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Record W2900931479 · doi:10.25071/10315/35246

The Effect Of Minimum Quantity Lubrication On The The Fsw Process Performance

2018· article· en· W2900931479 on OpenAlex
Wisam Al-Wajidi, Ibrahim Deiab, Fantahun M. Defersha

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProgress in Canadian Mechanical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLubricationProcess (computing)Materials scienceProcess engineeringComputer scienceComposite materialEngineeringOperating system

Abstract

fetched live from OpenAlex

The effect of Minimum Quantity Lubrication (MQL) on performance of Friction Stir Welding (FSW) process for Aluminum Alloy 6061-T651 plates was investigated. MQL was used as a cooling and lubrication medium. Five different levels of rotational speed and three feed speed ranges with and without MQL were tested. The effect of MQL on the mechanical properties of the weld joints was studied throughout means of Ultimate Tensile Strength (UTS) tests. Statistical analyses were run to study the relationship between certain process parameters and response. The results showed that the average UTS of the welds is improved when MQL was applied to most of the process variables. The highest UTS was achieved at spindle speed with 1600 rpm and with feed rate 180 mm/min due to improvement of the grain growth.

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.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.005
GPT teacher head0.231
Teacher spread0.226 · 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