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Record W831787892 · doi:10.1520/stp13429s

An Indirect Technique for Determining Closure-Free Fatigue Crack Growth Behavior

2000· book-chapter· en· W831787892 on OpenAlexaff
SW Smith, RS Piascik

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsClosure (psychology)Crack closureMaterials scienceParis' lawStructural engineeringMechanicsComposite materialEngineeringEconomicsFracture mechanicsPhysicsMarket economy

Abstract

fetched live from OpenAlex

The effects of stress ratio (R) and maximum applied stress-intensity factor (Kmax) on fatigue crack growth rate (da/dN) have been investigated. Fatigue crack growth behavior was analyzed by plotting applied cyclic stress-intensity factor (ΔK) versus applied Kmax for an α+β titanium alloy (Ti 6-2-2-2-2) at several values of da/dN. This analysis revealed two distinct regions of fatigue crack growth behavior. At threshold da/dN (≈ 10-10 m/cycle) and for Kmax < 4.6 MPa√m the threshold cyclic stress-intensity factor (ΔKth) is greatly influenced by crack closure. For closure free fatigue crack growth (Kmax > 4.6 MPa√m), a subtle but distinct decrease in ΔKth is observed with increasing Kmax. Plots of ΔK versus Kmax were also generated for AA 2024 test data produced in two different studies. These data also revealed two distinct regions of fatigue crack growth behavior consistent with the Ti 6-2-2-2-2 results. This methodology can be used to determine closure free fatigue crack growth and to monitor subtle changes in ΔKth.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.005

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 head0.027
GPT teacher head0.245
Teacher spread0.218 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations26
Published2000
Admission routes1
Has abstractyes

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