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Identification of stiffness and periodic excitation forces of a transverse switching crack in a Laval rotor

2012· article· en· W1934474743 on OpenAlex
C. Shravankumar, Rajiv Tiwari

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFatigue & Fracture of Engineering Materials & Structures · 2012
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsExcitationRotor (electric)Transverse planeStiffnessStructural engineeringEccentricity (behavior)Helicopter rotorWork (physics)MechanicsControl theory (sociology)EngineeringPhysicsComputer scienceMechanical engineering

Abstract

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ABSTRACT This work involves model‐based identification of rotor crack. A Laval rotor with a transverse surface crack and disc unbalance is studied. Viscous damping, disc eccentricity and additive stiffness due to crack are the parameters considered for identification. The linear system equations of motion together with the switching crack excitation function are used for developing the identification algorithm. Furthermore, the algorithm is extended for a novel attempt of estimating the coefficients of switching crack excitation function, which constitute the crack excitation force. This estimation could be used to provide valuable information on the actual opening/closing profile of the switching crack. The proposed algorithms are illustrated through numerical examples. They are tested against measurement noise and found to be reasonably robust.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.888

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 head0.012
GPT teacher head0.267
Teacher spread0.255 · 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