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Record W4417350387 · doi:10.1038/s41598-025-32316-z

Compressive strength and maturity of UHPC cubes and cylinders: new conversion factors and recommendations for early-age quality control

2025· article· en· W4417350387 on OpenAlexaff
Mohammed S. Ibrahim, Mohamed A. Moustafa, Shahrukh Shoaib

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsMcGill University
FundersAccelerated Bridge Construction University Transportation CenterU.S. Department of Transportation
KeywordsCompressive strengthCube (algebra)CylinderUltimate tensile strengthCuring (chemistry)Quality (philosophy)Cementitious

Abstract

fetched live from OpenAlex

Ultra-high-performance concrete (UHPC) is a robust cementitious material with high compressive strength exceeding 125 MPa. UHPC can reach up to 80 MPa after one day of casting, which expands the material application domain and makes it appealing for accelerated construction. The appropriate on-site quality control methods should be implemented to guarantee that desired UHPC design has been achieved. The cylinder specimens of 75 mm diameter are used in the United States for quality control purposes. However, cylinders require surface preparation and grinding using special equipment, which consumes more time and affects the strength results at very early ages. Thus, this research aims to establish the conversion factors to use cubes confidently for UHPC quality control. To provide comprehensive and generalized results and allow for immediate implementation, this research considers, for the first time, five UHPC types and a total of eight mixtures with variable steel fiber (SFs) ratios, different cube sizes, and examines the compressive behavior at both early and late ages. The study provides results from about 900 specimens with different curing conditions sets and covers a wide range of strength from 7 to 140 MPa. The experimental results assist in understanding the shape and size effect and revisit the cubes-to-cylinders strength conversion factors. A detailed application for strength maturity was also conducted to further validate the newly proposed conversion factors and extend the use of cubes for early age quality control. To summarize, this study presents new conversion factors for the cube compressive strength at an early age, in addition to recommendations for adopting the strength maturity method for quality control. The dataset of all tested specimens is also summarized and presented in the Appendices.

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)0.008
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.285
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 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

Citations2
Published2025
Admission routes1
Has abstractyes

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