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Record W2946649742 · doi:10.1115/1.4043837

Mechanism of Chip Segmentation in Orthogonal Cutting of Zr-Based Bulk Metallic Glass

2019· article· en· W2946649742 on OpenAlex
Naresh Kumar Maroju, Xiaoliang Jin

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

VenueJournal of Manufacturing Science and Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicMetallic Glasses and Amorphous Alloys
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsMaterials scienceAmorphous metalShear (geology)Shear matrixShear stressDeformation (meteorology)Amorphous solidChip formationComposite materialChipStress (linguistics)MetallurgyCrystallographyMachiningTool wearAlloyComputer science

Abstract

fetched live from OpenAlex

Abstract Bulk metallic glasses (BMGs) are a series of metal alloys with an amorphous structure. The deformation of BMGs occurs in localized regions and is highly sensitive to the applied stress, strain rate, and temperature. This paper presents a coupled thermomechanical model to analyze the chip segmentation mechanism due to material shear localization in orthogonal cutting of Zr-BMG. The shear stress variation in the primary shear zone is modeled considering the tool-chip friction and large strain of the material. The constitutive property of BMG corresponding to the inhomogeneous deformation through shear transformation zones is modeled. The oscillations of shear stress, temperature, and free volume are simulated based on the cutting conditions. The predicted chip segmentation frequency is compared with the experimental result under different cutting speeds and uncut chip thicknesses. The developed model provides the fundamental mechanism of material deformation and chip formation in cutting Zr-BMG with an amorphous structure.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.431

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 head0.008
GPT teacher head0.200
Teacher spread0.193 · 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