Cargando…
Integration of thermal imaging and neural networks for mechanical strength analysis and fracture prediction in 3D-printed plastic parts
Additive manufacturing demonstrates tremendous progress and is expected to play an important role in the creation of construction materials and final products. Contactless (remote) mechanical testing of the materials and 3D printed parts is a critical limitation since the amount of collected data an...
Autores principales: | Boiko, Daniil A., Korabelnikova, Victoria A., Gordeev, Evgeniy G., Ananikov, Valentine P. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9142534/ https://www.ncbi.nlm.nih.gov/pubmed/35624225 http://dx.doi.org/10.1038/s41598-022-12503-y |
Ejemplares similares
-
Deep neural network analysis of nanoparticle ordering to identify defects in layered carbon materials
por: Boiko, Daniil A., et al.
Publicado: (2021) -
Improvement of quality of 3D printed objects by elimination of microscopic structural defects in fused deposition modeling
por: Gordeev, Evgeniy G., et al.
Publicado: (2018) -
Exploring metallic and plastic 3D printed photochemical reactors for customizing chemical synthesis
por: Gordeev, Evgeniy G., et al.
Publicado: (2022) -
Revealing interactions of layered polymeric materials at solid-liquid interface for building solvent compatibility charts for 3D printing applications
por: Erokhin, Kirill S., et al.
Publicado: (2019) -
Thermal Mapping of Self-Promoted Calcium Carbide Reactions for Performing Energy-Economic Processes
por: Rodygin, Konstantin S., et al.
Publicado: (2022)