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Record W11430680 · doi:10.1136/vr.148.23.707

Mechanical Behavior of Advanced Materials for Aerospace Applications

2003· article· en· W11430680 on OpenAlexaboutno aff
Ignancy Telesman, Peter T. Kantzos, Brian Shannon

Bibliographic record

VenueNASA Technical Reports Server (NASA) · 2003
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceLow-cycle fatigueMemorandumAerospaceUltimate tensile strengthStress (linguistics)Structural engineeringComposite materialForensic engineeringEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

The purpose of this study was to determine whether High Cycle Fatigue (HCF) loading has any deleterious synergistic effect on life when combined with the typical Low Cycle Fatigue (LCF) loading present in engine disks. This interaction is particularly important in the rim region of blisk applications, where fatigue initiations from vibratory stresses (HCF) may be propagated to the disk by LCF. The primary effort in this study was focused on determining and documenting initiation sites and damage mechanisms. Under LCF loading conditions the failures were predominantly surface initiated, while HCF loading favored internal initiations. Deleterious HCF/LCF interactions would always result in a transition from internal to surface initiations. The results indicated that under the relative stress conditions evaluated there was no interaction between HCF and LCF. In FY99 this effort was extended to investigate several other loading conditions (R-ratio effects) as well as interactions between LCF and two-hour tensile dwells. The results will be published as a NASA Technical Memorandum.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.023
GPT teacher head0.304
Teacher spread0.281 · 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
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

Citations0
Published2003
Admission routes1
Has abstractyes

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