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Plane-Stress Analysis of the New Stress Tensor Decomposition

2013· article· en· W2042090526 on OpenAlexaff
Mohd Khir Mohd Nor, Rade Vignjević, J. Campbell

Bibliographic record

VenueApplied Mechanics and Materials · 2013
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsImpact
Fundersnot available
KeywordsOrthotropic materialCauchy stress tensorYield surfaceStress (linguistics)Plane stressMaterials scienceYield (engineering)Tensor (intrinsic definition)Plane (geometry)PlasticityStructural engineeringAluminiumDecompositionWork (physics)Composite materialGeometryMathematical analysisMathematicsFinite element methodEngineeringMechanical engineeringChemistry

Abstract

fetched live from OpenAlex

The accuracy and reliability of the new stress tensor decomposition to capture the plasticity behaviour of orthotropic materials under plane-stress conditions was examined in this paper. No experiment was required to perform this work. Therefore, the suitable, published paper which provides a relevant test result and sufficient material properties to characterise the new stress tensor decomposition, was used. This new stress tensor decomposition was used to presents a new yield criterion for orthotropic sheet metals under plane-stress conditions in this work. This was done by assuming the yield surface to be circular in the new deviatoric plane. The predictions of the new effectice stress expression were then compared with the experimental data of 6000 series aluminium alloy sheet (A6XXX-T4) and Al-killed cold-rolled steel sheet SPCE. The predicted new yield surfaces are in good agreement with respect to the experimental data for two materials (A6XXX-T4 and SPCE).

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.213
Teacher spread0.207 · 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 designTheoretical or conceptual
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

Citations9
Published2013
Admission routes1
Has abstractyes

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