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Record W4399995702 · doi:10.18540/jcecvl10iss5pp19085

Predictive response to the behaviour of old structures using ambient vibrations

2024· article· en· W4399995702 on OpenAlexaff
Zoubida Maraf, Mounir Naili, Mohamed Bensoula, Abderrahmane Kibboua, Hanifi Missoum

Bibliographic record

VenueThe Journal of Engineering and Exact Sciences · 2024
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsLaurentian University
Fundersnot available
KeywordsModalAmbient vibrationVibrationStiffnessModal analysisStructural engineeringSeismic noiseNormal modeFrequency responseAcousticsMaterials scienceGeologyEngineeringPhysicsComposite material

Abstract

fetched live from OpenAlex

The response of ancient structures such as the Saint-Jean-Baptiste church or the current El-Badr mosque in Mostaganem (Algeria) to earthquakes depends on these physical characteristics and consequently on modal properties such as frequencies, damping and modal deformations. In this paper, ambient vibration tests were carried out on the three parts of the mosque building, and the response spectra and damping obtained will be correlated with the mechanical tests carried out in the second part of the work. Determination of the dynamic characteristics made it possible to distinguish differences in stiffness and to clearly highlight a disparity in frequencies in each structure, which may correspond to the age of each part of the building, the design and construction and differences in levels, etc. The results of the destructive tests give indications that confirm the hypotheses of ageing of the materials. The low young modulus of the various components partly confirms the frequency and damping values obtained. The experimental study of the mosque using ambient vibrations will give an order of magnitude of the vibratory mode periods, which are the first steps in any modelling, reinforcement and/or verification strategy and constitute a health record for this type of heritage.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.136

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.011
GPT teacher head0.236
Teacher spread0.225 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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