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Record W1998974706 · doi:10.1137/070695940

A Multiscale Model of First and Second Order Phase Transformations with Application to SMA Single Crystals

2008· article· en· W1998974706 on OpenAlexaff
Vesselin Stoilov

Bibliographic record

VenueMultiscale Modeling and Simulation · 2008
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsHelmholtz free energyShape-memory alloyPhase transitionInternal energyNickel titaniumContext (archaeology)Statistical physicsClassical mechanicsPhysicsMaterials scienceMechanicsThermodynamics

Abstract

fetched live from OpenAlex

This work aims to connect an atomistic model with continuum theory of phase transformations in shape memory alloys (SMAs). A formulation of the Helmholtz free energy potential based on Einstein potential has been developed. The atomic potential was used to describe the interatomic interactions in a biatomic crystal of NiTi. The microscopic expressions of the instantaneous mechanical (continuum) variables of mass, momentum, internal energy, and temperature have been derived in terms of the atomic variables. The developed Helmholtz thermodynamic potential is used in the context of the sharp phase front-based continuum framework proposed by Stoilov and Bhattacharyya [Acta Mater., 50 (2002), pp. 4939–4952] to study the micro-macro transition during the thermomechanical response of NiTi crystals. The developed model has been successfully used to predict the response of a one-dimensional single crystal system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.272
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2008
Admission routes1
Has abstractyes

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