Study of a magnetic SMA-based energy harvester using a corrugated structure

Safari, Omid; Zakerzadeh, Mohammad Reza; Baghani, Mostafa

doi:10.1177/1045389x20983903

Cited by 3 publications

(1 citation statement)

References 32 publications

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“…This model should possess the capacity to predict the behavior of MSMA under diverse magnetic-mechanical loading conditions. While Safari et al [11] proposed a mathematically based model rooted in thermodynamics, it falls short in complying with all thermodynamic laws. To achieve more precise predictions of system output, a machine learning-based modeling approach was introduced [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Designing and modeling of a new MSMA vibration energy transducer

Luping,

Jing,

Yunhong

2024

J. vibroeng.

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The conversion of mechanical vibrational energy into electrical energy to power wireless electronic devices using the smart material magnetic shape memory alloy (MSMA) has garnered substantial attention. This paper presents a vibration energy transducer founded on the inverse effect of MSMA, elucidating the principle of power generation. The variations in martensite and magnetic domain characteristics within MSMA were analyzed, and a constitutive model was established for the MSMA vibration energy transducer, integrating the thermodynamic theory of the Gibbs free energy function. Although this model performs well in predicting experimental outcomes, it falls short in capturing all features of the experimental data. To comprehensively encompass these features, the PSO-XGBoost machine learning approach was introduced to train the experimental data by incorporating factors such as stress, magnetic field, and induced voltage. An experimental prototype of the MSMA vibration energy transducer is fabricated, and the predictions of both models are compared with the collected experimental data, validating the accuracy of the model and indicating the enhanced effectiveness of machine learning methods in prediction. This research not only validates the correctness of the models but also emphasizes the potential for more precise predictions using machine learning methods, thereby establishing a robust foundation for the thorough study and broader application of MSMA vibration energy transducers.

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Section: Introductionmentioning

confidence: 99%

Designing and modeling of a new MSMA vibration energy transducer

Luping,

Jing,

Yunhong

2024

J. vibroeng.

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Investigating the Behavior of Composite Shear Walls with Corrugated Shape Memory Alloys Plate and Steel Fiber Concrete under Cyclic Loading

Barhagh

Aghabarati

2022

Iran J Sci Technol Trans Civ Eng

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Nonlinear Dynamics of a Magnetic Shape Memory Alloy Oscillator

Souza,

Monteiro,

Savi

2024

Journal of Computational and Nonlinear Dynamics

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Magnetic shape memory alloys (MSMAs) constitute a class of smart materials capable of exhibiting large magnetic field induced strain (MFIS) when subjected to magnetomechanical loadings. Two distinct mechanisms are responsible for the induced strain: martensitic variant reorientation and phase transformation. The martensitic reorientation is the most explored mechanism presenting the advantage to potential provide high-frequency actuation since it does not rely on phase transformation cycles. Despite its capabilities and potential dynamical applications, the dynamical behavior of MSMAs is not extensively explored in the literature that is usually focused on quasi-static behavior. Thereby, the objective of this work is to analyze the nonlinear dynamics of MSMAs. In this regard, an MSMA nonlinear oscillator is investigated, exploiting the system response under different bias magnetic field levels and actuation frequencies. A phenomenological model is employed to describe the MSMA magnetomechanical behavior. Numerical simulations are carried out using the operator split technique together with an iterative process and the fourth-order Runge–Kutta method. Results show that the application of a bias magnetic field can reduce the mean displacement of the system, increasing the oscillation amplitude. Furthermore, the period of oscillation can be modified, even achieving complex behaviors, including chaos. The potential use of MSMAs to dynamical systems is explored showing the possibility to provide adaptive behaviors.

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Study of a magnetic SMA-based energy harvester using a corrugated structure

Cited by 3 publications

References 32 publications

Designing and modeling of a new MSMA vibration energy transducer

Designing and modeling of a new MSMA vibration energy transducer

Investigating the Behavior of Composite Shear Walls with Corrugated Shape Memory Alloys Plate and Steel Fiber Concrete under Cyclic Loading

Nonlinear Dynamics of a Magnetic Shape Memory Alloy Oscillator

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