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Record W2119177140 · doi:10.1139/l08-097

Polynomial correction function for half-power bandwidth (HPB) method of damping of glulam beams reinforced with e-glass reinforced epoxy polymer (GRP)

2009· article· en· W2119177140 on OpenAlexaffvenue
Morteza Naghipour, Morteza Mehrzadi, Farid Taheri‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Guang Ping Zou

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2009
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMaterials scienceEpoxyVibrationHammerStructural engineeringFrequency domainComposite materialPolynomialLogarithmic decrementMathematicsAcousticsMathematical analysisPhysicsEngineering

Abstract

fetched live from OpenAlex

Analytical and experimental investigation into dynamic properties of glued–laminated (glulam) beams reinforced with various lay ups of e-glass reinforced epoxy polymer (GRP) composites are discussed. Three unreinforced glulam (control) beams and 11 glulam beams reinforced with GRP on their bottom surface were clamped in a cantilever condition and tested using an instrumental hammer. The natural frequencies of all beams determined by the impact dynamic (hammer) method using power spectral density (PSD) were used to estimate damping ratio of all the beams through both time domain and frequency domain methods. In the time domain analysis, the method of logarithmic decrement analysis (LDA) and the Hilbert transform analysis (HTA) were considered; in the frequency domain analysis, both moving block analysis (MBA) and half-power bandwidth (HPB) were applied to the data and a new approach HPB method with a polynomial correction function was numerically established. A comparison between the results obtained from all the methods of analysis and a new approach shows that this method may improve the accuracy of the HPB method in evaluation of vibration damping properties of glulam reinforced composite beams because glulam beams have high level damping ratios and that this method should be modified especially when used with materials having high level damping ratios.

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)0.001
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: none
Teacher disagreement score0.704
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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

Citations7
Published2009
Admission routes2
Has abstractyes

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