Environmental and operational safety of tailing storage facilities: analysis of accidents, causes and technical state diagnostic methods
Notice bibliographique
Résumé
A number of high-profile industrial accidents occurred at sludge and tailings storage facilities in different countries of the world are considered. The problem of ecological and technogenic danger of operating such objects, which leads to significant casualties among the civilian population, serious economic losses and harms the surrounding natural environment, is illustrated. The main causes of emergency situations have been established and analysed, it will help to reduce the risk of accidents and to minimize negative environmental consequences for similar facilities in Ukraine. The retrospective review covers the period from 1960 to 2022. During this time, about 150 cases of soil dams’ destruction in waste storage facilities were recorded. The different tendency in the frequency of accidents is noted. In particular, during the period from 1960 to 2009, there were 98 accidents with an average frequency of nearly two (1.98) per year. Over the last decade (2010-2020), the number of accidents reached 36 cases, and their frequency almost doubled to 3.6 accidents per year. Over the past two years, from the beginning of 2021 to December 2022, 10 accidents have already been registered. The vast majority of accidents during this period occurred in 34 countries of the world. The largest number of them was noted in the USA (22.4%), China (10.4%), Brazil (7.5%), Chile (6.7%), the Philippines (6.0%), Canada (5.2 %), Great Britain (4.5%) and other countries. Studies note jumps in the increase of accidents that have ten-year trends (1975, 1985, 1995, 2005). The general tendency of mass accidents since the beginning of 2015 is shown, which is substantiated by the expired terms of operation of many mining and ore enterprises (mines) and significant (exceeding normative) terms of operation of tailings storage facilities, which in some places were left without proper supervision and care. It was established that a violation of the dam slope stability (37%), an overflow of the designed capacity of the tailings storage facility (12%), seismic activity (11%), etc., are the main causes of accidents. A review of modern approaches to the management of dangerous anthropogenic objects and methods of diagnosing the technical condition of such structures was conducted. The use of a complex of organizational and technical solutions about the implementing the modern methods of assessment and control the technical condition of waste storage facilities at various levels of their operation and stages of the life cycle is proposed.
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 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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,009 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».