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Record W2064214744 · doi:10.1115/ipc2010-31385

Toughness Considerations for Strain-Based Design

2010· article· en· W2064214744 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
TopicStructural Integrity and Reliability Analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsToughnessSimilitudeScale (ratio)Pipeline (software)Pipeline transportRangingComputer scienceStructural engineeringMechanical engineeringMaterials scienceForensic engineeringEngineeringComposite materialArtificial intelligence

Abstract

fetched live from OpenAlex

Toughness is a critical parameter in all phases of a pipeline service life. There are a variety of toughness testing forms, ranging from relatively inexpensive small-scale laboratory specimens to highly sophisticated full-scale tests. The correlation of physically significant parameters, such as transition temperature and upper shelf energy/toughness, from those test forms is examined. The ultimate objective is to understand of the similitude of various specimen forms. The similitude allows the prediction of large-scale behavior from small-scale laboratory test specimens. The paper presents data developed from various current and past research programs. The trends exhibited by the various forms of specimens are examined. The implications of those trends in the strain-based design of pipelines are summarized at the end of the paper.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.032
GPT teacher head0.252
Teacher spread0.220 · 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