Development of statistical models to simulate and optimize self-consolidating concrete mixes incorporating high volumes of fly ash
Notice bibliographique
Résumé
Self-consolidating concrete (SCC), a latest version of high performance concrete, has created tremendous interest today as it can be easily placed in congested reinforced concrete structures with difficult casting conditions. It also reduces the construction time and cost of the labor. Normally SCC is being developed using a superplasticizer to generate desired flow and a viscosity modifying admixture (VMA) to prevent segregation in the concrete. In this research project, instead of VMA, high volumes of fly ash were used along with superplasticizer to develop SCC. The minimum use of superplasticizer and optimum use of fly ash were desired to achieve required properties of SCC. The fly ash is expected to be useful not only in generating the flow but as segregation resistance as well. The aim of the present research project was to develop SCC for sustainable construction by optimizing the use of high volumes of fly ash with some proposed statistical models. The rheological study for paste and mortar was carried out first, and Bingham model parameters such as plastic viscosity and yield stress were correlated with the marsh cone flow of paste and fresh concrete properties such as slump flow and filling capacity. The limits for plastic viscosity, yield stress, and specific marsh cone flow of paste and mortar were identified for concrete mixes to be qualified for SCC. Four independent variables such as total binder content (limit 350 to 450 kg/m3), percentage of fly ash replacing cement (limit 30 to 60 %), % of superplasticizer (limit 0.1 to 0.6 %), and W/B (limit 0.33 to 0.45) were considered for design of experiment and for development of statistical models for SCC. Statistically balanced twenry-one concrete mixes were chosen and fresh concrete tests such as slump and slump flow, V -funnel flow, filling capacity, L-box, bleeding, air content, segregation, and initial and final setting time tests were performed. Seven harden concrete tests (for mechanical characteristics and durability) such as compressive strength (1, 7, 28-day), freezing and thawing cycles resistance, surface scaling resistance, rapid chloride permeability, modulus of elasticity, flexural strength, and drying shrinkage were performed to evaluate the performance of SCC. Five statistical models for important properties of SCC such as slump flow, I-day strength, 28-day strength, rapid chloride permeability, and material cost were developed. The limits of rheological parameters of pastes and mortars can be useful to predict the flow behavior of SCC and the proposed models can be useful to design and optimize SCC mixes incorporating high volumes of fly ash.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».