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Record W1969514645 · doi:10.1115/pvp2007-26784

Stress Categorization Using the Reference Two-Bar Structure

2007· article· en· W1969514645 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Structural Analysis Methods
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPipingFinite element methodPressure vesselBar (unit)Structural engineeringCategorizationLinear elasticityComputer scienceStress (linguistics)Engineering drawingEngineeringMechanical engineeringArtificial intelligenceGeology

Abstract

fetched live from OpenAlex

The ASME Boiler and Pressure Vessel Codes and Standards used for designing pressure vessel and piping provide guidelines to classify the linear elastic stresses into primary, secondary and peak categories. Although these guidelines cover a wide range of pressure components, they are sometimes difficult to apply to the three-dimensional components with complex loading and geometries. The concept of “reference two-bar structure” is used in this paper to categorize the stresses in pressure components and structures, using linear elastic finite element analyses. The method is applied to a number of components and structures from simple to relatively complex geometric configurations. The results compare well with those obtained from commercial finite element codes.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.356

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 head0.019
GPT teacher head0.285
Teacher spread0.267 · 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

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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