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Record W4416041219 · doi:10.1016/j.jsv.2025.119537

Vibration suppression performance of tunable parallel asymmetric nonlinear energy sinks with distinct stability characteristics under impulse excitation

2025· article· en· W4416041219 on OpenAlexaff
Muxuan Guo, Yi Wu, Changzhi Hu, Lihua Tang, Kefu Liu

Bibliographic record

VenueJournal of Sound and Vibration · 2025
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsLakehead University
FundersChina Scholarship Council
KeywordsVibrationNonlinear systemExcitationAsymmetryImpulse (physics)AttenuationMultivibratorMagnetAmplitude

Abstract

fetched live from OpenAlex

• Parallel asymmetric NESs with three repulsive magnets (P-3ARMNESs) are proposed. • Impulse vibration suppression is studied numerically and experimentally. • Key parameters of P-3ARMNESs and counterparts are optimized via genetic algorithm. • P-3ARMNESs show superior performance over counterparts with equal mass. • Initial position and constraint-induced performance factors are discussed. Nonlinear energy sinks (NESs) are promising vibration absorbers known for their unique Targeted Energy Transfer (TET) mechanism and superior performance over linear vibration absorbers (LVAs) in terms of attenuation bandwidth and/or amplitude suppression. However, current research in NES lacks comprehensive studies on asymmetric multistable NES, even though the introduction of asymmetry fundamentally reshapes the potential landscape. Additionally, the limited research on multi-degree-of-freedom NESs has primarily focused on symmetric monostable systems, leaving the advantages of asymmetric parallel configurations largely unexplored. To overcome these challenges, this work explores the vibration attenuation capability of tunable parallel NESs incorporating three asymmetric repulsive magnets (P-3ARMNESs) across different impulse intensities, using theoretical modeling, numerical simulation, parameter tuning, and experimental validation. Taking into account the beam deflection and the tip magnet rotation, a dipole–dipole model is employed to characterize the magnetic force to enable dynamic system modeling for numerical simulation. For fair comparison, critical design parameters of the P-3ARMNESs and additional comparative configurations (single LVA, single symmetric NES (3RMNES), and single asymmetric NES (3ARMNES)) are optimized using genetic algorithm under varying excitation intensities. Numerical simulations and experimental validation reveal that the 3ARMNES outperforms the symmetric 3RMNES, confirming the benefit of asymmetry. Furthermore, maintaining identical equivalent mass, the optimized P-3ARMNESs achieves the best performance, demonstrating the advantage of parallel asymmetric configuration. Simulation and experimental results show that introducing asymmetry weakens the potential barriers of multistable NESs, thereby lowering the threshold for inter-well transitions. Meanwhile, the parallel configuration enriches dynamic responses, and the synergistic interaction of different modes enables efficient TET. These features—frequent inter-well transitions and efficient TET—are key to the superior vibration mitigation performance of the proposed structure. Additionally, the effect of initial positions on NES performance is investigated numerically and experimentally. Factors affecting P-3ARMNESs not addressed in experiments due to physical constraints are also numerically explored. These findings provide valuable insights for designing efficient, tunable parallel asymmetric NESs capable of mitigating impulse responses across a range of excitation amplitudes without increasing mass.

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: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.319

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 communication0.0000.001
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 head0.008
GPT teacher head0.211
Teacher spread0.202 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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