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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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Dikici, Burak
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Publications (6/6 displayed)
- 2025Effect of Nb0.5 and Mo0.75 addition on in-vitro corrosion and wear resistance of high-speed laser metal deposited Al0.3CrFeCoNi high-entropy alloy coatingscitations
- 2024Enhanced Cadmium Sensing in Fertilizer Samples using Zeolite-modified Graphite Electrodecitations
- 2024Anticorrosive characteristics of imidazole derivative on carbon steel in 1 M HClcitations
- 2023Investigation of the influence of high-pressure torsion and solution treatment on corrosion and tribocorrosion behavior of CoCrMo alloys for biomedical applicationscitations
- 2021An artificial neural network (ANN) solution to the prediction of age-hardening and corrosion behavior of an Al/TiC functional gradient material (FGM)citations
- 2020The effect of graphene nano-sheet (GNS) weight percentage on mechanical and corrosion properties of AZ61 and AZ91 based magnesium matrix compositescitations
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article
An artificial neural network (ANN) solution to the prediction of age-hardening and corrosion behavior of an Al/TiC functional gradient material (FGM)
Abstract
<jats:p> In this theoretical study, the prediction of the corrosion resistance and age-hardening behavior of an Al/TiC functional gradient material (FGM) has been investigated by using the artificial neural network (ANN). The input parameters have been selected as TiC volume fraction of the composite layers, aging periods of the composite, environmental conditions, and applied potential during the corrosion tests. Current and microhardness were used as the one output in the proposed network. Also, a new three-layered composite has been imaginarily designed to demonstrate the predictive capability and flexibilities of the ANN model as a case study. Artificially aging (T6) process and potentiodynamic scanning (PDS) tests were used for heat-treating and corrosion response of the FGS, respectively. The results showed that the generated PDS curves of the FGM and calculated corrosion parameters of the case study are quite near and in acceptable limits for similar composites obtained values in experimental studies. Besides, this study has been a great success in predicting peak-aging times and its corresponding hardness values more precisely. </jats:p>