Prediction of hardness and electrical properties in ZrB2 particle reinforced metal matrix composites using artificial neural network

Authors

  • Jovana Ružić
  • Davor Antanasijević
  • Dušan Božić
  • Karlo Raić

Keywords:

mechanical alloying, hot pressing process, Cu-ZrB2 alloy, mechanical properties, Artificial Neural Network

Abstract

In the present study, the hardness and electrical properties of copper based composite prepared by hot pressing of mechanically alloyed powders were predicted using Artificial Neural Network (ANN) approach. Milling time (t, h), particles size of mechanically alloyed powders (d, nm), dislocation density (Ï, m-2) and compressive yield stress (σ0.2, MPa) were used as inputs. The ANN model was developed using general regression neural network (GRNN) architecture. Cu-based composites reinforced with micro and nano ZrB2 particles were consolidated via powder metallurgy processing by combining mechanical alloying and hot pressing. Analysis of the obtained results concerning hardness and electrical properties of the Cu-7 vol.% ZrB2 alloy showed that the distribution of micro and nano ZrB2 particles and the presence of agglomerates in the Cu matrix directly depend on the milling time. Also, the results show a strong influence of the milling time on hardness and electrical properties of Cu-7 vol.% ZrB2 alloy. Addition of ZrB2 particles decreases electrical conductivity of copper, but despite this fact Cu-7 vol.% ZrB2 alloy can be marked as highly conductive alloy (samples made of mechanically alloyed powders milled longer than 20 h). Experimental results of the samples have shown a consistency with the predicted results of ANN.

 

http://dx.doi.org/10.5937/metmateng1404255R

References

H. Kimura, Muramatsu N, Suzuki K, Copper Alloy and Copper Alloy

Manufacturing Method, US0211346A1, 2005.

K.U. Kainer, Metal Matrix Composites, Wiley-VCH, Weinheim, 2006.

R. KoneĐná, S. Fintová, Copper and Copper Alloys: Casting, Classification and Characteristic Microstructures, Žilina, 2012.

M. Li, S.J. Zinkle, Comprehensive Nuclear Materials, Amsterdam, 4 (2012) 667-690

J.S. Andrus, R. G. Gordon, NASA Contractor Report, Florida, 1989.

M.M. Opeka, I.G. Talmy, E.J. Wuchina, J.A. Zaykoski, S.J. Causey, J. Eur. Ceram. Soc., 19 (1999) 2405-2414

T. Tsuchida, S. Yamamoto, J. Eur. Ceram. Soc, 24 (2004) 45-51

D. Božić, O. DimĐić, B. DimĐić, I. Cvijović, V. Rajković, Mater. Charact, 59 (2008) 1122-1126

D.W.A. Rees, Composites Part A, 29A (1998) 171-182

M. Amirjan, H. Khorsand, M. H. Siadati, R. E. Farsani, The Journal of Materials Research and Technology, 32 (2013) 351-355

Necat Altinkok a, Rasit Koker, Mater. Design., 27 (2006) 625-631

G. R. M. Balamuruga, V. Sugumaran, International Journal of Design and Manufacturing Technology, 1 (2010) 29-44

D. F. Specht, Ieee Transactions on Neural Networks, 2 (1991)

J. Ružić, Doctoral dissertation, Faculty of Technology and Metallurgy, University of Belgrade, 2014.

M.R. Roshan, M. Mirzaei, S.A. J. Jahromi, J. Alloy Compd., 569 (2013) 111-117

J. Ružić, J. StaÅ¡ić, S. Marković, K. Raić, D. Božić, Sci. Sinter., 46 (2014) 217-224

J. Ružić, J. StaÅ¡ić, V. Rajkovi , D. Božić’, Mater. Design., 62 (2014) 409-415

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Published

2014-12-31

How to Cite

Ružić, Jovana, Davor Antanasijević, Dušan Božić, and Karlo Raić. 2014. “Prediction of Hardness and Electrical Properties in ZrB2 Particle Reinforced Metal Matrix Composites Using Artificial Neural Network”. Metallurgical and Materials Engineering 20 (4):255-60. https://metall-mater-eng.com/index.php/home/article/view/147.

Issue

Vol. 20 No. 4 (2014): Special Issue: 20 years of Journal publishing

Section

Articles - archived

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