Generation of electrical energy from shear stress that exerts a viscoelastic fluid flow on a piezoelectric material to drive power sensors

Abstract This work develops a theoretical study for the harvest of piezoelectrical energy produced by the external action of a viscoelastic fluid through shear stresses. We have selected the Bleustein–Gulyaev waves to characterize the elastic-electrical behavior of the piezoelectric material. The rheological model is presented using two simple rheological behaviors: the Maxwell and Kelvin–Voigt models. In this manner, the dynamic interaction between the flow and the piezoelectric material offers a new conjugate formulation. By imposing the appropriate initial and boundary conditions on the conjugate model, the deformation, voltage, and power generated in the piezoelectric element can easily be found. This increases the energy obtained by up to four times compared with the Newtonian case. It is important to note that a dimensionless analysis is carried out not only to simplify the results but also to show a wide variety of scenarios. Although this scheme strongly depends on the Deborah number and the Womersley number, both have an influence either on the incident frequency of the pressure gradient or on the construction of the device. Considering that a more realistic model is necessary to obtain more accurate results, this first approximation can serve as a starting point to build devices immersed in a rheological environment to feed sensors by transforming the alternating current into direct current with the help of a diode bridge rectifier with an RC filter.

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Publication Details

Journal
Journal of Physics D Applied Physics
Published
2025-07-14
DOI
https://doi.org/10.1088/1361-6463/adef65
Citations
2
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
1.35

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article

Generation of electrical energy from shear stress that exerts a viscoelastic fluid flow on a piezoelectric material to drive power sensors

FEDERICO MÉNDEZ, L Alejandro García-Mora
2 citations
Journal of Physics D Applied Physics
Advanced Sensor and Energy Harvesting Materials
1.35
article

Generation of electrical energy from shear stress that exerts a viscoelastic fluid flow on a piezoelectric material to drive power sensors

FEDERICO MÉNDEZ, L Alejandro García-Mora
article en
2 citations

Abstract

Abstract This work develops a theoretical study for the harvest of piezoelectrical energy produced by the external action of a viscoelastic fluid through shear stresses. We have selected the Bleustein–Gulyaev waves to characterize the elastic-electrical behavior of the piezoelectric material. The rheological model is presented using two simple rheological behaviors: the Maxwell and Kelvin–Voigt models. In this manner, the dynamic interaction between the flow and the piezoelectric material offers a new conjugate formulation. By imposing the appropriate initial and boundary conditions on the conjugate model, the deformation, voltage, and power generated in the piezoelectric element can easily be found. This increases the energy obtained by up to four times compared with the Newtonian case. It is important to note that a dimensionless analysis is carried out not only to simplify the results but also to show a wide variety of scenarios. Although this scheme strongly depends on the Deborah number and the Womersley number, both have an influence either on the incident frequency of the pressure gradient or on the construction of the device. Considering that a more realistic model is necessary to obtain more accurate results, this first approximation can serve as a starting point to build devices immersed in a rheological environment to feed sensors by transforming the alternating current into direct current with the help of a diode bridge rectifier with an RC filter.

Journal of Physics D Applied PhysicsVol. 58(30)
Universidad Nacional Autónoma de México (MX)
Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México
Openalex Percentile: Top 19%
Advanced Sensor and Energy Harvesting Materials
1.35
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