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High‐Pressure Device for Fluid Extraction from Porous Materials: Application to Cement‐Based Materials

2008· article· en· W2167096048 on OpenAlexaff
Martin Cyr, Patrice Rivard, Francis Labrecque, Alain Daidié

Bibliographic record

VenueJournal of the American Ceramic Society · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsExtraction (chemistry)RepeatabilityMaterials sciencePorosityCementPortland cementPorous mediumMortarComposite materialChromatographyChemistry

Abstract

fetched live from OpenAlex

A high‐pressure device, reaching an axial pressure of 1000 MPa, intended to the extraction of the pore solution of rigid and slightly porous materials, has been developed to improve the efficiency of extraction. This paper gives an application of fluid extraction from mortars made with Portland cement. It includes an experimental study of the performance of the apparatus, and an analysis of the results in terms of efficiency of extraction, repeatability of measurement, and effect of the squeezing pressure on the pore solution composition. Results shows that: (1) the squeezing efficiency using our apparatus is higher than those found in the literature; (2) the measurement uncertainty ranges between 1.5% and 14%; (3) no significant effect of pressure (up to 1000 MPa) is observed for concentrations of Ca, Na, K, and Si. This paper suggests conducting extraction at 1000 MPa, especially on old concrete or concrete made with low W / C ratios.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.245
Teacher spread0.227 · 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

Citations72
Published2008
Admission routes1
Has abstractyes

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