MétaCan
Menu
Retour à la cohorte
Enregistrement W7162018767 · doi:10.82308/36663

The effects of microwave irradiation on kimberlite and associated rocks: Basis for the development of microwave-assisted rock breakage technology

2023· dissertation· en· W7162018767 sur OpenAlexaboutno aff
Samir Deyab

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineChemistry
ThématiqueMicrowave-Assisted Synthesis and Applications
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésKimberliteExcavationRock mass classificationBreakageRock mechanicsCountry rockGeomechanicsUnderground mining (soft rock)

Résumé

récupéré en direct d'OpenAlex

Finding an efficient non-explosive rock breakage method is an ongoing challenge in mining and civil engineering applications and is required for hard rock underground excavation. The explosive/ blasting techniques employed over many years have caused numerous problems, including excessive noise, dust, pollution, vibrations, and potential damage to nearby structures. As the future of underground hard rock mining is continuous mining techniques, drill-and-blast have the disadvantage of time for the fumed gasses to be cleared. Continuous mechanical excavation in hard rocks has low production rates and high operating costs, and field trials have shown that the lifespan of the cutting tools is short, reducing the efficiency of the operation. New approaches are needed to consider safety, efficiency, and economics. This thesis is part of an overall research project which has been ongoing for the past several years in the Geomechanics Laboratory at McGill University on the application of microwave irradiation to facilitate rock breakage for excavations and mineral processing. It tackles the problem of rock breaking by exploring how hard rocks might be preconditioned and weakened prior to impact by a mechanical excavator. This project investigates the effect of microwave irradiation on the mechanical strength of specific rock samples such as kimberlite, and associated rocks such as granite, limestone and basalt for comparison. Given the lack or limited knowledge on kimberlite as well as its effect under microwave irradiation.,different properties of these rock samples, such as dielectric properties, physical properties (i.e., mineral composition, rock quality designation, specific gravity, porosity, specific heat capacity and moisture content), abrasivity, were measured during the project to evaluate the heating behaviors, as well as mechanical properties of rocks subjected to microwave irradiation, were investigated. Mechanical strength tests were conducted to evaluate the effect of microwave irradiations on the strength of rock samples. The rock samples for the first time were treated for 4–360s in a multi-mode and single-mode microwave cavity at power levels from 2 to 15 kW. Also, in this study, calorimetry is performed to measure and analyze heat absorption, and thermal images are studied to determine the temperature contour on the sample surface.The unconfined compressive strength (UCS) and Brazilian tensile strength (BTS) were significantly reduced by microwave irradiation. The tests showed that Cerchar Abrasivity Index (CAI) was not affected by microwave irradiation. Furthermore, the Percentage of the change of Pulse sound velocity (PSV) increased with microwave power level and exposure time as a result of the microcracks within the samples. The mode I fracture toughness (KIC) test results showed that KIC decreases when exposure time increases and when the samples are cut prior to treatment. It was also observed in the study that energy absorption by the samples was more when the samples were close to the horn of the microwave. Microwave treatment is found to be a promising strategy that combines microwave irradiation and mechanical techniques. The aim of potentially implementing microwave-based methods is to facilitate continuous mining and to improve the production rate while reducing the costs of fracture

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,127
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

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

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 Opus0,011
Tête enseignante GPT0,247
Écart entre enseignants0,237 · 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 tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

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
Publié2023
Routes d'admission1
Résumé présentoui

Explorer davantage

Même sujetMicrowave-Assisted Synthesis and ApplicationsTravaux en français237 207