MétaCan
Menu
Back to cohort
Record W4411657002 · doi:10.51847/rbrp7is9ti

10.51847/Rbrp7is9tI

2000· article· en· W4411657002 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsnot available
Fundersnot available
KeywordsLoad bearingBearing (navigation)Adaptation (eye)Resistance (ecology)Load resistanceEngineeringStructural engineeringComputer sciencePsychologyArtificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

Engineering design is made functional and durable by applying some engineering considerations such as material selection, availability, formability, besides the geometric shape orientation that is considered in this paper.Many designs especially the world class cars in the automotive industries, aircraft and aerospace technology use shape as basis for designing with consideration for fuel economy and speed.This also is / could be applied in structural engineering and mechanical components for load resistance ability.Geometric shape orientation becomes significant by considering the load resistance ability of the flat or straight beam and a curve beam of the same material -using solid Work 2014 verified with the well-known Hooke's law of elasticity. = is the relation for the investigation.Studies revealed that curve beam has high stiffness, K ,(N/m), than the flat under a point (P) load 1200N.Verification conducted using Ansys Workbench with mild steel, the curve and the flat bars have equivalent Von Mises stress of 1.8799 10 6 and 1.3092 10 7 respectively and total deformation of 9.6896 10 -6 m and 2.2582 10 -7 m respectively.Therefore, besides the consideration for conservation of space, geometric curve orientation should be adapted when designing for a load carrying member in Engineering designs and systems where space is not a constrain.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.894
Threshold uncertainty score0.329

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)0.9850.971

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 head0.008
GPT teacher head0.188
Teacher spread0.181 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueTime to knitSame topicMechanical Engineering and Vibrations ResearchFrench-language works237,207