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مقالات فارسیISIکنفرانسهاژورنالها

Granite Downstream Production Dependent Size and Profitability Assessment: an application of Mathematical-based Artificial Intelligence Model and WipFrag Software

محل انتشار: مجله معدن و محیط زیست، دوره: 15، شماره: 2
سال انتشار: 1403
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 41

فایل این مقاله در 19 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:
https://civilica.com/doc/1896096

شناسه ملی سند علمی:

JR_JMAE-15-2_007

تاریخ نمایه سازی: 8 بهمن 1402

چکیده مقاله:

The purpose of this research work is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo State, aggregate quarries. In addition, an Artificial Neural Network (ANN) model for granite profitability was developed. A structured survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study includes granite marketing operations, royalty, production costs, and mine production information. In this study, the efficacy of granite fragmentation was assessed using the WipFrag software. The relationship between particle size distribution, blast design, blast efficiency, and uniformity index were analyzed using the WipFrag result. The optimum blast design was also identified and recommended for mine production. The result revealed that large burden distances result in bigger X۵۰, X۸۰, and Xmax fragmentation sizes. A burden distance of ۲ m and a ۲ m spacing were identified as the optimum burden and spacing. The finding revealed that blast mean size and ۸۰% passing mesh size have a positive correlation. The result from this study indicated that the uniformity index has a positive correlation with blast efficiency and a negative correlation with maximum blast fragmentation size. The prediction accuracy of the developed models was evaluated using the coefficient of determination (R۲), root mean square error (RMSE), and mean square error (MSE). The error analysis revealed that the ANN model is suitable for predicting quarry-generated profit.

کلیدواژه ها:

blast efficiency ، uniformity index ، blast fragmentation ، granite ، mineral economic

نویسندگان

Blessing Taiwo

Department of Mining Engineering, Federal University of Technology, Akure, Nigeria

Oluwaseun Famobuwa

Department of Mining Engineering, West Virginia University, USA

Melodi Mata

Mineral Economics Lab, Department of Mining Engineering, Federal University of Technology, Akure, Nigeria

Mohammed Sazid

Mining Engineering Department, King Abdulaziz University, Jeddah, Saudi Arabia

Yewuhalashet Fissha

Department of Geosciences, Geotechnology and Materials Engineering for Resources, Graduate School of International Resource Sciences, Akita University, Japan

Victor Jebutu

University of Bolton, England

Adams Akinlabi

Department of Mining Engineering, Federal University of Technology, Akure, Nigeria

Olaoluwa Ogunyemi

Mineral Economics Lab, Department of Mining Engineering, Federal University of Technology, Akure, Nigeria

Ozigi Abubakar

Mines Department, Dangote Cement Plc, Ibese, Nigeria

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