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Record W1968049974 · doi:10.1115/pvp2005-71328

Dynamic Relaxation and New Periodic Symmetry Techniques for Simulating Atomistic Dislocation Models Subjected to Two-Dimensional External Forces

2005· article· en· W1968049974 on OpenAlexaff
Li Pan, Don R. Metzger, M. Niewczas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDislocationSymmetry (geometry)Displacement (psychology)Boundary value problemRelaxation (psychology)Field (mathematics)Periodic boundary conditionsPeierls stressBoundary (topology)Force field (fiction)Classical mechanicsPhysicsMechanicsStatistical physicsDislocation creepCondensed matter physicsMathematical analysisMathematicsGeometry

Abstract

fetched live from OpenAlex

The movement and interactions of dislocations, under the potential energy and the external driving forces, affect the performance of materials in various applications. The Dynamic Relaxation (DR) technique, the Embedded Atom method (EAM) potential function and a newly developed periodic symmetry method are combined and expanded for simulations of the relaxation of atomistic models with dislocation defects subjected to two-dimensional external forces. This paper focuses on solving two challenges in the simulation: (i) it evaluates correct internal forces and corresponding external forces with more complicated periodic boundary in the model and (ii) finds a proper way to revise the displacement field of atoms in the boundary layers to satisfy the requirements of the periodic symmetry in the direction other than the direction of dislocation line. The numerical parameters, such as the choice of damping ratios and the variation of forces in different directions, are studied. The example given, illustrated by behaviour of stress and/or displacement components, deals with and compares the relaxation of a dislocation model under biaxial external forces.

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 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 score0.336
Threshold uncertainty score0.371

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 head0.018
GPT teacher head0.273
Teacher spread0.255 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2005
Admission routes1
Has abstractyes

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