Enhanced passive vibration suppression using self-powered piezoelectric circuitry integration

Wang, Ting; Dupont, Joshua; Tang, Jiong

doi:10.1117/12.2613399

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…The transfer matrix method is employed to establish the dynamic modeling of the entire metamaterial beam. Based on Timoshenko beam theory and 1D constitutive relation, the overall transfer matrix from harmonic input wave to the final transmitted wave can be expressed as [32] The circuit impedance of each identical unit cell can be written as,…”

Section: Theoretical Modelingmentioning

confidence: 99%

“…Particularly, this observation is more remarkable in graded metamaterial cases in which the unit cells are designed to be non-uniform, i.e., the electrical LR of each unit cell is graded for achieving extra wider bandgap for broadband wave attenuation [11]. Based on the modeling of graded metamaterials [32], the transmission ratio results are shown in…”

Section: Local Resonance and Wave Attenuation Operating Frequencymentioning

confidence: 99%

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Local resonance prediction based on physics-informed machine learning in piezoelectric metamaterials

Wang,

Zhou,

Tang

2024

Active and Passive Smart Structures and Integrated Systems XVIII

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Under ideal assumptions of infinite lattices where the infinite wave attenuation intensity is achievable, the bandgap estimation considers the bandgap bounds to achieve broadened band width. However, for practical applications in which finite or limited numbers of unit cells are allowed, the induced bandgap region actually includes frequencies with poor wave attenuation intensity. Therefore, for realizing true wave attenuation applications at targeted operating frequencies, it is of critical importance to locate the operating frequency not only within the bandgap region but also at which the wave attenuation intensity is strongest. To address this issue, we explore a tool for estimating the operating frequency with strong wave attenuation intensity from local resonances of scattering unit cells. Since the implicit correlation between the local resonance and the frequency location of strong wave attenuation intensity is determined by multiple parameters and cannot be analytically expressed by the complicated modeling, we suggest a physics-informed machine leaning approach. By introducing analytical modeling physics into the machine learning models, both the operating frequency and the corresponding achievable strongest wave attenuation intensity can be predicted, which could provide insight into the future design and optimization in the piezoelectrical local resonance metamaterials field.

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Section: Theoretical Modelingmentioning

confidence: 99%

Section: Local Resonance and Wave Attenuation Operating Frequencymentioning

confidence: 99%

Local resonance prediction based on physics-informed machine learning in piezoelectric metamaterials

Wang,

Zhou,

Tang

2024

Active and Passive Smart Structures and Integrated Systems XVIII

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“…It is worth noting that the integration of NC has attracted increasing attention in recent years due to significantly improved vibration control performance [19,20]. In metamaterial synthesis, it has been investigated that NC has promising potential in broadening single bandgap in conventional uniform piezoelectric metamaterials [10].…”

Section: Introductionmentioning

confidence: 99%

Adaptive piezoelectric metamaterials leveraging non-uniform local resonators

Wang¹,

Dupont²,

Tang³

2023

Active and Passive Smart Structures and Integrated Systems XVII

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Metamaterials with locally resonant unit cells based on piezoelectric shunting have led to a new way of realizing elastic/acoustic wave manipulation with online tuning capability. One limitation of uniform locally resonant metamaterials with identical unit cells is their relatively narrow bandgap. Recently, the concept of graded metamaterials with non-uniform local resonators has emerged as a promising approach for improvement. In this research, we explore an adaptive piezoelectric metamaterial-based metamaterial design with spatially varying piezoelectric shunt circuits integrated with negative capacitance. Through systematic parametric analysis, a new design is identified to take advantage of the graded resonant shunt to enhance wave manipulation performance and enlarge the bandgap. Case investigations are presented to demonstrate the feasibility.

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Enhanced passive vibration suppression using self-powered piezoelectric circuitry integration

Cited by 2 publications

References 11 publications

Local resonance prediction based on physics-informed machine learning in piezoelectric metamaterials

Local resonance prediction based on physics-informed machine learning in piezoelectric metamaterials

Adaptive piezoelectric metamaterials leveraging non-uniform local resonators

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