MétaCan
Menu
Back to cohort
Record W2321662756 · doi:10.1139/cjce-2011-0247

Traffic-induced vibrations of frame structures

2013· article· en· W2321662756 on OpenAlexvenueno aff
Marija Nefovska-Danilović, Mira Petronijević, Branko Šavija

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsVibrationStructural engineeringFrame (networking)Computer simulationFinite element methodEngineeringComputer scienceAcousticsSimulationTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Using the spectral element method (SEM), a 2-D numerical model of multi-storey frame structures has been developed. The model has been used to predict traffic-induced vibrations of two, six, and twelve-story concrete buildings measured along the route of a future metro line in Belgrade, the capital of Serbia. Vibration simulations of the six-storey frame match satisfactorily the measured dynamic response. However, there is a difference between numerical simulation and the actual measurements for the two-storey and twelve-story buildings. The results indicate a great potential of the proposed SEM to simulate ground-induced vibrations of frame buildings. However, more complex structural models should be developed to better replicate actual situations.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.575

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 head0.219
Teacher spread0.207 · 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 designSimulation or modeling
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

Citations4
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicStructural Health Monitoring TechniquesFrench-language works237,207