相关实验视频

Updated: May 10, 2026

Production of a Strain-Measuring Device with an Improved 3D Printer
06:17

Production of a Strain-Measuring Device with an Improved 3D Printer

Published on: January 30, 2020

6.5K

从工艺参数预测3D打印聚合物的机械性质的机器学习:一篇评论

Savvas Koltsakidis1, Emmanouil K Tzimtzimis1, Dimitrios Tzetzis1

  • 1Digital Manufacturing and Materials Characterization Laboratory, School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece.

Polymers
|February 27, 2026
PubMed
概括

机器学习模型准确地预测了聚合物增材制造 (AM) 零件的机械性能. 这些数据驱动的方法显著减少了对3D打印组件的实验优化需求.

关键词:
添加剂制造 添加剂制造 添加剂制造人工神经网络的人工神经网络机器学习是机器学习.机械性能 机械性能 机械性能过程参数 过程参数

更多相关视频

Author Spotlight: Real-Time Imaging of Bonding in 3D-Printed Layers04:36

Author Spotlight: Real-Time Imaging of Bonding in 3D-Printed Layers

Published on: September 1, 2023

4.0K
Characterizing Dissipative Elastic Metamaterials Produced by Additive Manufacturing09:39

Characterizing Dissipative Elastic Metamaterials Produced by Additive Manufacturing

Published on: June 28, 2024

1.7K

相关概念视频

Classification and Mechanical Properties of Synthetic Polymers01:28

Classification and Mechanical Properties of Synthetic Polymers

Synthetic polymers are classified as elastomers, fibers, or plastics based on their crystallinity. Crystallinity, the degree of long-range order in the solid state, influences the mechanical properties (stretching or contracting) of elastomers. Elastomers are flexible polymers that can expand or contract easily upon the application of an external force. They have numerous crosslinks that pull them back into their original shape when stress is removed. Silicones, for instance, are highly elastic...