Water and material balance at mine tailings impoundments : software program development and risk analysis
Notice bibliographique
Résumé
Tailings impoundments are commonly used in the mining industry for the disposal and storage of mine wastes including tailings, waste rock and process water. The impoundments often require engineered embankment dams to facilitate containment. Failure of impoundment dams can lead to serious effects downstream due to the release of significant amounts of water and solids. Inadequate water management has been recognized as the primary cause of such failures. Tailings impoundment dam design involves estimating the site water and material balance to design appropriate impoundment structures and material management facilities. The balances are usually conducted using monthly average hydrologic values and output from the balance are the required dam crest elevations during the life of the mine. The "models" that are employed by industry and their consultants to complete these hydrologic budgets are simple and spreadsheet based, using average hydrologic values to predict required monthly dam crest elevations. The lack of flexibility and transparency in these spreadsheet balances has been identified as a problem by mining engineers. A Microsoft Windows based software program written in Visual Basic, Visual Balance, was developed as part of this study. Visual Balance is a fast, simple method of modelling the water and material balance in a single impoundment tailings disposal system and predicting required dam crest elevations. Visual Balance also includes a risk analysis module which predicts probable impoundment operation and closure conditions based on a Monte Carlo simulation of expected precipitation and surface runoff values. Water management problems identified by Visual Balance include insufficient free pond water available for reclaim, inadequate freeboard, uncontrolled release requirements, or tailings solids exposure. Knowledge and anticipation of these challenges could influence tailings impoundment site selection, design, or mine operating conditions. Planning for these conditions in impoundment and facility design could save companies considerable cost and aggravation. The results of the five Case Studies conducted as part of this study emphasized the predictive capabilities of Visual Balance. Monthly dam crest elevations similar to those previously predicted by spreadsheet based balances were modelled for the five Case Studies by Visual Balance. In the two Case Studies where actual operating conditions were available for comparison, insufficient free pond water availability and excess water leading to low freeboards experienced at each site were successfully predicted by Visual Balance.
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 | 0,000 | 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 | 0,000 | 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 ».