Enhanced Cellular Materials through Multiscale, Variable-Section Inner Designs: Mechanical Attributes and Neural Network Modeling
Abstract
:1. Introduction
2. Multiscale Hollow and Variable Inner Cross-Section Cellular Material Designs
2.1. Analytical and Numerical Characterization
2.2. Additive Manufacturing and Experimental Characterization
3. Machine-Learning-Based Modeling and Design of Multiscale Metamaterial Architectures
4. Effective Mechanical Attributes of Multiscale, Variable Inner Section Cellular Materials
5. Neural-Network-Based Multiscale Metamaterial Forward Modeling and Inverse Design
6. Discussion
7. Conclusions
- Hollow, variable-section inner structural designs allow for an enhanced, specific normal, shear and bulk metamaterial response, well beyond the range of single-scale metamaterial architectures.
- The insertion of a second inner scale affects the macroscale metamaterial performance in a non-unique manner, which depends on the uppermost-scale cellular pattern design.
- Multiscale designs can modify the stiffness-to-density scaling of cellular materials from a bending-dominated towards a stretching-dominated response.
- Low-numerical-cost neural network models can derive a robust link between the different inner scales and the complete set of effective elastic cellular material properties.
- Inverse multi-objective engineering tasks can, therefore, be performed, identifying the optimal multiscale cellular patterns that best satisfy the macroscale performance requests.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
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Input Features | Range | Sampling Points |
---|---|---|
Es | 50–210 (GPa) | 9 |
0.5–1.5 (mm) | 11 | |
0.2–0.8 (-) | 7 | |
1/20–1/50 (0) | 7 | |
0–1 (-) | 11 |
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Karathanasopoulos, N.; Rodopoulos, D.C. Enhanced Cellular Materials through Multiscale, Variable-Section Inner Designs: Mechanical Attributes and Neural Network Modeling. Materials 2022, 15, 3581. https://doi.org/10.3390/ma15103581
Karathanasopoulos N, Rodopoulos DC. Enhanced Cellular Materials through Multiscale, Variable-Section Inner Designs: Mechanical Attributes and Neural Network Modeling. Materials. 2022; 15(10):3581. https://doi.org/10.3390/ma15103581
Chicago/Turabian StyleKarathanasopoulos, Nikolaos, and Dimitrios C. Rodopoulos. 2022. "Enhanced Cellular Materials through Multiscale, Variable-Section Inner Designs: Mechanical Attributes and Neural Network Modeling" Materials 15, no. 10: 3581. https://doi.org/10.3390/ma15103581
APA StyleKarathanasopoulos, N., & Rodopoulos, D. C. (2022). Enhanced Cellular Materials through Multiscale, Variable-Section Inner Designs: Mechanical Attributes and Neural Network Modeling. Materials, 15(10), 3581. https://doi.org/10.3390/ma15103581