Recent Advances on the Design Automation for Performance-Optimized Fiber Reinforced Polymer Composite Components
| Autor: | Goram Gohel, Sunil C. Joshi, Somen K. Bhudolia, Yi Di Boon |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Computer science Composite number 02 engineering and technology lcsh:Technology 020901 industrial engineering & automation composite microstructure Advanced manufacturing lcsh:Science Process engineering Engineering (miscellaneous) topology optimization lcsh:T business.industry Deep learning Topology optimization deep learning Material Design Fibre-reinforced plastic 021001 nanoscience & nanotechnology fiber-reinforced polymer Ceramics and Composites stress analysis lcsh:Q Electronic design automation Artificial intelligence 0210 nano-technology Engineering design process business |
| Zdroj: | Journal of Composites Science, Vol 4, Iss 61, p 61 (2020) |
| ISSN: | 2504-477X |
| DOI: | 10.3390/jcs4020061 |
| Popis: | Advanced manufacturing techniques, such as automated fiber placement and additive manufacturing enables the fabrication of fiber-reinforced polymer composite components with customized material and structural configurations. In order to take advantage of this customizability, the design process for fiber-reinforced polymer composite components needs to be improved. Machine learning methods have been identified as potential techniques capable of handling the complexity of the design problem. In this review, the applications of machine learning methods in various aspects of structural component design are discussed. They include studies on microstructure-based material design, applications of machine learning models in stress analysis, and topology optimization of fiber-reinforced polymer composites. A design automation framework for performance-optimized fiber-reinforced polymer composite components is also proposed. The proposed framework aims to provide a comprehensive and efficient approach for the design and optimization of fiber-reinforced polymer composite components. The challenges in building the models required for the proposed framework are also discussed briefly. |
| Databáze: | OpenAIRE |
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