Design and Performance Study of Carbon Fiber-Reinforced Polymer Connection Structures with Surface Treatment on Aluminum Alloy (6061)
COATINGS（2024）
State Key Laboratory for Modification of Chemical Fibers and Polymer Materials
Abstract
The existing connection methods for aluminum alloy profiles primarily include adhesive bonding and mechanical connections, with metal welding being widely employed. However, metal welding connections exhibit issues such as low joint strength, significant welding deformation, susceptibility to surface oxidation, poor welding surface quality, and challenges in achieving thin-walled metal structures. This paper presents a novel aluminum alloy connection structure that utilizes carbon fiber-reinforced polymer (CFRP) composites to replace welding for connecting aluminum alloy profiles. This innovative aluminum alloy composite connection structure not only enhances connection strength but also addresses the difficulties associated with metal welding. Research indicates that the optimal width of the CFRP structure in the connector is 60 mm, and with synergistic treatment of the aluminum alloy surface, the connection enhancement effect is optimal. Under these conditions, the tensile load can reach 58.71 kN and the bending load can reach 14.33 kN, which are 375.38% and 380.87% higher than those of welded aluminum alloy connections, respectively. The mass-specific strength increases by 106.27% and 134.42%, respectively. Simulations of this connection structure in components demonstrate that it improves strength by 73.99% and mass-specific strength by 71.95% compared to pure metal welded connections. Using ABAQUS 2023 software for simulation and calculation, the difference between the simulation and experimental results is within 5%, verifying the feasibility of the designed structure. This study provides new insights and a theoretical foundation for the development and application of hybrid connection methods involving metal and fiber-reinforced composites.
MoreTranslated text
Key words
connection structure,CFRP,surface treatment,finite element simulation,mechanical performance
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined