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Record W3046683786 · doi:10.1088/1361-6463/abab2b

Bandgap merging and widening of elastic metamaterial with heterogeneous resonator

2020· article· en· W3046683786 on OpenAlexaff
Yingli Li, Hao Li

Bibliographic record

VenueJournal of Physics D Applied Physics · 2020
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsMinistry of Education and Child Care
FundersNational Key Research and Development Program of ChinaNatural Science Foundation of Hainan ProvinceState Key Laboratory of High Performance Complex ManufacturingNatural Science Foundation of Hunan Province
KeywordsMetamaterialResonatorBand gapMaterials scienceOpticsOptoelectronicsAcoustic metamaterialsPhysics

Abstract

fetched live from OpenAlex

Abstract Much effort has been devoted to exploring broad bandgap in low frequency with limited mass by various structural designs of elastic metamaterials (EMs). In this paper, a heterogeneous resonator configuration in 1-D dissipative lattice mass system without additional increase of mass and coupling complexity is presented to generate multiple bandgaps. Special attention is focused on the effect of parameters control to merge the multiple bandgaps, and the analytical expression of parameters setting is obtained for broad bandgap merging. Specifically, the merging of all bandgaps in EMs with two heterogeneous resonators achieves 30% lower and 135% wider bandgap than that of classical local resonance (LR) EMs with the same mass ratio and stiffness ratio, while the merging of three LR bandgaps in EMs with three heterogeneous resonators is 20% lower and 63% wider. The relative movements of masses in the unit cell at different frequencies are depicted to reveal the working mechanism. The effect of damping factor on broadening vibration attenuation regime is studied. Finally, the vibration transmission properties of finite system with heterogeneous resonators, mass graded resonators and mass detuning resonators are compared to ensure the broad vibration attenuation range. This work could be beneficial for the design of vibration attenuation application in industry.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.211
Teacher spread0.196 · 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 designBench or experimental
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

Citations23
Published2020
Admission routes1
Has abstractyes

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