Investigation on the effect of process parameters in atmospheric pressure plasma treatment on carbon fiber reinforced polymer surfaces for bonding
| Autor: | Mahdi Yoozbashizadeh, Doug Decker, Marios Chartosias, Chad Victorino |
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| Rok vydání: | 2019 |
| Předmět: |
010302 applied physics
Carbon fiber reinforced polymer chemistry.chemical_classification 0209 industrial biotechnology Materials science business.industry Mechanical Engineering Composite number Atmospheric-pressure plasma 02 engineering and technology Polymer Plasma 01 natural sciences Industrial and Manufacturing Engineering 020901 industrial engineering & automation chemistry Mechanics of Materials Surface preparation Scientific method 0103 physical sciences General Materials Science Composite material Aerospace business |
| DOI: | 10.6084/m9.figshare.7798967.v1 |
| Popis: | Carbon Fiber Reinforced Polymer (CFRP) is used extensively in aerospace applications. Acceptance of bonded CFRP structures, mainly for aerospace applications, requires a robust surface preparation method with improved process controls to ensure high bond quality. Consistent repeatability is a factor lacking from many surface preparation processes. Atmospheric pressure plasma surface treatment is one of the robust surface preparation processes that have drawn wide attention in recent years. This process is capable of being applied in a production clean room environment that would minimize the risk of contamination and reduce cost. In plasma surface treatment the process parameters are easily controlled, documented providing a repeatable process with a high level of consistency. In this paper, the process parameters for atmospheric pressure plasma surface treatment and their effect on bonding for Out-Of-Autoclave (OOA) CFRP composite panels were fully investigated. A mechanized machine with sensory feedback to plasma treat surfaces was developed to change the process parameters for application on larger panels. By the aid of Design of Experiment (DOE) methodology critical process parameters were identified and a mathematical regression model was developed. The mathematical regression model was used to quantify the effect of process parameters on the bonding strength and the model was optimized to find the optimum settings. |
| Databáze: | OpenAIRE |
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