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Record W1999172776 · doi:10.1109/tmech.2015.2395437

Regenerative Shock Absorber Using a Two-Leg Motion Conversion Mechanism

2015· article· en· W1999172776 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2015
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsShock absorberDamperMechanism (biology)Control theory (sociology)Shock (circulatory)ExcitationSuspension (topology)Mechanical engineeringMaterials scienceAcousticsPhysicsMechanicsComputer scienceEngineeringStructural engineeringElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents the development of a novel regenerative shock absorber sized for a passenger car suspension system. The shock absorber includes a simple and highly efficient motion converter called a two-leg mechanism , a planetary gearhead, and a brushless three-phase rotary machine. The design and analysis of the regenerative shock absorber are presented by considering the dynamics and efficiency of the electromechanical device. The performance of the regenerative damper is evaluated under sinusoidal excitation inputs for typical amplitudes and frequencies in a vehicular suspension system. Experimental results show that a damping coefficient of $1720$ N$\cdot$s/m can be achieved by controlling the external loads. Furthermore, a mechanical energy conversion efficiency between 0.71 and 0.84 is achieved, which is considerably higher than other mechanisms reported in the literature, such as ball screw, rack-and-pinion, and linear mechanisms.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.924
Threshold uncertainty score1.000

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 head0.032
GPT teacher head0.241
Teacher spread0.208 · 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