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Record W2093556392 · doi:10.1115/imece2007-42176

Optimal Design of Asymmetric Passive and Semi-Active Dampers

2007· article· en· W2093556392 on OpenAlexaff
Nima Eslaminasab, Siamak Arzanpour, M. F. Golnaraghi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsSimon Fraser UniversityUniversity of Waterloo
Fundersnot available
KeywordsIsolatorTransmissibility (structural dynamics)Control theory (sociology)VibrationTuned mass damperVibration controlVibration isolationDisplacement (psychology)DamperAccelerationOptimal designStructural engineeringStiffnessRoot mean squareDamping torqueComputer scienceEngineeringAcousticsPhysicsElectronic engineering

Abstract

fetched live from OpenAlex

Vibration isolators are essentially used to reduce the magnitude of motion or force transmitted from a vibrating source to vibration recipient bodies. Such recipients might be a foundation, a structure, or even a human’s body. Despite all the advancement in vibration control using active and semi-active systems, passive vibration isolators are still widely used in different industrial applications because of their simplicity and low cost. In this paper we investigate an asymmetric one-degree of freedom vibration isolator. This is very important in practice, because all hydraulic dampers are asymmetric in nature. Due to the non-linearity of this system as a result of asymmetric damping, analytical methods of averaging and numerical simulation are used to analyze its frequency and time response characteristics. Optimal damping and stiffness values for the isolator are obtained by minimizing the cost functions, which are the Root Mean Square (RMS) of the acceleration transmissibility and the relative displacement transmissibility. The effect of the asymmetric damping on the optimal values in passive systems are then analyzed and used to create a design chart for the isolator parameters. In addition, the effect of asymmetry on the conventional semi-active systems is studied and the method to the optimal design of asymmetric semi-active systems is discussed.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.180

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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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

Citations4
Published2007
Admission routes1
Has abstractyes

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