Приказ основних података о документу
Artificial neural networks in advanced thermoset matrix composite manufacturing
dc.creator | Carlone, Pierpaolo | |
dc.creator | Aleksendrić, Dragan | |
dc.creator | Rubino, Felice | |
dc.creator | Ćirović, Velimir | |
dc.date.accessioned | 2022-09-19T18:38:56Z | |
dc.date.available | 2022-09-19T18:38:56Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 2195-4356 | |
dc.identifier.uri | https://machinery.mas.bg.ac.rs/handle/123456789/2992 | |
dc.description.abstract | Autoclave curing is a common practice to manufacture high temperature thermoset matrix composites. The cycle design and optimization of the temperature-time curve is a key issue for a competitive production. In this paper artificial neural networks (ANN), as a technique of artificial intelligence, were used for prediction of the composite temperature profile during the autoclave curing process. Different neural network models have been investigated regarding their capabilities for prediction of the composite temperature profile. The new neural network model has been developed able to predict the composite temperature profile in the wide range of manufacturing conditions changing. | en |
dc.publisher | Pleiades journals | |
dc.rights | restrictedAccess | |
dc.source | Lecture Notes in Mechanical Engineering | |
dc.subject | Curing process | en |
dc.subject | Composite material | en |
dc.subject | Artificial neural networks | en |
dc.title | Artificial neural networks in advanced thermoset matrix composite manufacturing | en |
dc.type | bookPart | |
dc.rights.license | ARR | |
dc.citation.epage | 88 | |
dc.citation.issue | 9783319895628 | |
dc.citation.other | 0(9783319895628): 78-88 | |
dc.citation.rank | M14 | |
dc.citation.spage | 78 | |
dc.citation.volume | 0 | |
dc.identifier.doi | 10.1007/978-3-319-89563-5_5 | |
dc.identifier.scopus | 2-s2.0-85046801777 | |
dc.type.version | publishedVersion |