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Record W2011579960 · doi:10.1061/40690(2003)33

Experimental Investigations of the Effect of Selected Admixtures on the Resistance of Concrete to Sulfuric Acid Attack

2003· article· en· W2011579960 on OpenAlexaff
E. Hewayde, E. N. Allouche, George Nakhla

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsWestern University
Fundersnot available
KeywordsSulfuric acidMetakaolinSilica fumeCompressive strengthPorosityMaterials scienceCorrosionCementComposite materialPolymer concreteMetallurgy

Abstract

fetched live from OpenAlex

Each year billions of dollars are spent around the world on the rehabilitation and/or replacement of concrete sewer pipes damaged by sulfuric acid corrosion. This paper reports the findings of an extensive experimental program undertaken to evaluate the resistance of 17 different concrete mix designs with different additives and w/c ratios to sulfuric acid attack. Silica fume, Metakaolin and Organic Corrosion Inhibitors (OCI) in different concentrations were added to the cement to improve the resistance of the concrete paste to sulfuric acid attack. The weight loss of the concrete samples immersed in two concentrations of sulfuric acid (3% and 7%) was measured to evaluate the degree of concrete degradation. The effect of the various admixtures on the compressive strength and porosity of the concrete samples were also evaluated in an effort to determine the relationships between these attributes and the resistance of the concrete samples to a sulfuric acid attack. Data from a two months exposure test showed that the addition of Metakaolin or OCI to the concrete mix resulted in a significant improvement in the concrete resistance to sulfuric acid attack compared to the control mix. Silica fume treated concrete exhibited little or no improvement compared to the control mix. The data also showed that the compressive strength and porosity of the concrete provide little guidance if any to the resistance of the concrete paste to sulfuric acids attack.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.234
Teacher spread0.221 · 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 teacher head, 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

Citations14
Published2003
Admission routes1
Has abstractyes

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