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Record W36588403 · doi:10.1002/ajh.26803

Modeling, mathematical simulation and non-linear analysis of magnetorheological valve damper

2007· article· en· W36588403 on OpenAlexaff
Nima Eslaminasab, Tom Gillespie, M. F. Golnaraghi

Bibliographic record

Venueinternational conference on Modelling and simulation · 2007
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsUniversity of Waterloo
FundersKræftens Bekæmpelse
KeywordsMagnetorheological fluidDamperClassification of discontinuitiesMagnetorheological damperComputer scienceControl theory (sociology)Control engineeringEngineeringMathematicsControl (management)Artificial intelligenceMathematical analysis

Abstract

fetched live from OpenAlex

In this paper a newly in-house designed MR piloted valve damper, which will be defined briefly in the next sections, is modeled and analyzed. Due to the complex and highly non-linear characteristics of the system, especially frequent discontinuities in the system, different assumptions and simplifications have been made to enable the modeling and analysis of the system. Approximate method, namely averaging method, has been also adopted to analyse the system. A brief technological review is also presented to give a background on the driving forces behind the selection and innovations in MR damper analysis. Finally the results of approximate method of averaging and numerical simulations are compared.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.058
GPT teacher head0.311
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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
Published2007
Admission routes1
Has abstractyes

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