Topology-optimized thermal cloak-concentrator



Credit: Garuda Fujii, Institute of Engineering, Shinshu University, Japan

Topology-optimized thermal cloak-concentrator realizes excellent cloaking and concentrating simultaneously although it is built of a simple composition. The thermal cloak-concentrator is not so easily effected by fluctuations of thermal conductivity and is designed by incorporating multiple objective functions under various thermal conductivities.

Garuda Fujii of Shinshu University succeeded in simplifying cloaking with the use of topology optimization. In previous studies, metamaterials, which are artificial structures were used to achieve two functions, such as cloaking and concentrating. However, metamaterials make it difficult to manufacture and performance is not easily improved because the performance estimation becomes approximate.

Previous studies investigated the use of general bulk materials, however, it is difficult to achieve multifunctionality and the studies look at just cloaking or concentrating only. By using topology optimization, which is a computational structural design methodology, researchers can use general bulk materials and realize multifunctionality.

The study looked at cloaking the concentrating system in thermal conduction and concentrating heat flux using general materials such as iron, copper, and PDMS. To create STL data of the optimized structures for future experimental demonstrations, they used a structural expression method that can handle the boundaries between different materials clearly and numerically, so called level set-boundary expression. The STL data is publicly available for those who would like to experiment with it.

This study relied on simulations, Associate Professor Fujii hopes to realize this performance in an experiment.


For more information on the study, please read, Cloaking a concentrator in thermal conduction via topology optimization.

Associate Professor Garuda Fujii’s Research Laboratory:

This work is supported by JSPS KAKENHI Grant number 17K17778.

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