693.932 PEOPLE
| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Kamble, Vikram G.
Polymer Competence Center Leoben (Austria)
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (4/4 displayed)
- 2021Fundamentals and working mechanisms of artificial muscles with textile application in the loopcitations
- 2015Study of Tool Wear Properties Using Magnetorheological Fluid Dampercitations
- 2015PREDICTION OF FRICTIONAL AND WEAR BEHAVIOR OF ALUMINIUM MATRIX COMPOSITES BY ARTIFICIAL NEURAL NETWORKcitations
- 2014Preparation of a Silicon oil based Magneto Rheological Fluid and an Experimental Study of its Rheological Properties using a Plate and Cone Type Rheometer
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article
PREDICTION OF FRICTIONAL AND WEAR BEHAVIOR OF ALUMINIUM MATRIX COMPOSITES BY ARTIFICIAL NEURAL NETWORK
Abstract
Modern technologies require materials with unusual combination of properties that cannot be met by conventional metal alloys, ceramic, etc. In our work, we prepared the samples of metal alloys such as Al356-TiB2. Processing of samples is done by artifcial neural network (ANN) which is one of the promising fields of research in predicting experimental results. In our investigation we worked on grain size analysis, micro hardness, regression analysis, friction test, wear test and micro structure analysis of samples to describe the materials properties of Al356-TiB2.