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Record W7162087986 · doi:10.82308/25203

Condition assessment of concrete bridge girders using modal testing - a preliminary study

2009· dissertation· en· W7162087986 on OpenAlexaboutno aff
Nirajkumar Chalishajar

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsnot available
Fundersnot available
KeywordsGirderModalModal testingVibrationNatural frequencyStiffnessCrackingBridge (graph theory)Modal analysis

Abstract

fetched live from OpenAlex

This thesis deals with vibration frequency evaluation using non-destructive modal testing of beam-type structures. The current state of Canada's bridges is reviewed for its present condition and urgent needs. The basic modes of deterioration in concrete bridges, namely, corrosion of reinforcing steel and freezing and thawing cycles were also reviewed. Bridge inspection fundamentals are discussed summarily. In addition, a summary of the available research on modal testing is presented. Five reinforced concrete beams were tested in this preliminary research program to study the effect of progressive cracking at increasing load levels on the changes in their natural frequencies. Analysis of the results shows that the natural frequency is related to the changes in the structural stiffness of the beam, and the level of damage. The results from this preliminary investigation show that vibration testing is a useful tool for studying the existing health of a structural system.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.326
Teacher spread0.289 · 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 designObservational
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
Published2009
Admission routes1
Has abstractyes

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