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Record W2939048528 · doi:10.1142/s1756973719500021

Modeling of Cementitious Representative Volume Element with Various Water–Cement Ratios

2019· article· en· W2939048528 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Multiscale Modelling · 2019
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRepresentative elementary volumeHomogenization (climate)Materials scienceFinite element methodCementitiousPoisson's ratioBoundary value problemShear modulusElastic modulusCementComposite materialMicrostructureStructural engineeringPoisson distributionMathematical analysisMathematicsEngineeringStatistics

Abstract

fetched live from OpenAlex

This study uses the finite element method (FEM) to measure the mechanical properties of microstructure-based cementitious representative volume elements (RVEs) with various water–cement ratios (W/Cs) generated by CEMHYD3D. The finite element boundary condition effects that significantly and computationally change the elastic properties are studied and discussed. Various boundary conditions in ABAQUS are applied and compared with the results obtained using the variational asymptotic method for unit cell homogenization (VAMUCH). This comparison is conducted using ANSYS. This study aims to analyze and determine the effect of different boundary conditions in detail on the prediction of the elastic properties of cementitious RVE with various W/Cs and identify the best approach in this regard. Results show that Young’s, shear, and bulk moduli decrease with the increase in W/C and the boundary conditions in ABAQUS influence the outcomes, particularly on bulk modulus and Poisson’s ratio.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.465
Threshold uncertainty score0.556

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 head0.012
GPT teacher head0.208
Teacher spread0.196 · 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