An effective approach for topological design to the acoustic–structure interaction systems with infinite acoustic domain

Zhao, Wenchang; Chen, Leilei; Chen, Haibo; Marburg, Steffen

doi:10.1007/s00158-020-02550-2

Cited by 12 publications

(6 citation statements)

References 67 publications

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“…The Kriging surrogate model could design acoustic metamaterials with a specific sound insulation frequency and bandwidth. 75 A similar approach to FEM in acoustic design was utilized by Zhao et al 76 The AI-based design presented a great advantage for sound insulation of a specific frequency range. However, several questions regarding the half-life and durability of AI-based design remain.…”

Section: Emerging Applications Of Ai-based Design In Acoustic Metamat...mentioning

confidence: 99%

AI-Based Metamaterial Design

Tezsezen,

Yigci,

Ahmadpour

et al. 2024

ACS Appl. Mater. Interfaces

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The use of metamaterials in various devices has revolutionized applications in optics, healthcare, acoustics, and power systems. Advancements in these fields demand novel or superior metamaterials that can demonstrate targeted control of electromagnetic, mechanical, and thermal properties of matter. Traditional design systems and methods often require manual manipulations which is time-consuming and resource intensive. The integration of artificial intelligence (AI) in optimizing metamaterial design can be employed to explore variant disciplines and address bottlenecks in design. AI-based metamaterial design can also enable the development of novel metamaterials by optimizing design parameters that cannot be achieved using traditional methods. The application of AI can be leveraged to accelerate the analysis of vast data sets as well as to better utilize limited data sets via generative models. This review covers the transformative impact of AI and AI-based metamaterial design for optics, acoustics, healthcare, and power systems. The current challenges, emerging fields, future directions, and bottlenecks within each domain are discussed.

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Section: Emerging Applications Of Ai-based Design In Acoustic Metamat...mentioning

confidence: 99%

AI-Based Metamaterial Design

Tezsezen,

Yigci,

Ahmadpour

et al. 2024

ACS Appl. Mater. Interfaces

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“…For fuid in NASTRAN, the shear modulus G e � 1 [27]. Using equation (22) and the gradient of u, equation ( 19) yields…”

Section: Fe Equations For Fluid In the Interior Domainmentioning

confidence: 99%

“…Te existing fast BEM [17][18][19][20] uses special iterative solvers to speed up matrix operations and to reduce memory consumption, which remains solving the problem on the structural surface and contains a large number of boundary elements. Besides, the FE-mixed FE-BE coupling method is in the line of using a virtual surface [21,22]. Nevertheless, the existing numerical algorithms do not seem to improve the computational efciency from the perspective of the sound radiation mechanism.…”

Section: Introductionmentioning

confidence: 99%

A Computational Method for Acoustic Interaction with Large Complicated Underwater Structures Based on the Physical Mechanism of Structural Acoustics

Tang

Zhou

Wang

et al. 2022

Advances in Materials Science and Engineering

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A numerical coupling approach is proposed to fast predict the acoustic radiation from a vibrating large-complicated underwater structure. In this study, the physical mechanism of sound radiation from underwater large target is used for the first time to improve the efficiency and keep the accuracy of the numerical algorithm. Although the traditional coupled finite element method/boundary element method (FEM-BEM) is accurate, it contains a large number of boundary elements and thus requires a long computation time for large-complicated structures. The research on the physical mechanism of structural acoustics shows that when BEM is applied on the near-field artificial boundary at a proper distance away from the wet structural surface, large-size boundary elements are acceptable and the number of boundary elements and computation time are remarkably reduced. Thus, the fluid outside the structure is divided into the interior domain and the exterior domain by the artificial boundary. Then, the numerical method is realized by coupling structural finite element modelling with interior fluid finite element modelling and with exterior fluid boundary element modelling. Compared with the theoretical value, the experimental value and the results of the traditional FEM-BEM, the correctness of the proposed algorithm and its advantage of computational efficiency are verified. The computation time of the proposed method is over 99% shorter than that of FEM-BEM in the calculation example of a large-complicated structure. The proposed method can be further applied to multidomain acoustic and multibody acoustic calculations.

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“…Sound absorbing materials [21,22] reduce the noise intensity in the surrounding area by absorbing the acoustic waves radiated/scattered outwards from the structure, but full coverage of these materials applied to the surface of the structure will increase its weight and design cost. Adjusting the distribution of sound absorbing materials through topology optimization design [23][24][25][26] is important to achieve noise control.…”

Section: Introductionmentioning

confidence: 99%

A Subdivision-Based Combined Shape and Topology Optimization in Acoustics

Lu,

Chen,

Luo

et al. 2024

CMES

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We propose a combined shape and topology optimization approach in this research for 3D acoustics by using the isogeometric boundary element method with subdivision surfaces. The existing structural optimization methods mainly contain shape and topology schemes, with the former changing the surface geometric profile of the structure and the latter changing the material distribution topology or hole topology of the structure. In the present acoustic performance optimization, the coordinates of the control points in the subdivision surfaces fine mesh are selected as the shape design parameters of the structure, the artificial density of the sound absorbing material covered on the structure surface is set as the topology design parameter, and the combined topology and shape optimization approach is established through the sound field analysis of the subdivision surfaces boundary element method as a bridge. The topology and shape sensitivities of the approach are calculated using the adjoint variable method, which ensures the efficiency of the optimization. The geometric jaggedness and material distribution discontinuities that appear in the optimization process are overcome to a certain degree by the multiresolution method and solid isotropic material with penalization. Numerical examples are given to validate the effectiveness of the presented optimization approach.

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An effective approach for topological design to the acoustic–structure interaction systems with infinite acoustic domain

Cited by 12 publications

References 67 publications

AI-Based Metamaterial Design

AI-Based Metamaterial Design

A Computational Method for Acoustic Interaction with Large Complicated Underwater Structures Based on the Physical Mechanism of Structural Acoustics

A Subdivision-Based Combined Shape and Topology Optimization in Acoustics

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