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Record W4391615428 · doi:10.18260/1-2--42345

3D-Printed Piezoelectric Acoustic Energy Harvester

2024· article· en· W4391615428 on OpenAlexfundno aff
Michael Palmateer, Jacob Plesums, Ryan Santiago, Austin J. Miller, Reza Rashidi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsPiezoelectricityAcousticsEnergy harvestingEnergy (signal processing)Computer science3d printedMaterials scienceEngineeringPhysicsManufacturing engineering

Abstract

fetched live from OpenAlex

Energy harvesting has been widely researched in the past decade due to its significant usage for providing energy to remote areas and electronic devices. Harvesting energy from piezoelectric beams is one of the popular forms of energy conversion, enabling a wide range of applications. A team of four senior undergraduate students in a microfabrication course completed a project to develop a piezoelectric-based acoustic energy harvester. The students performed all development steps, including ideation, literature review, calculation, design, fabrication, assembly, testing, and writing. This paper investigates the plausibility of maximizing the generation of acoustically harvested energy by combining multiple generally known methods for harvesting acoustic energy from sound waves. One such method is using a Helmholtz resonator, a spherical device with one opening, which can create a region of considerable pressure variation when sound waves are directed inside. Another method for acoustic energy harvesting is utilizing the principles of resonance and antinodes in a cylindrical tube. Antinodes are areas of high sound pressure created by standing sound waves resonating through a cylindrical tube at specific frequencies. Our design combines these methods by placing a Helmholtz resonator at the closed end of a cylindrical tube to harvest energy from all areas of high pressure due to resonance; located at the antinodes along the cylinder. The open end of the cylinder expands outward in a parabolic fashion to increase the surface area for capturing as many incident sound waves as possible and directing them into the device. The acoustic energy harvester is fabricated using a three-dimensional (3D) print of the solid model constructed of PLA, a thermoplastic polyester. The device was tested using a speaker projecting known frequencies in the range of optimal frequencies of 600-2500Hz and a data acquisition card (DAQ) measuring voltages for each 100Hz increment. It was determined that the waveform amplitude of 12.13mV produced at 2300Hz was the highest compared to the ones taken at lower frequencies. This evidence proved that the device is more effective at higher frequencies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.210
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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