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Two-scale data-driven design for heat manipulation
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DOI：10.1016/j.ijheatmasstransfer.2023.124823.png)
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摘要
En 中文
Data-driven methods have gained increasing attention in computational mechanics and design. This study investigates a two-scale data-driven design for thermal metamaterials with various functionalities. To address the complexity of multiscale design, the design variables are chosen as the components of the homogenized thermal conductivity matrix originating from the lower scale unit cells. Multiple macroscopic functionalities including thermal cloak, thermal concentrator, thermal rotator/inverter, and their combinations, are achieved using the developed approach. Sensitivity analysis is performed to determine the effect of each design variable on the desired functionalities, which is then incorporated into topology optimization. Geometric extraction demonstrates an excellent matching between the optimized homogenized conductivity and the extraction from the constructed database containing both architecture and property information. The designed heterostructures exhibit multiple thermal meta-functionalities that can be applied to a wide range of heat transfer fields from personal computers to aerospace engineering.
Keyword:
Data-driven methods
Thermal metamaterials
Design optimization
Homogenization
Heat manipulation
Heat conduction
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期刊
IF:
5.8
论文数:
2.6W
被引数:
10.2W
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引用论文
Design optimization of multifunctional metamaterials with tunable thermal expansion and phononic bandgap具有可调热膨胀和声子带隙的多功能超材料的设计优化.png)
MATERIALS & DESIGNOAAI
MATERIALS & DESIGNIF7.9
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