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Record W4409800011 · doi:10.11159/icsect25.172

Characterization of Hydraulic Concrete with Recycled Concrete Aggregates

2025· article· en· W4409800011 on OpenAlexvenueno aff
Julio César López Zerón, J. Zúñiga, Karla Antonia Uclés Brevé

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCharacterization (materials science)Geotechnical engineeringMaterials scienceComputer scienceGeology

Abstract

fetched live from OpenAlex

The rise of urban development has led to an increase in construction projects, resulting in the demolition of existing structures on sites designated for new construction.This demolition process generates construction waste, which becomes an environmental pollutant.In response to this issue, research has been undertaken to find solutions for waste management.One proposed alternative is the reuse of concrete waste as a replacement for natural aggregate materials such as sand and gravel in the production of hydraulic concrete.The treatment of construction waste involves a process that starts with the mechanical crushing of the material to produce smaller fragments.The recycled material is then subjected to laboratory tests to determine properties such as absorption, specific gravity, and bulk density.Test cylinders are prepared by substituting 33% of the natural aggregate with recycled aggregate, followed by tests with 66% recycled aggregate, and finally, 100% recycled aggregate.Additionally, research is conducted on the use of fine recycled aggregates in mortars, developing mortar cubes with the same principle of replacing natural aggregate with recycled aggregate in one-third increments.As an added value to the work, the same tests are performed for different mix combinations, with the inclusion of additives to evaluate their effect on the behavior of recycled concrete.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.952

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 head0.003
GPT teacher head0.164
Teacher spread0.161 · 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

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicRecycled Aggregate Concrete PerformanceFrench-language works237,207