This study explores the design of 3D-printable biomimetic rods with enhanced buckling resistance using machine learning. By mimicking the structures of plant stems and roots, a training database was created through finite element analysis (FEA) and validated experimentally. Machine learning was then employed to optimize the rod designs, resulting in a 150% improvement in buckling resistance compared to natural counterparts. This approach offers potential for designing superior engineering rods and columns for various applications.
Publisher
Scientific Reports
Published On
Nov 26, 2020
Authors
Adithya Challapalli, Guoqiang Li
Tags
3D printing
biomimetic design
machine learning
buckling resistance
finite element analysis
engineering
optimization
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