Particle swarm optimization for realizing bilayer thermal sensors with bulk isotropic materials
•A size-adjusted optimization model for thermal sensors is proposed.•Designed scheme keeps high performance, confirmed by experiments.•This method has strong portability, applying many structures.•Such a scheme greatly simplifies engineering preparation. Metamaterial-based devices have been extensiv...
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| Vydáno v: | International journal of heat and mass transfer Ročník 172; s. 121177 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Oxford
Elsevier Ltd
01.06.2021
Elsevier BV |
| Témata: | |
| ISSN: | 0017-9310, 1879-2189 |
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| Abstract | •A size-adjusted optimization model for thermal sensors is proposed.•Designed scheme keeps high performance, confirmed by experiments.•This method has strong portability, applying many structures.•Such a scheme greatly simplifies engineering preparation.
Metamaterial-based devices have been extensively researched on account of their novel functions, such as cloaking, concentrating, rotating, and sensing. However, they are usually achieved by employing metamaterials with extreme parameters, critically restricting engineering preparation. To simplify parametric designs, we propose an optimization model with particle swarm algorithms to realize bilayer thermal sensors composed of bulk isotropic materials (circular structure). For this purpose, the fitness function is defined to evaluate the difference between the actual and expected temperatures. By choosing suitable materials for different regions and treating the radii of sensor, inner shell, and outer shell as design variables, we finally minimize the fitness function via particle swarm optimization. The designed scheme is not only easy to implement in applications, but shows excellent performances in both detective accuracy and thermal invisibility, which are well confirmed by finite-element simulations and laboratory experiments. Optimization model can also be flexibly extended to a square case. This method can not only calculate numerical solutions for difficult analytical theories (circular structure), but also calculate optimal solutions for problems without analytical theories (square structure), providing new inspiration for simplifying the design of metamaterials in a wide range of communities. |
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| AbstractList | •A size-adjusted optimization model for thermal sensors is proposed.•Designed scheme keeps high performance, confirmed by experiments.•This method has strong portability, applying many structures.•Such a scheme greatly simplifies engineering preparation.
Metamaterial-based devices have been extensively researched on account of their novel functions, such as cloaking, concentrating, rotating, and sensing. However, they are usually achieved by employing metamaterials with extreme parameters, critically restricting engineering preparation. To simplify parametric designs, we propose an optimization model with particle swarm algorithms to realize bilayer thermal sensors composed of bulk isotropic materials (circular structure). For this purpose, the fitness function is defined to evaluate the difference between the actual and expected temperatures. By choosing suitable materials for different regions and treating the radii of sensor, inner shell, and outer shell as design variables, we finally minimize the fitness function via particle swarm optimization. The designed scheme is not only easy to implement in applications, but shows excellent performances in both detective accuracy and thermal invisibility, which are well confirmed by finite-element simulations and laboratory experiments. Optimization model can also be flexibly extended to a square case. This method can not only calculate numerical solutions for difficult analytical theories (circular structure), but also calculate optimal solutions for problems without analytical theories (square structure), providing new inspiration for simplifying the design of metamaterials in a wide range of communities. Metamaterial-based devices have been extensively researched on account of their novel functions, such as cloaking, concentrating, rotating, and sensing. However, they are usually achieved by employing metamaterials with extreme parameters, critically restricting engineering preparation. To simplify parametric designs, we propose an optimization model with particle swarm algorithms to realize bilayer thermal sensors composed of bulk isotropic materials (circular structure). For this purpose, the fitness function is defined to evaluate the difference between the actual and expected temperatures. By choosing suitable materials for different regions and treating the radii of sensor, inner shell, and outer shell as design variables, we finally minimize the fitness function via particle swarm optimization. The designed scheme is not only easy to implement in applications, but shows excellent performances in both detective accuracy and thermal invisibility, which are well confirmed by finite-element simulations and laboratory experiments. Optimization model can also be flexibly extended to a square case. This method can not only calculate numerical solutions for difficult analytical theories (circular structure), but also calculate optimal solutions for problems without analytical theories (square structure), providing new inspiration for simplifying the design of metamaterials in a wide range of communities. |
| ArticleNumber | 121177 |
| Author | Dai, Gaole Xu, Liujun Ouyang, Xiaoping Yang, Shuai Huang, Jiping Jin, Peng |
| Author_xml | – sequence: 1 givenname: Peng orcidid: 0000-0002-4440-5240 surname: Jin fullname: Jin, Peng email: 19110190022@fudan.edu.cn organization: Department of Physics, State Key Laboratory of Surface Physics, and Key Laboratory of Micro and Nano Photonic Structures (MOE), Fudan University, Shanghai 200438, China – sequence: 2 givenname: Shuai surname: Yang fullname: Yang, Shuai organization: Department of Physics, State Key Laboratory of Surface Physics, and Key Laboratory of Micro and Nano Photonic Structures (MOE), Fudan University, Shanghai 200438, China – sequence: 3 givenname: Liujun surname: Xu fullname: Xu, Liujun organization: Department of Physics, State Key Laboratory of Surface Physics, and Key Laboratory of Micro and Nano Photonic Structures (MOE), Fudan University, Shanghai 200438, China – sequence: 4 givenname: Gaole surname: Dai fullname: Dai, Gaole organization: School of Sciences, Nantong University, Nantong 226019, China – sequence: 5 givenname: Jiping surname: Huang fullname: Huang, Jiping email: jphuang@fudan.edu.cn organization: Department of Physics, State Key Laboratory of Surface Physics, and Key Laboratory of Micro and Nano Photonic Structures (MOE), Fudan University, Shanghai 200438, China – sequence: 6 givenname: Xiaoping surname: Ouyang fullname: Ouyang, Xiaoping email: oyxp2003@aliyun.com organization: School of Materials Science and Engineering, Xiangtan University, Xiangtan 411105, China |
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| Snippet | •A size-adjusted optimization model for thermal sensors is proposed.•Designed scheme keeps high performance, confirmed by experiments.•This method has strong... Metamaterial-based devices have been extensively researched on account of their novel functions, such as cloaking, concentrating, rotating, and sensing.... |
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| SubjectTerms | Algorithms Design Fitness Isotropic material Metamaterials Optimization Particle swarm algorithm Particle swarm optimization Sensors Simplified engineering preparation Thermal sensor Visibility |
| Title | Particle swarm optimization for realizing bilayer thermal sensors with bulk isotropic materials |
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