Analysis and Optimization of the Electrohydraulic Forming Process of Sinusoidal Corrugation Tubes Article Swipe
Da Cai
,
Yinlong Song
,
Hao Jiang
,
Guangyao Li
,
Junjia Cui
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.32604/fdmp.2023.025833
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.32604/fdmp.2023.025833
Aluminum alloy thin-walled structures are widely used in the automotive industry due to their advantages related to light weight and crashworthiness.They can be produced at room temperature by the electrohydraulic forming process.In the present study, the influence of the related parameters on the forming quality of a 6063 aluminum alloy sinusoidal corrugation tube has been assessed.In particular, the orthogonal experimental design (OED) and central composite design (CCD) methods have been used.Through the range analysis and variance analysis of the experimental data, the influence degree of wire diameter (WD) and discharge energy (DE) on the forming quality was determined.Multiple regression analysis was performed using the response surface methodology.A prediction model for the attaching-die state coefficient was established accordingly.The following optimal arrangement of parameters was obtained (WD = 0.759 mm, DE = 2.926 kJ).The attaching-die state coefficient reached the peak value of 0.001.Better optimized wire diameter and discharge energy for a better attaching-die state could be screened by CCD compared with OED.The response surface method in CCD was more suitable for the design and optimization of the considered process parameters.
Related Topics
Concepts
Materials science
Design of experiments
Crashworthiness
Response surface methodology
Die (integrated circuit)
Central composite design
Aluminium
Alloy
Process optimization
Composite material
Forming processes
Tube (container)
Composite number
Orthogonal array
Mechanical engineering
Structural engineering
Taguchi methods
Finite element method
Engineering
Computer science
Mathematics
Environmental engineering
Statistics
Nanotechnology
Machine learning
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.32604/fdmp.2023.025833
- https://www.techscience.com/fdmp/online/detail/19574/pdf
- OA Status
- diamond
- Cited By
- 1
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389443416
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4389443416Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.32604/fdmp.2023.025833Digital Object Identifier
- Title
-
Analysis and Optimization of the Electrohydraulic Forming Process of Sinusoidal Corrugation TubesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-12-07Full publication date if available
- Authors
-
Da Cai, Yinlong Song, Hao Jiang, Guangyao Li, Junjia CuiList of authors in order
- Landing page
-
https://doi.org/10.32604/fdmp.2023.025833Publisher landing page
- PDF URL
-
https://www.techscience.com/fdmp/online/detail/19574/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://www.techscience.com/fdmp/online/detail/19574/pdfDirect OA link when available
- Concepts
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Materials science, Design of experiments, Crashworthiness, Response surface methodology, Die (integrated circuit), Central composite design, Aluminium, Alloy, Process optimization, Composite material, Forming processes, Tube (container), Composite number, Orthogonal array, Mechanical engineering, Structural engineering, Taguchi methods, Finite element method, Engineering, Computer science, Mathematics, Environmental engineering, Statistics, Nanotechnology, Machine learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- References (count)
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30Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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