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Record W2590764150

Developing and Evaluating Rapid Test Methods for Measuring the Sulphate Penetration Resistance of Concrete in Relation to Chloride Penetration Resistance

2011· dissertation· en· W2590764150 on OpenAlexaboutno aff
Ester Karkar

Bibliographic record

VenueTSpace (University of Toronto) · 2011
Typedissertation
Languageen
FieldEngineering
TopicElectrical and Thermal Properties of Materials
Canadian institutionsnot available
Fundersnot available
KeywordsPenetration (warfare)Penetration testChlorideMaterials scienceGeotechnical engineeringComposite materialEngineeringMetallurgyOperations research
DOInot available

Abstract

fetched live from OpenAlex

External sulphate attack on concrete can lead to cracking, expansion and sometimes loss of cohesiveness of hardened cement paste. Therefore, aside from using sulphate resistant cementitious binders, it is important to design concrete which can resist sulphate penetration. In this research, both ASTM C1202 and NT Build 492 electrical migration tests were modified such that sulphate rather than chloride penetration resistances were measured. Modifications included exposing concrete specimens to Na2SO4 rather than NaCl solutions and measuring the depth of sulphate penetration visually using BaCl2+KMnO4 rather than AgNO3 solution. Nine concrete mixtures of varying w/cm, slag replacement and cement types were tested in both original standard tests and modified tests to evaluate the influence of these material variables on test results and compare chloride to sulphate results. It was found that while migration coefficients and total charge passing were lower for sulphate, the influence of material variables were relatively similar.

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)0.007
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.045
GPT teacher head0.285
Teacher spread0.240 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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