Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm
Driven by the urgent demand for low-frequency vibration and noise control in engineering scenarios such as automobiles, acoustic metamaterials (AMs), as a new class of functional materials, have demonstrated significant application potential. This paper proposes a low-frequency band gap optimization...
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MDPI AG
2025-07-01
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| author | Jianjiao Deng Yunuo Qin Xi Chen Yanyong He Yu Song Xinpeng Zhang Wenting Ma Shoukui Li Yudong Wu |
| author_facet | Jianjiao Deng Yunuo Qin Xi Chen Yanyong He Yu Song Xinpeng Zhang Wenting Ma Shoukui Li Yudong Wu |
| author_sort | Jianjiao Deng |
| collection | DOAJ |
| description | Driven by the urgent demand for low-frequency vibration and noise control in engineering scenarios such as automobiles, acoustic metamaterials (AMs), as a new class of functional materials, have demonstrated significant application potential. This paper proposes a low-frequency band gap optimization design method for local resonance acoustic metamaterials (LRAMs) based on a multi-objective genetic algorithm. Within a COMSOL Multiphysics 6.2 with MATLAB R2024b co-simulation framework, a parameterized unit cell model of the metamaterial is constructed. The optimization process targets two objectives: minimizing the band gap’s deviation from the target and reducing the structural mass. A multi-objective fitness function is formulated by incorporating the band gap deviation and structural mass constraints, and non-dominated sorting genetic algorithm II (NSGA-II) is employed to perform a global search over the geometric parameters of the resonant unit. The resulting Pareto-optimal solution set achieves a unit cell mass as low as 26.49 g under the constraint that the band gap deviation does not exceed 2 Hz. The results of experimental validation show that the optimized metamaterial configuration reduces the peak of the low-frequency frequency response function (FRF) at 63 Hz by up to 75% in a car door structure. Furthermore, the simulation predictions exhibit good agreement with the experimental measurements, confirming the effectiveness and reliability of the proposed method in engineering applications. The proposed multi-objective optimization framework is highly general and extensible and capable of effectively balancing between the acoustic performance and structural mass, thus providing an efficient engineering solution for low-frequency noise control problems. |
| format | Article |
| id | doaj-art-98437a92398a4dafab0970a01666eb02 |
| institution | DOAJ |
| issn | 2075-1702 |
| language | English |
| publishDate | 2025-07-01 |
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| series | Machines |
| spelling | doaj-art-98437a92398a4dafab0970a01666eb022025-08-20T02:45:37ZengMDPI AGMachines2075-17022025-07-0113761010.3390/machines13070610Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic AlgorithmJianjiao Deng0Yunuo Qin1Xi Chen2Yanyong He3Yu Song4Xinpeng Zhang5Wenting Ma6Shoukui Li7Yudong Wu8State Key Laboratory of Advanced Vehicle Integration and Control, China FAW Group Co., Ltd., Changchun 130013, ChinaCollege of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, ChinaState Key Laboratory of Advanced Vehicle Integration and Control, China FAW Group Co., Ltd., Changchun 130013, ChinaCollege of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, ChinaState Key Laboratory of Advanced Vehicle Integration and Control, China FAW Group Co., Ltd., Changchun 130013, ChinaState Key Laboratory of Advanced Vehicle Integration and Control, China FAW Group Co., Ltd., Changchun 130013, ChinaState Key Laboratory of Advanced Vehicle Integration and Control, China FAW Group Co., Ltd., Changchun 130013, ChinaState Key Laboratory of Advanced Vehicle Integration and Control, China FAW Group Co., Ltd., Changchun 130013, ChinaCollege of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, ChinaDriven by the urgent demand for low-frequency vibration and noise control in engineering scenarios such as automobiles, acoustic metamaterials (AMs), as a new class of functional materials, have demonstrated significant application potential. This paper proposes a low-frequency band gap optimization design method for local resonance acoustic metamaterials (LRAMs) based on a multi-objective genetic algorithm. Within a COMSOL Multiphysics 6.2 with MATLAB R2024b co-simulation framework, a parameterized unit cell model of the metamaterial is constructed. The optimization process targets two objectives: minimizing the band gap’s deviation from the target and reducing the structural mass. A multi-objective fitness function is formulated by incorporating the band gap deviation and structural mass constraints, and non-dominated sorting genetic algorithm II (NSGA-II) is employed to perform a global search over the geometric parameters of the resonant unit. The resulting Pareto-optimal solution set achieves a unit cell mass as low as 26.49 g under the constraint that the band gap deviation does not exceed 2 Hz. The results of experimental validation show that the optimized metamaterial configuration reduces the peak of the low-frequency frequency response function (FRF) at 63 Hz by up to 75% in a car door structure. Furthermore, the simulation predictions exhibit good agreement with the experimental measurements, confirming the effectiveness and reliability of the proposed method in engineering applications. The proposed multi-objective optimization framework is highly general and extensible and capable of effectively balancing between the acoustic performance and structural mass, thus providing an efficient engineering solution for low-frequency noise control problems.https://www.mdpi.com/2075-1702/13/7/610acoustic metamaterialslocal resonancenon-dominated sorting genetic algorithm II (NSGA-II)COMSOL with MATLAB co-simulationnoise, vibration and harshness (NVH) |
| spellingShingle | Jianjiao Deng Yunuo Qin Xi Chen Yanyong He Yu Song Xinpeng Zhang Wenting Ma Shoukui Li Yudong Wu Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm Machines acoustic metamaterials local resonance non-dominated sorting genetic algorithm II (NSGA-II) COMSOL with MATLAB co-simulation noise, vibration and harshness (NVH) |
| title | Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm |
| title_full | Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm |
| title_fullStr | Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm |
| title_full_unstemmed | Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm |
| title_short | Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm |
| title_sort | multi objective optimization design of low frequency band gap for local resonance acoustic metamaterials based on genetic algorithm |
| topic | acoustic metamaterials local resonance non-dominated sorting genetic algorithm II (NSGA-II) COMSOL with MATLAB co-simulation noise, vibration and harshness (NVH) |
| url | https://www.mdpi.com/2075-1702/13/7/610 |
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