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Record W2802246902 · doi:10.1139/tcsme-2008-0015

EXPERIMENTAL INVESTIGATION OF THE PROPERTIES OF A NOVEL COMPLIANT AIR BEARING MATERIAL HANDLING SYSTEM

2008· article· en· W2802246902 on OpenAlexaffvenue
Joon Chung, Bryan Townsend, Luke Stras, L. Lee, P. A. Sullivan

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2008
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsUniversity of TorontoToronto Metropolitan University
Fundersnot available
KeywordsNozzleLoad bearingBearing (navigation)Air bearingStructural engineeringComputer scienceMechanical engineeringMaterials scienceEngineering

Abstract

fetched live from OpenAlex

An air bearing materials handling system supports its load on two compliant runners having the form of oval cylinders moving along shallow concave rails. Air is supplied by manifolds integral with the rails through nozzles spaced at intervals in the rail surface. Loads up to 3 tonnes can be moved with an effective coefficient of sliding friction of about 1%. Developed by trial-and-error, the system has incompletely understood features. Two are: the role of the system geometry in providing load support; and the construction of the runners, which consist of layers of cellulose fibre tissue wound onto a core, and enclosed in a plastic cover. Exploratory research aimed at establishing the effect of these features on the load fraction supported by air pressure is reviewed. Flat surface equivalents instrumented for pressure surveys are developed to assess the role of the tissue, and to suggest alternatives. The load fraction is determined, and the response to asymmetric loading is investigated. The minimum number of tissue layers necessary for bearing action is identified, and the performance of compliant alternatives is explored. The review concludes with a discussion of the elements required of a mathematical model suitable for guiding design improvement.

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 score0.009
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 head0.033
GPT teacher head0.209
Teacher spread0.176 · 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

Citations0
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicTendon Structure and TreatmentFrench-language works237,207