| 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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Ramesh, S.
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (12/12 displayed)
- 2024Enhancing wear resistance of AZ61 alloy through friction stir processing: experimental study and prediction modelcitations
- 2024Impact of ply stacking sequence on the mechanical response of hybrid Jute-Banana fiber phenoplast compositescitations
- 2023Magnetic and Magnetostrictive Properties of Sol–Gel-Synthesized Chromium-Substituted Cobalt Ferritecitations
- 2023Effect of sintering additives on the properties of alumina toughened zirconia (ATZ)citations
- 2022Surface thermodynamic properties by reverse phase chromatography and visual traits using computer vision techniques on Amberlite XAD-7 acrylic-ester-resincitations
- 2021An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural Networkcitations
- 2021Design and formulation of microbially induced self-healing concrete for building structure strength enhancementcitations
- 2021Simulation Process of Injection Molding and Optimization for Automobile Instrument Parameter in Embedded Systemcitations
- 2018Is Graphitic Silicon Carbide (Silagraphene) Stable?citations
- 2016Poly(methyl methacrylate-co-butyl acrylate-co-acrylic acid): Physico-chemical characterization and targeted dye sensitized solar cell applicationcitations
- 2014Effect of Silver Nanoparticles on the Mechanical and Physical Properties of Epoxy Based Silane Coupling Agentcitations
- 2014Scratch resistance enhancement of 3-glycidyloxypropyltrimethoxysilane coating incorporated with silver nanoparticlescitations
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article
Enhancing wear resistance of AZ61 alloy through friction stir processing: experimental study and prediction model
Abstract
<jats:title>Abstract</jats:title><jats:p>In this study, friction stir processing (FSP) is proposed for the treatment of AZ61 alloy, and an artificial neural network is built to predict and compare the experimental wear results. The effects of different processing parameters, including spindle speed (800–1200 rpm), traveling speed (5–15 mm min<jats:sup>−1</jats:sup>), and depth of press (0.8–1.2 mm) on the microstructural evolution, mechanical properties, and wear behavior are investigated. Microstructural analysis reveals a grain size of 14 ± 2 <jats:italic>μ</jats:italic>m for the FSP1 sample, with observed shifting of x-ray diffraction (XRD) peaks, indicative of texture development. Increasing spindle and traveling speeds increase the surface roughness, as observed by average roughness (Ra) values of 68.4 nm for a rotational speed of 800 rpm, traveling speed of 5 mm min<jats:sup>−1</jats:sup>, and shoulder depth of 0.8 mm (FSP1) and 116.3 nm for rotational speed of 1200 rpm, traveling speed of 15 mm min<jats:sup>−1</jats:sup>, and shoulder depth of 1 mm (FSP9). Microhardness values increase to 113.36 Hv for FSP1 and 79. 51 Hv for FSP9 compared to 65.92 Hv for the base material (BM) sample. The decrement in hardness from FSP1 to FSP9 can be attributed to increased heat input, resulting in coarse microstructure. Wear results show that FSP1 exhibits the lowest weight loss (0.003 g) and coefficient of friction (COF) (0.28) compared to other FSP conditions and BM samples (weight loss of 0.022 g and COF of 0.68). This work demonstrates the efficacy of friction stir processing in enhancing the wear resistance of magnesium alloys.</jats:p>