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Paste Tailings Management (Hardcover, 1st ed. 2017): Erol Yilmaz, Mamadou Fall Paste Tailings Management (Hardcover, 1st ed. 2017)
Erol Yilmaz, Mamadou Fall
R4,113 R3,466 Discovery Miles 34 660 Save R647 (16%) Ships in 12 - 17 working days

This book provides an overview of paste tailings disposal at mine sites. It deals comprehensively with the characterization of sulphide-rich tailings, geotechnical and microstructural behaviour, surface tailings disposal applications, underground paste backfilling, and case studies. The authors place emphasis on the characterization, monitoring, disposal and treatment, as well as environmental considerations of problematic sulphidic tailings. The framework is supported by worldwide case studies.

Paste Tailings Management (Paperback, Softcover reprint of the original 1st ed. 2017): Erol Yilmaz, Mamadou Fall Paste Tailings Management (Paperback, Softcover reprint of the original 1st ed. 2017)
Erol Yilmaz, Mamadou Fall
R4,352 Discovery Miles 43 520 Ships in 10 - 15 working days

This book provides an overview of paste tailings disposal at mine sites. It deals comprehensively with the characterization of sulphide-rich tailings, geotechnical and microstructural behaviour, surface tailings disposal applications, underground paste backfilling, and case studies. The authors place emphasis on the characterization, monitoring, disposal and treatment, as well as environmental considerations of problematic sulphidic tailings. The framework is supported by worldwide case studies.

Machine Learning Applications in Industrial Solid Ash: Chongchong Qi, Qiusong Chen, Erol Yilmaz Machine Learning Applications in Industrial Solid Ash
Chongchong Qi, Qiusong Chen, Erol Yilmaz
R3,823 Discovery Miles 38 230 Ships in 12 - 17 working days

Offering the ability to process large or complex datasets, machine learning (ML) holds huge potential to reshape the whole status for solid ash management and recycling. Machine Learning for Solid Ash Management and Recycling is, as far as the author knows, the first published book about ML in solid ash management and recycling. This book highlights fundamental knowledge and recent advances in this topic, offering readers new insight into how these tools can be utilized to enhance their own work. The reference begins with fundamentals in solid ash, covering the status of solid ash generation and management. The book moves on to foundational knowledge on ML in solid ash management, which provides a brief introduction of ML for solid ash applications. The reference then goes on to discuss ML approaches currently used to address problems in solid ash management and recycling, including solid ash generation, clustering analysis, origin identification, reactivity prediction, leaching potential modelling and metal recovery evaluation, etc. Finally, potential future trends and challenges in the field are discussed.

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