Implications of collecting additional data for slope design in an open pit operation
Notice bibliographique
Résumé
Geotechnical stability analysis and design in open pit mines requires access to representative geological, structural, hydrogeological, and rock mass models. The quality and quantity of collected geomechanical data used to build such models can have significant implications in the design of safe and economically viable slopes. Data collection is a continuous process throughout the life of a mine. The process starts from exploration to conceptual/preliminary feasibility, feasibility, design and construction, operations (early production/late production), and mine closure. As geomechanical data is often limited at an early stage of a project, the estimated variability of the geotechnical factors may be larger than the actual data variability. This can potentially result in a conservative selection of the pit slope angle. Collecting additional geomechanical data at later stages of the mine development may contribute to reducing the uncertainty associated with the geotechnical properties and a steeper slope angle may be used for the design. This can result in significant economic benefits. This paper investigates the impact of access to new data over time, following a series of geomechanical data collection campaigns, on design decisions. This is illustrated by comparing the resulting slope design, at three stages of the mine project, at a South African open pit mine. To demonstrate this, a series of slope stability analyses were performed using limit equilibrium tools. For each project stage, the slope angle design was modified until a similar probability of failure of 5% or less was obtained. The corresponding factor of safety distributions for each project stage were then compared to evaluate the impact of collecting additional data on the resulting slope design. The results showed that data variability can differ significantly from one project stage to another. Data variability may be greater at more advanced project stages (i.e. a wider distribution of the factor of safety). Furthermore, the results showed that, even for the cases with greater variability, steeper slope angles were possible at more advanced stages for the proposed design requirement (probability of failure < 5%). In this investigation, as more data became available, the uncertainty associated with data variability could be sufficiently reduced to allow the selection of less conservative slope angles. This can be used as a managerial tool in developing data collection strategies and allocating the necessary funds, and can lead to important economic benefits to the mining operation.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».