Cargando…
Comparative Study of Machine Learning Approaches for Predicting Creep Behavior of Polyurethane Elastomer
The long-term mechanical properties of viscoelastic polymers are among their most important aspects. In the present research, a machine learning approach was proposed for creep properties’ prediction of polyurethane elastomer considering the effect of creep time, creep temperature, creep stress and...
Autores principales: | Yang, Chunhao, Ma, Wuning, Zhong, Jianlin, Zhang, Zhendong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8198355/ https://www.ncbi.nlm.nih.gov/pubmed/34071349 http://dx.doi.org/10.3390/polym13111768 |
Ejemplares similares
-
Low-Velocity Impact Behavior of Sandwich Plates with FG-CNTRC Face Sheets and Negative Poisson’s Ratio Auxetic Honeycombs Core
por: Yang, Chunhao, et al.
Publicado: (2022) -
Prediction of creep failure time using machine learning
por: Biswas, Soumyajyoti, et al.
Publicado: (2020) -
Creeping Bentgrass Yield Prediction With Machine Learning Models
por: Zhou, Qiyu, et al.
Publicado: (2021) -
Polyurethane elastomers: from morphology to mechanical aspects
por: Prisacariu, Cristina
Publicado: (2011) -
Corrigendum: Creeping Bentgrass Yield Prediction With Machine Learning Models
por: Zhou, Qiyu, et al.
Publicado: (2022)