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Record W3144592256 · doi:10.26682/csjuod.2020.23.2.44

Experimental Determination of Static And Dynamic Elastic Moduli of Rc Slabs

2020· article· en· W3144592256 on OpenAlexfundno aff
Mezgeen Ahmed, Abdulhameed Yaseen, Yaman S. S. Al-Kamaki, Fouad Mohammad

Bibliographic record

VenueThe Journal of The University of Duhok · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsnot available
FundersTrent UniversityNottingham Trent University
KeywordsMaterials scienceSlabStructural engineeringNatural frequencyComposite materialVibrationFrequency domainCompressive strengthAcousticsComputer scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

The purpose of this paper is to experimentally determine the static (Ec) and dynamic (Ed) elastic moduli of reinforced concrete (RC) from both static and dynamic techniques. Initially, the aforementioned parameters were estimated from the concrete compressive strength of the used mix, using compressive strength machine. Subsequently, the RC slab specimens themselves were dynamically tested dynamically under free boundary conditions. Then from, the experimentally measured natural frequency, the static and dynamic moduli were determined. To check the reliability of the dynamic test for estimating the natural frequency, the intact and defected slabs were utilized. The dynamic test was performed on four RC square slab samples of dimensions 600 mm × 600 mm × 40 mm. The first set, two intact slabs, is used as control specimens were prepared with no artificial voids. While, the second set, two defected slabs, is used as defected specimens. The defected slabs contained the artificial void by fixing a polystyrene block at the center of the steel reinforcement of the slabs prior to pouring concrete. In the latter technique, a RC slab specimen is hanged by using elastic ropes to approach fully free boundary conditions. The slabs were excited by an impact hammer, to induce vibration, whilst the accelerometers were employed to record the response under such excitation. Pico Scope 6 device and amplifier was used to acquire, magnify and analyze the data. In addition, MATLAB software is used to convert the time domain to the frequency domain as well as to plot Frequency Response Function (FRF). The first natural frequency is determined as the first resonant peak on the FRF plot. It is showed that the use of the first natural frequency-based method can be usefully employed to determine the dynamic modulus of elasticity of concrete. It was found that the testing sequence did not significantly affect the measured results for the obtained Ec and Ed in this study

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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