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Record W3097098142 · doi:10.9798/kosham.2020.20.5.195

Mechanical and Durability Characteristics of Rainwater Penetration and Retention Pavement Concrete Blocks Incorporating Bottom Ash Aggregates

2020· article· en· W3097098142 on OpenAlexaff
Hwang-Hee Kim, Ri-On Oh, Jae-Young Lee, Sung‐Ki Park, Sang-Sun Cha, Chan-Gi Park

Bibliographic record

VenueKorean Society of Hazard Mitigation · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsContech (Canada)Optech (Canada)
FundersKorea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and FisheriesNational Research Foundation of KoreaMinistry of Agriculture, Food and Rural Affairs
KeywordsDurabilityCompressive strengthRainwater harvestingBottom ashCementFly ashMaterials sciencePervious concreteImpervious surfaceGeotechnical engineeringAggregate (composite)Permeability (electromagnetism)Flexural strengthComposite materialAbrasion (mechanical)Environmental scienceEngineering

Abstract

fetched live from OpenAlex

In this study, the mechanical properties and durability of rainwater penetration and retention pavement concrete blocks incorporating bottom ash fine aggregate were investigated to develop pavement concrete blocks that could reduce the rainwater leakage of impervious concrete structures. Pavement concrete blocks were prepared by replacing 0%, 10%, and 20% of the weight of natural fine aggregate with bottom ash fine aggregate for 410 and 450 kg/m<sup>3</sup> cement contents. Experimental tests were conducted to determine the compressive strength, flexural strength, abrasion resistance, slip resistance, freeze–thaw resistance, and permeability coefficient of the pavement concrete blocks. Pavement concrete blocks produced with a cement content of 450 kg/m<sup>3</sup> and a 10% replacement ratio of bottom ash fine aggregate satisfied the target performance and exhibited the best overall performance. Theseoptimal mix parameters were applied in this study to design and manufacture pavement concrete blocks for rainwater penetration and retention that satisfied the target performance.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.015
GPT teacher head0.204
Teacher spread0.189 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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