Fatigue Analysis of Printed Composites of Onyx and Kevlar
The transformation of powertrains, powered by internal combustion engines, into electrical systems generates new challenges in developing lightweight materials because electric vehicles are typically heavy. It is therefore important to develop new vehicles and seek more aesthetic and environmentally...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Journal of Composites Science |
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| Online Access: | https://www.mdpi.com/2504-477X/8/1/12 |
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| author | Moises Jimenez-Martinez Julio Varela-Soriano Julio S. De La Trinidad-Rendon Sergio G. Torres-Cedillo Jacinto Cortés-Pérez Manuel Coca-Gonzalez |
| author_facet | Moises Jimenez-Martinez Julio Varela-Soriano Julio S. De La Trinidad-Rendon Sergio G. Torres-Cedillo Jacinto Cortés-Pérez Manuel Coca-Gonzalez |
| author_sort | Moises Jimenez-Martinez |
| collection | DOAJ |
| description | The transformation of powertrains, powered by internal combustion engines, into electrical systems generates new challenges in developing lightweight materials because electric vehicles are typically heavy. It is therefore important to develop new vehicles and seek more aesthetic and environmentally friendly designs whilst integrating manufacturing processes that contribute to reducing the carbon footprint. At the same time, this research explores the development of new prototypes and custom components using printed composite materials. In this framework, it is essential to formulate new approaches to estimate fatigue life, specifically for components tailored and fabricated with these kinds of advanced materials. This study introduces a novel fatigue life prediction approach based on an artificial neural network. When presented with given inputs, this neural network is trained to predict the accumulation of fatigue damage and the temperature generated during cyclic loading, along with the mechanical properties of the compound. Its validation involves comparing the network’s response with the load ratio result, which can be calculated using the fatigue damage parameter. Comparing both results, the network can successfully predict the fatigue damage accumulation; this implies an ability to directly employ data on the mechanical behavior of the component, eliminating the necessity for experimental testing. Then, the current study introduces a neural network designed to predict the accumulated fatigue damage in printed composite materials with an Onyx matrix and Kevlar reinforcement. |
| first_indexed | 2024-03-08T10:46:30Z |
| format | Article |
| id | doaj.art-af29106d1577490487687bfe6c7dbd95 |
| institution | Directory Open Access Journal |
| issn | 2504-477X |
| language | English |
| last_indexed | 2024-03-08T10:46:30Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Composites Science |
| spelling | doaj.art-af29106d1577490487687bfe6c7dbd952024-01-26T17:10:41ZengMDPI AGJournal of Composites Science2504-477X2023-12-01811210.3390/jcs8010012Fatigue Analysis of Printed Composites of Onyx and KevlarMoises Jimenez-Martinez0Julio Varela-Soriano1Julio S. De La Trinidad-Rendon2Sergio G. Torres-Cedillo3Jacinto Cortés-Pérez4Manuel Coca-Gonzalez5Tecnologico de Monterrey, School of Engineering and Science, 5718 Via Atlixcayotl, Puebla 72453, MexicoTecnologico de Monterrey, School of Engineering and Science, 5718 Via Atlixcayotl, Puebla 72453, MexicoTecnologico de Monterrey, School of Engineering and Science, 5718 Via Atlixcayotl, Puebla 72453, MexicoCentro Tecnológico FES Aragón, Universidad Nacional Autónoma de México, Mexico City 57171, MexicoCentro Tecnológico FES Aragón, Universidad Nacional Autónoma de México, Mexico City 57171, MexicoTecnologico de Monterrey, School of Engineering and Science, 5718 Via Atlixcayotl, Puebla 72453, MexicoThe transformation of powertrains, powered by internal combustion engines, into electrical systems generates new challenges in developing lightweight materials because electric vehicles are typically heavy. It is therefore important to develop new vehicles and seek more aesthetic and environmentally friendly designs whilst integrating manufacturing processes that contribute to reducing the carbon footprint. At the same time, this research explores the development of new prototypes and custom components using printed composite materials. In this framework, it is essential to formulate new approaches to estimate fatigue life, specifically for components tailored and fabricated with these kinds of advanced materials. This study introduces a novel fatigue life prediction approach based on an artificial neural network. When presented with given inputs, this neural network is trained to predict the accumulation of fatigue damage and the temperature generated during cyclic loading, along with the mechanical properties of the compound. Its validation involves comparing the network’s response with the load ratio result, which can be calculated using the fatigue damage parameter. Comparing both results, the network can successfully predict the fatigue damage accumulation; this implies an ability to directly employ data on the mechanical behavior of the component, eliminating the necessity for experimental testing. Then, the current study introduces a neural network designed to predict the accumulated fatigue damage in printed composite materials with an Onyx matrix and Kevlar reinforcement.https://www.mdpi.com/2504-477X/8/1/12compositefatigueadditive manufacturingdamagelightweight materials |
| spellingShingle | Moises Jimenez-Martinez Julio Varela-Soriano Julio S. De La Trinidad-Rendon Sergio G. Torres-Cedillo Jacinto Cortés-Pérez Manuel Coca-Gonzalez Fatigue Analysis of Printed Composites of Onyx and Kevlar Journal of Composites Science composite fatigue additive manufacturing damage lightweight materials |
| title | Fatigue Analysis of Printed Composites of Onyx and Kevlar |
| title_full | Fatigue Analysis of Printed Composites of Onyx and Kevlar |
| title_fullStr | Fatigue Analysis of Printed Composites of Onyx and Kevlar |
| title_full_unstemmed | Fatigue Analysis of Printed Composites of Onyx and Kevlar |
| title_short | Fatigue Analysis of Printed Composites of Onyx and Kevlar |
| title_sort | fatigue analysis of printed composites of onyx and kevlar |
| topic | composite fatigue additive manufacturing damage lightweight materials |
| url | https://www.mdpi.com/2504-477X/8/1/12 |
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