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Mechanical properties of polymer-modified porous concrete

2018· article· en· W2795915316 on OpenAlexaff
Nur Farhayu Ariffin, Mohd Faizal Md Jaafar, Nor Hasanah Abdul Shukor Lim, Muhammad Aamer Rafique Bhutta, Mohd Warid Hussin

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsUniversity of British Columbia
FundersUniversiti Teknologi Malaysia
KeywordsMaterials sciencePolymer concreteComposite materialPolymerFlexural strengthPervious concreteCementCompressive strengthPorosityPermeability (electromagnetism)Void ratioWater–cement ratioPorous mediumChemistry

Abstract

fetched live from OpenAlex

In this research work, polymer-modified porous concretes (permeable concretes) using polymer latex and redispersible polymer powder with water-cement ratio of 30 %, polymer-cement ratios of 0 to 10 % and cement content of 300 kg/m 3 are prepared. The porous concrete was tested for compressive strength, flexural strength, water permeability and void ratio. The cubes size of specimen is 100 mm × 100 mm × 100 mm and 150 mm × 150 mm × 150 mm while the beam size is 100 mm × 100 mm × 500 mm was prepared for particular tests. The tests results show that the addition of polymer as a binder to porous concrete gives an improvement on the strength properties and coefficient of water permeability of polymer-modified porous concrete. It is concluded from the test results that increase in compressive and flexural strengths and decrease in the coefficient of water permeability of the polymer-modified porous concrete are clearly observed with increasing of polymer-cement 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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.021
GPT teacher head0.196
Teacher spread0.175 · 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".

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Citations13
Published2018
Admission routes1
Has abstractyes

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