Item Infomation

Full metadata record
DC FieldValueLanguage
dc.contributor.authorTien,Thinh Le-
dc.contributor.authorMinh, Vuong Le-
dc.date.accessioned2022-05-05T07:26:11Z-
dc.date.available2022-05-05T07:26:11Z-
dc.date.issued2022-
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-030-92574-1_80-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/5715-
dc.description.abstractThis work develops a Neural Network (NN) model for the prediction of the tensile modulus of carbon nanotube (CN)/polymer nanocomposites, based on experimental database. A data set composed of 282 configurations is collected from available resources. Considered input variables of the dataset are such as mechanical properties of separated phases, density of polymer matrix, processing method, geometry of CN, modification method at the CN surface, etc. while the problem output is the tensile modulus of nanocomposite. Parametric studies have been performed in finding optimum architecture of the proposed NN model.vi
dc.language.isoenvi
dc.publisherSpringervi
dc.subjectNeural Network-
dc.subjectCarbon nanotubes
dc.titlePrediction Model for Tensile Modulus of Carbon Nanotube–Polymer Compositesvi
dc.typeBài tríchvi
eperson.identifier.doihttps://doi.org/10.1007/978-3-030-92574-1_80-
Appears in Collections
Bài báo khoa học

Files in This Item:

There are no files associated with this item.