Update search
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
NARROW
Format
Journal
Type
Date
Availability
1-2 of 2
Keywords: Friction stir processing
Close
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Sort by
Journal Articles
Predicting the wear rate of AA6082 aluminum surface composites produced by friction stir processing via artificial neural network
Available to Purchase
Multidiscipline Modeling in Materials and Structures (2020) 16 (2): 409–423.
Published: 24 September 2019
...Isaac Dinaharan; Ramaswamy Palanivel; Natarajan Murugan; Rudolf Frans Laubscher Purpose Friction stir processing (FSP) as a solid-state process has the potential for the production of effective aluminum matrix composites (AMCs). In this investigation, various ceramic particles including...
Journal Articles
Micro-hardness prediction of friction stir processed magnesium alloy via response surface methodology
Available to Purchase
Multidiscipline Modeling in Materials and Structures (2017) 13 (3): 377–390.
Published: 06 September 2017
...Ahmed Naser; Basil Darras Purpose The purpose of this paper is to present a model to predict the micro-hardness of friction stir processed (FSPed) AZ31B magnesium alloy using response surface methodology (RSM). Another objective is to identify process parameters and through-thickness position...
