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Record W2515139329 · doi:10.1115/1.4034509

A Physics-Based Model for Metal Matrix Composites Deformation During Machining: A Modified Constitutive Equation

2016· article· en· W2515139329 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.

Bibliographic record

VenueJournal of Engineering Materials and Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsConstitutive equationMachiningMaterials scienceVolume fractionDeformation (meteorology)Particle (ecology)Work (physics)Matrix (chemical analysis)Composite materialMechanicsFinite element methodStructural engineeringMechanical engineeringEngineeringPhysicsMetallurgy

Abstract

fetched live from OpenAlex

One of the main challenges encountered in modeling the behavior of metal matrix composites (MMCs) during machining is the availability of a suitable constitutive equation. Currently, the Johnson–Cook (J–C) constitutive equation is being used, even though it was developed for homogeneous materials. In such a case, an equivalent set of homogeneous parameters is used, which is only suitable for a particular combination of particle size and volume fraction. The current work presents a modified form of the J–C constitutive equation that suits MMCs, and explicitly accounts for the effects of particle size and volume fraction, as controlled parameters. Also, an energy-based force model is presented, which considers particle cracking and debonding based on the principles of fracture mechanics. In order to validate the new approach, cutting forces were predicted and compared to experimental results, where a good agreement was found. In addition, the predicted forces were compared to other analytical models available in the literature.

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 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 score0.408
Threshold uncertainty score0.439

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 head0.014
GPT teacher head0.208
Teacher spread0.194 · 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