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Record W1969322606 · doi:10.1115/ipc2012-90565

J-Resistance Results From Multi-Specimen and Single-Specimen Surface Notched SEN(T) Geometry

2012· article· en· W1969322606 on OpenAlexaffabout
Lakshman N. Pussegoda, Sanjay Tiku, Dong-Y. Park, W. R. Tyson, Jim Gianetto

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsSingle specimenMaterials scienceToughnessAxial symmetryComposite materialUltimate tensile strengthEnhanced Data Rates for GSM EvolutionTensile testingStructural engineeringComputer scienceEngineeringGeology

Abstract

fetched live from OpenAlex

In a collaborative program, J-R results were compared from multi-specimen and single-specimen procedures for toughness testing with single-edge notched tensile loaded SEN(T) specimens. Grade 483 MPa (X70) grade pipeline steel was used to prepare surface notched axially loaded specimens. Test procedures followed the multi-specimen method and a single-specimen recommended practice recently developed at the CANMET Materials Technology Laboratory (recently name-changed to CanmetMATERIALS) in a program jointly funded by PERD, PRCI, and DOT. The multi-specimen method adopted side grooves with the objective of comparison with results from the single–specimen method. The specimen geometry was B × B for both test procedures. The target ao/W was about 0.5. The multi-specimen testing was performed at BMT Fleet Technology. The single-specimen testing was performed at the CANMET laboratory, formerly located in Ottawa. The paper describes experimental and analysis details, and compares results from the two techniques, using J expressions developed at CANMET. The results showed similar J-resistance curves at small crack extensions for both techniques, and higher J-resistance values at larger crack extensions for the multi-specimen method. The results are discussed in terms of initial crack length and the analysis methods adopted for the two techniques. Validity criteria according to ASTM E1820 were applied and the results are presented.

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 score0.302
Threshold uncertainty score0.841

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 head0.029
GPT teacher head0.212
Teacher spread0.182 · 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

Citations12
Published2012
Admission routes2
Has abstractyes

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