Dengpeng Huang

Dengpeng Huang is an assistant professor at the University of Twente. His research focuses on the computational modeling of elastomers. Before that, he was a postdoc researcher at the University of Erlangen-Nuremberg from 2020 to 2023. He received his PhD in computational mechanics at the Leibniz University of Hannover in 2020. He studied mechanical engineering at the Jilin University and Shandong University in China.

---

Presentation

Prediction of elastomer properties using convolutional neural networks

To predict the elastomer properties from its microstructures, material models in different scales have been developed ranging from the molecular level to the macro level. However, the application of these models is limited by either the computational costs or their accuracy. An efficient but accurate modeling is still missing. Due to its promising prediction performance, machine learning provides a suitable alternative to traditional methods. In this study, the tensile properties of elastomers are predicted from the expanded TEM images using convolutional neural networks (CNN). The CNN model shows good accuracy and efficiency in prediction.