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Record W2963079453 · doi:10.1080/17480272.2019.1644371

Dynamic response of guided spline circular saws vs. collared circular saws, subjected to external loads

2019· article· en· W2963079453 on OpenAlexaff
Ahmad Mohammadpanah, Stanley G. Hutton

Bibliographic record

VenueWood Material Science and Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of British ColumbiaFPInnovations
Fundersnot available
KeywordsStructural engineeringSpline (mechanical)Materials scienceAcousticsComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

While collared saws are no longer widely used in North America for primary breakdown of logs to boards, these are common in most of European sawmills. In North America, guided spline circular saws are used for sawing of boards of varying dimensions. This paper presents a stability analysis of spinning disk, an idealized representation of circular saw, for collared and splined arbor saws, when subjected to radial and tangential in-plane forces. The governing linear equations of transverse motion of a spinning disk, subjected to edge-loads, are used in evaluation of the energy transfer from the applied loads to the disk vibrations. This analysis is used to examine the role of critical system components in the development of instability. Unique experimental results of dynamic behavior of both saw types are presented in calculation of critical and flutter instability speeds of the system.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.195
Teacher spread0.190 · 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 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

Citations5
Published2019
Admission routes1
Has abstractyes

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