Metallurgy and Materials, 3, 1145-1150.
• 13. Sumelka W., Łodygowski T., 2013, Reduction of the number of material parameters by ANN approximation, Computational Mechanics, 52, 2, 287-300.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).