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Record W2036986539 · doi:10.3141/2335-01

Guidelines for Selection and Use of Coarse Recycled-Concrete Aggregates in Structural Concrete

2013· article· en· W2036986539 on OpenAlexaffabout
Liam Butler, Susan Tighe, Jeffrey West

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2013
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsUniversity of WaterlooRead Jones Christoffersen (Canada)
Fundersnot available
KeywordsAggregate (composite)Computer scienceCivil engineeringConstruction engineeringEngineeringMaterials science

Abstract

fetched live from OpenAlex

This paper presents guidelines for using recycled-concrete aggregate (RCA) as a full or partial replacement for natural coarse aggregate in new concrete (RCA concrete). Several international standards and guidelines for the use of RCA in concrete are reviewed and contrasted to identify areas in which further development is required. The main results of an extensive experimental research program by the authors are summarized here to provide a basis for the development of a framework for using RCA in structural concrete. Several RCA performance classes are proposed, each with a specific set of requirements and suitable applications. The proposed performance classes define further requirements and guidance for the use of RCA beyond the requirements of Canadian Standards Association A23.1 and ASTM C33. The authors propose a detailed decision tree to allow engineers, concrete producers, aggregate suppliers, and contractors to assess whether a particular RCA source is suitable for use in reinforced concrete or plain concrete or as fill material.

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)0.019
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.019
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.005
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0060.002
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0060.007

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 head0.109
GPT teacher head0.370
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations22
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueTransportation Research Record Journal of the Transportation Research BoardSame topicRecycled Aggregate Concrete PerformanceFrench-language works237,207