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Record W2061602839 · doi:10.1680/macr.2006.58.5.301

Effect of fineness of high-alumina ground granulated blastfurnace slag on magnesium sulphate attack

2006· article· en· W2061602839 on OpenAlexaff
S. T. Lee, R.D. Hooton, S. S. Kim, E. K. Kim

Bibliographic record

VenueMagazine of Concrete Research · 2006
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFinenessMortarMaterials scienceMagnesiumGround granulated blast-furnace slagPortland cementCementGypsumSlag (welding)MetallurgyComposite material

Abstract

fetched live from OpenAlex

This paper describes the sulphate resistance of hardened mortar and paste specimens incorporating 50% ground granulated blastfurnace slag (BFS). The main variable is the fineness level of the slag materials, which are divided into 445, 600 and 800 m 2 /kg Blaine surface area. Ordinary Portland cement mortar and paste were also used to compare the degree of deterioration by sulphate attack. All mortar and paste specimens were exposed to 4·24% magnesium sulphate solution at 20 ± 1°C for 540 days. The tests used in this study include visual examination, compressive strength and mass loss for mortar samples, and microstructural observations such as X-ray diffraction (XRD), differential thermogravimetric analysis and scanning electromicroscopy for paste samples. Experimental results indicated that mortar specimens with a high-fineness ground granulated blast-furnace slag at 50% replacement showed a poor resistance to magnesium sulphate attack compared with those of lower fineness. The XRD results confirmed that gypsum formation was primarily responsible for the deterioration in the hardened cement matrices of mixtures with high-fineness ground granulated blastfurnace slag. In addition, the conversion of cementitious C–S–H to M–S–H (or M–C–S–H) also led to the severe deterioration in the mortar specimens with a 800 m 2 /kg fineness level. This work suggests that care should be taken when using BFS with high-fineness level under magnesium sulphate 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.302
Teacher spread0.283 · 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.

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

Citations6
Published2006
Admission routes1
Has abstractyes

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