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Record W7085085081 · doi:10.20381/ruor-31435

Bond Behaviour of Recycled Coarse Aggregate Concrete Beam-Ends under Monotonic and Cyclic Loading for Seismic Applications

2025· dissertation· en· W7085085081 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Ottawa - Library · 2025
Typedissertation
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsEmbedmentAggregate (composite)MortarMonotonic functionVolume (thermodynamics)Bond strengthCompressive strengthReduction (mathematics)Tension (geology)

Abstract

fetched live from OpenAlex

In pursuit of reducing the carbon footprint and improve the efficiency of the concrete industry, the use of recycled concrete aggregates (RCA) has been proposed and researched as possible solution. However, their reputation has been hampered by the low workability and performance of new RCA concrete mixes. The development of the Equivalent Mortar Volume (EMV) Method in the past decade allowed a better understanding of RCA characteristics and provided way to produce reliable and consistent concrete with properties like those of conventional concrete. This project continues the development path of the EMV Method by studying its influence on the bond behaviour of small-scale structural specimens subjected to cyclic loads to assess the possible use of structural concrete containing RCA in seismic applications. The first stage was dedicated to the development of an EMV mix with a characteristic compressive strength of 35 MPa and a water-to-cement ratio of 0.40. These parameters resulted in a cement mass reduction of 28% and an RCA replacement ratio of 74% when compared to a reference mix without RCA. The second stage of the project focused on 18 beam-end tests with three bar size - embedment length configurations, namely 15M - 170 mm, 15M - 320 mm, and 25M - 320 mm. Half of the specimens were subjected to monotonic loading and the other half to tension cyclic loading. The chosen combinations allowed the study of different failure mechanisms, such as splitting/pullout failure, bar rupture, and splitting failure, respectively. The results of the bond tests indicate the EMV mixes were able to follow the performance of the conventional concrete during the cyclic tests across all combinations, closely matching the failure mechanisms, peak loads, and ultimate displacements; thus, following the same trends observed during previous monotonic studies. It is also proved that the current Canadian provisions for conventional concrete could be potentially applied for RCA concrete made with the EMV Method.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.884

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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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