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Record W918572244 · doi:10.1520/stp38269s

Modeling Abrasive Wear of Homogeneous and Heterogeneous Materials

2001· book-chapter· en· W918572244 on OpenAlexaff
Khaled Elalem, Li Dy, M.J. Anderson, S. Chiovelli

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMaterials Science
TopicMetal Alloys Wear and Properties
Canadian institutionsSyncrude (Canada)University of Alberta
Fundersnot available
KeywordsAbrasiveHomogeneousMaterials scienceComposite materialMetallurgyPhysicsThermodynamics

Abstract

fetched live from OpenAlex

A micro-scale dynamic approach was recently proposed to simulate wear of materials. The model was developed based on fundamental physical laws without employing empirical equations or tribological rules. In this model, a material system is discretized and represented using a discrete lattice. Each lattice site represents a small volume of the material. During wear, a lattice site may move under the influence of external force and the interaction between the site and its adjacent sites, which depends on the mechanical properties of the material, such as the elastic modulus, yield strength and work-hardening. The movement and trajectory of lattice sites during wear were determined using Newton's law of motion. A bond can be broken when the total accumulated plastic strain exceeds the fracture strain. A site or a cluster of sites is worn away if all bonds connecting the site or the cluster to its neighbors are broken. The model can provide information on the strain distribution in a contact region, consistent with finite element analysis. This model was applied to single-phase and composite materials abraded under dry sand/rubber wheel abrasion testing condition. Good agreement between the modeling and experiments was found.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.135
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0110.000

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 head0.032
GPT teacher head0.223
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
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

Citations12
Published2001
Admission routes1
Has abstractyes

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