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Enregistrement W7057891245

Mechanical behaviour of masonry assemblages built with mortar containing anti-freeze admixtures subject to sub-freezing curing temperatures

2022· dissertation· en· W7057891245 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Langueen
DomainePhysics and Astronomy
ThématiqueMagnetic confinement fusion research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMortarMasonryCuring (chemistry)Compressive strengthCementLime mortar
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Cold weather masonry construction is a major concern for contractors in North America as well as other geographic locations. When exposed to cold conditions during construction and curing, the performance of masonry assemblies may be affected. Because of the vulnerability of mortar joints to considerable delay in setting time and low strength development rate in cold temperatures, the construction industry has been forced to follow extraordinary building methods. These methods focused primarily on protecting the freshly mixed and placed mortar from freezing for a suitable curing time. This can lead to loss of productivity rate and postponements in construction plans with related additional costs. This research evaluates the performance of mortars that contain nanocellulose and sodium nitrite and as a cold-weather admixture in masonry assemblages under sub-freezing curing temperatures. The effect of sodium nitrite with a dosage of 12% by mass of mixing water and nanocellulose with a dosage of 0.3% by mass of cement on Type S masonry mortars cured at -10°C and room temperatures was investigated. Flowability, air content, and setting time of fresh mixtures were determined. Moreover, for the hardened mortar state, the 28-day compressive strength of mortar cubes and the air content of mortar cylinders were determined. For the purpose of this study, two types of experiments were performed on masonry prisms constructed with four different kinds of mortars and cured under both sub-freezing and room temperatures. The first test was the compressive test to assess the design compressive strength and failure behaviour of the assemblies. A total of 72 prisms of six hollow concrete bricks stacked vertically with full bedding were built and tested in eight separate sets of nine prisms each. The second test was the flexural bond strength test using the bond wrench method described in CSA A3004-C9. For this test, 40 prisms were built, each one six units in height with five mortar joints for a total of 200 joints. These were divided into eight groups based on the kind of mortar used and the curing temperature. Test results indicated that the addition of sodium nitrite and cellulose nanocrystals affected the properties of the fresh and hardened mortar mixtures. The admixtures generally increased the flowability, reduced the air content, and sped up the hydration of cement. The mechanical property tests on masonry prisms showed that the compressive and flexural bond strengths of the prisms were affected considerably by the addition of these admixtures when cured at room temperature. At room temperature, the incorporation of nanocellulose in the mortar resulted in an increase in the compressive strength of the brick prisms by 15% compared to the control sample, while the use of sodium nitrite in the mortar resulted in an 11% increase in the compressive strength compared to the control prisms. For the flexural bond strength, the average results for prisms cured at room temperature indicate that the addition of sodium nitrite lowered the flexural bond strength by 14%, while incorporating nanocellulose separately or in combination with sodium nitrite improved the flexural bond strength by 13% and 14%, respectively. However, at -10°C, only samples with sodium nitrite reached acceptable compressive and flexural bond strengths (21.2 MPa and 0.404 MPa, respectively), as defined by the relevant Canadian standards. Generally, test results showed that sodium nitrite can be used successfully to minimize the adverse effects of freezing temperatures as low as -10°C on strength development of Type S mortar joints by lowering the freezing point of the mixing water, which opens a new approach in mitigating the problems associated with cold weather masonry construction. On the other hand, the use of nanocellulose at normal curing temperatures (22±2°C) resulted in a considerable improvement in the mechanical properties of masonry prisms. In order to improve the mechanical properties of the masonry assemblages, the incorporation of nanocellulose with sodium nitrite resulted in the highest compressive and flexural bond strengths at both normal and subfreezing curing temperatures. From the results discussed in this work, it is shown that the addition of sodium nitrite in masonry mortar mixtures can speed up masonry construction during the winter, with the need for only 4-8 hours of pre-curing at room temperature before being exposed to subfreezing temperatures, which is much relaxed compared to the 48 hours of protection currently required by the Canadian CSA A371 standard.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,007
Tête enseignante GPT0,206
Écart entre enseignants0,199 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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