Unraveling the Relationship between Microstructure and Mechanical Properties of Friction Stir-Welded Copper Joints by Fuzzy Logic Neural Networks Article Swipe
Mousa Javidani
,
Akbar Heidarzadeh
,
Reza Vatankhah Barenji
,
Moslem Paidar
,
H.R. Jafarian
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/cryst12020216
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/cryst12020216
In this study, fuzzy logic neural networks were employed to optimize the friction stir welding (FSW) process parameters in the joining of copper plates. The FSW parameters were considered as the input variables, for which micro-hardness, nano-hardness, and yield strength of the joints were the responses. The micro-hardness and nano-hardness were measured by Vickers hardness and nanoindentation tests, respectively. The microstructure and substructure of the joints were evaluated by optical, scanning electron, and orientation imaging microscopes. The optimum process parameters through which the maximum strength was achieved were the tool rotational rate of 560 rpm, tool traverse speed of 175 mm/min, and tool axial force of 2.27 kN. The low heat input joints, owing to the finer grain sizes, high density of dislocations, and larger Taylor factors, indicated greater strength relative to the high input joints. Microstructure characterization revealed that dominant strengthening mechanisms of the joints were dislocation density, texture effect, and grain boundary hardening.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/cryst12020216
- https://www.mdpi.com/2073-4352/12/2/216/pdf?version=1645514451
- OA Status
- gold
- Cited By
- 5
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4210471200
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4210471200Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/cryst12020216Digital Object Identifier
- Title
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Unraveling the Relationship between Microstructure and Mechanical Properties of Friction Stir-Welded Copper Joints by Fuzzy Logic Neural NetworksWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-01-31Full publication date if available
- Authors
-
Mousa Javidani, Akbar Heidarzadeh, Reza Vatankhah Barenji, Moslem Paidar, H.R. JafarianList of authors in order
- Landing page
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https://doi.org/10.3390/cryst12020216Publisher landing page
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https://www.mdpi.com/2073-4352/12/2/216/pdf?version=1645514451Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2073-4352/12/2/216/pdf?version=1645514451Direct OA link when available
- Concepts
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Materials science, Microstructure, Friction stir welding, Vickers hardness test, Nanoindentation, Composite material, Rotational speed, Welding, Ultimate tensile strength, Copper, Substructure, Hardening (computing), Metallurgy, Structural engineering, Mechanical engineering, Layer (electronics), EngineeringTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2025: 2, 2024: 2, 2022: 1Per-year citation counts (last 5 years)
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25Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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