Two-scale data-driven design for heat manipulation

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.

[1]  X. Gu,et al.  Topology optimization of thermal cloaks in euclidean spaces and manifolds using an extended level set method , 2023, International Journal of Heat and Mass Transfer.

[2]  M. Xiao,et al.  Topology-optimized freeform thermal metamaterials for omnidirectionally cloaking sensors , 2022, Materials Today Physics.

[3]  M. Yu Wang,et al.  Design of Multi-material Isotropic Auxetic Microlattices with Zero Thermal Expansion , 2022, Materials & Design.

[4]  M. Xiao,et al.  Topology-optimized thermal metamaterials traversing full-parameter anisotropic space , 2022, npj Computational Materials.

[5]  Shikui Chen,et al.  Level-Set-Based Shape & Topology Optimization of Thermal Cloaks , 2022, Volume 3A: 48th Design Automation Conference (DAC).

[6]  O. Sigmund,et al.  On the use of artificial neural networks in topology optimisation , 2022, Structural and Multidisciplinary Optimization.

[7]  Yu-Chin Chan,et al.  Generalized de-homogenization via sawtooth-function-based mapping and its demonstration on data-driven frequency response optimization , 2022, Computer Methods in Applied Mechanics and Engineering.

[8]  Liang Gao,et al.  Robustly printable freeform thermal metamaterials , 2021, Nature Communications.

[9]  R. Tao,et al.  Design optimization of multifunctional metamaterials with tunable thermal expansion and phononic bandgap , 2021 .

[10]  Yu-Chin Chan,et al.  Data-driven and Topological Design of Structural Metamaterials for Fracture Resistance , 2021, Video Proceedings of Advanced Materials.

[11]  M. Fuge,et al.  IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures , 2021, Computer Methods in Applied Mechanics and Engineering.

[12]  D. Kochmann,et al.  Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy , 2020, ArXiv.

[13]  Seungjae Min,et al.  Heat flux manipulation by using a single-variable formulated multi-scale topology optimization method , 2020 .

[14]  Youhei Akimoto,et al.  Cloaking a concentrator in thermal conduction via topology optimization , 2020 .

[15]  Jiping Huang,et al.  Thermal Metamaterial: Fundamental, Application, and Outlook , 2020, iScience.

[16]  J. Yvonnet.  Computational Homogenization of Heterogeneous Materials with Finite Elements , 2020, Solid Mechanics and Its Applications.

[17]  Yu-Chin Chan,et al.  Deep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems , 2020, Computer Methods in Applied Mechanics and Engineering.

[18]  Zhen Liu,et al.  Data-driven design approach to hierarchical hybrid structures with multiple lattice configurations , 2020, Structural and Multidisciplinary Optimization.

[19]  Youhei Akimoto,et al.  Optimizing the structural topology of bifunctional invisible cloak manipulating heat flux and direct current , 2019, Applied Physics Letters.

[20]  Youhei Akimoto,et al.  Topology-optimized thermal carpet cloak expressed by an immersed-boundary level-set method via a covariance matrix adaptation evolution strategy , 2019, International Journal of Heat and Mass Transfer.

[21]  Guoying Dong,et al.  Design and Optimization of Graded Cellular Structures With Triply Periodic Level Surface-Based Topological Shapes , 2019, Journal of Mechanical Design.

[22]  Xiaobing Luo,et al.  While rotating while cloaking , 2019, Physics Letters A.

[23]  Youhei Akimoto,et al.  Exploring optimal topology of thermal cloaks by CMA-ES , 2018 .

[24]  Tsuyoshi Nomura,et al.  Thermal Metamaterials for Heat Flow Control in Electronics , 2017 .

[25]  Ignacio Peralta,et al.  Optimization-based design of heat flux manipulation devices with emphasis on fabricability , 2017, Scientific Reports.

[26]  Wojciech Matusik,et al.  Two-Scale Topology Optimization with Microstructures , 2017, TOGS.

[27]  Paolo Cignoni,et al.  Elastic textures for additive fabrication , 2015, ACM Trans. Graph..

[28]  Fei Chen,et al.  Experimental Realization of Extreme Heat Flux Concentration with Easy-to-Make Thermal Metamaterials , 2015, Scientific Reports.

[29]  Jiping Huang,et al.  Thermal cloak-concentrator , 2015, 1506.01532.

[30]  Krishna P. Vemuri,et al.  Guiding conductive heat flux through thermal metamaterials , 2014 .

[31]  Sailing He,et al.  Experimental demonstration of a multiphysics cloak: manipulating heat flux and electric current simultaneously. , 2014, Physical review letters.

[32]  Cheng-Wei Qiu,et al.  Full Control and Manipulation of Heat Signatures: Cloaking, Camouflage and Thermal Metamaterials , 2014, Advanced materials.

[33]  Casper Schousboe Andreasen,et al.  How to determine composite material properties using numerical homogenization , 2014 .

[34]  Fei Gao,et al.  Ultrathin three-dimensional thermal cloak. , 2014, Physical review letters.

[35]  Tiancheng Han,et al.  Experimental demonstration of a bilayer thermal cloak. , 2014, Physical review letters.

[36]  G. Castaldi,et al.  Independent Manipulation of Heat and Electrical Current via Bifunctional Metamaterials , 2013, 1311.6119.

[37]  Tsuyoshi Nomura,et al.  Heat flux cloaking, focusing, and reversal in ultra-thin composites considering conduction-convection effects , 2013 .

[38]  Cheng-Wei Qiu,et al.  Homogeneous Thermal Cloak with Constant Conductivity and Tunable Heat Localization , 2013, Scientific Reports.

[39]  M. Wegener,et al.  Experiments on transformation thermodynamics: molding the flow of heat. , 2012, Physical review letters.

[40]  Yuki Sato,et al.  Heat flux manipulation with engineered thermal materials. , 2012, Physical review letters.

[41]  Claude Amra,et al.  Transformation thermodynamics: cloaking and concentrating heat flux. , 2012, Optics express.

[42]  Jiping Huang,et al.  Shaped graded materials with an apparent negative thermal conductivity , 2008 .

[43]  U. Leonhardt.  Optical Conformal Mapping , 2006, Science.

[44]  E. Hinton,et al.  A review of homogenization and topology opimization II—analytical and numerical solution of homogenization equations , 1998 .

[45]  E. Hinton,et al.  A review of homogenization and topology optimization I- homogenization theory for media with periodic structure , 1998 .

[46]  Tsuyoshi Nomura,et al.  Thermal-composite design optimization for heat flux shielding, focusing, and reversal , 2014 .