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Corrosion analysis in the Al6061-T6 alloy exposed to anhydrous ethanol-gasoline blends using the Stockwell transform and the Shannon energy
The study of corrosion on aluminum alloys exposed to alternative fuels, such as ethanol, or bioethanol has been studied and presented in the literature by different researchers. Among signal processing methods reported in the literature can be found the statistical method (SM), the Fast Fourier Tran...
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Published in: | Journal of alloys and compounds 2022-05, Vol.902, p.163802, Article 163802 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The study of corrosion on aluminum alloys exposed to alternative fuels, such as ethanol, or bioethanol has been studied and presented in the literature by different researchers. Among signal processing methods reported in the literature can be found the statistical method (SM), the Fast Fourier Transform (FFT), and the Wavelet transform. In the present research, we focused on the corrosion analysis in aluminum proposing an alternative signal processing method (the Stockwell Transform (ST)) and using ethanol-gasoline blends. In this analysis, the metallic material used was aluminum alloy 6061-T6 (Al6061-T6). And the signal processing is carried out by the ST and Shannon energy (SSE) methods. The results showed an average corrosion rate of 3.25 × 10−7mm∕year and 3.81 × 10−4mm∕year in the Al6061-T6 exposed to E0 and E100, respectively. Highlighting that E10 and E20 produced lower corrosion effects, and E60, E80, and E100 caused the highest corrosion levels.
•Corrosion analysis of the 6061-T6 aluminum alloy exposed to anhydrous ethanol-gasoline blends.•Stockwell transform analysis for classifying the corrosion type.•Stockwell transform and Shannon energy analysis to establish the corrosion behavior in the 6061-T6 aluminum alloy exposed to different ethanol-gasoline blends. |
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ISSN: | 0925-8388 1873-4669 |
DOI: | 10.1016/j.jallcom.2022.163802 |