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Record W3025332748 · doi:10.1080/17436753.2020.1765292

Cutting performances of TiCN–HfC and TiCN–HfC–WC ceramic tools in dry turning hardened AISI H13

2020· article· en· W3025332748 on OpenAlex

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

VenueAdvances in Applied Ceramics Structural Functional and Bioceramics · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsUniversity of Alberta
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMaterials scienceMetallurgyAbrasiveCeramicRake angleFlankRakeAdhesive wearWear resistanceMachiningEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Cutting performances of TiCN–HfC (TH) and TiCN–HfC–WC (THW) ceramic tools in dry turning hardened AISI H13 was investigated. The optimal cutting parameters – cutting speed of 110 m/min, feed rate of 0.1 mm/rev and depth of cut of 0.15 mm – were obtained by the orthogonal experiment. At the optimal cutting parameters, the tool life of TH was 82 min higher than that of THW, which indicated that TH had better wear resistance than THW. Meanwhile, the workpiece had better surface quality after turned by TH than by THW. In addition, a crescent depression formed in the rake face and a jackboot-like shape appeared in the flank. The rake face took place crater wear, while the flank took place abrasive wear, oxidation wear and adhesive wear.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.220
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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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