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Record W4386283279 · doi:10.18280/mmep.100406

Experimental and Numerical Study of Sudden Stop Case for Twist Drill Tool and Treated by Lubricant

2023· article· en· W4386283279 on OpenAlexvenueno aff
Abbas Allawi Abbas, Maher Ali Hussein, Tawfeeq Naji Hussein

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2023
Typearticle
Languageen
FieldMaterials Science
TopicMetal Alloys Wear and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsLubricantTwistDrillGeologyComputer scienceMechanical engineeringEngineeringMathematicsGeometry

Abstract

fetched live from OpenAlex

The drilling process using a twist drill tool has high interest in industry, especially in plate metal work.Consequently, during the first penetration through the metal, the sudden stop of the tool at the cutting end or the pulling of the tool from the work piece in the finish can cause crystal nodes to form.This generates torsional torque between the tool and the work piece, which causes torsional shear stress and strain to be translated to the tool root, potentially leading to failure or a dislocated catch region, resulting in hole deformation.So, this paper focuses on how to deal with the increasing stress and strain caused by a sudden stop by using a lubricant liquid that directs flow when a strain gauge attached to the cutting tool detects increasing tool strain.The experimental strain readings in dry conditions and with lubricant liquid are recorded.The Timoshenko equations are used to improve the translation of stress and strain to the tool root and to simulate a torsional case in a cutting tool subjected to torsional torque with the same experimental value (576, 220, 130, 95 N.m.).The results are approximately convergence with a R2 correction factor of 0.9.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.396

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 head0.041
GPT teacher head0.245
Teacher spread0.203 · 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 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
Published2023
Admission routes1
Has abstractyes

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