Exploitation
Hamid Saberi; Mohammad Golmohammadi; Mohammadali Zanjani; Yaghoub Saberi
Abstract
The Bavanapadu-Nuvvalarevu coastal sector in Andhra Pradesh, India, hosts substantial subsurface heavy mineral (HM) resources, presenting significant economic potential. This study employs ArcGIS raster techniques to estimate Total Heavy Mineral (THM) and Total Economic Heavy Mineral (TEHM) resources ...
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The Bavanapadu-Nuvvalarevu coastal sector in Andhra Pradesh, India, hosts substantial subsurface heavy mineral (HM) resources, presenting significant economic potential. This study employs ArcGIS raster techniques to estimate Total Heavy Mineral (THM) and Total Economic Heavy Mineral (TEHM) resources in a 39 square kilometers area, integrating geospatial analysis with field data from core sediment samples. The findings reveal a total of 2.681953 million tons of THM, including 2.434422 million tons of TEHM, with the highest concentration observed in the top 1-meter sea bed sediment layer (1.605286 million tons). Ilmenite, garnet, and sillimanite dominate the mineral assemblage, accompanied by smaller quantities of zircon, monazite, and rutile, offering an estimated revenue potential of $634 to $851 million USD. The application of ArcGIS methodologies, particularly inverse distance weighting (IDW) interpolation, enabled precise mapping of HM distribution, despite challenges such as wide sample spacing and shallow core penetration. While the study highlights the economic and industrial significance of the Bavanapadu sector, it also underscores environmental concerns, including habitat disruption and sediment degradation, associated with mining. Sustainable practices, such as advanced separation technologies, site rehabilitation, and comprehensive environmental impact assessments (EIAs), are essential to mitigate ecological impacts. This research demonstrates the efficacy of GIS-based techniques in resource estimation and sustainable mining, offering a replicable framework for coastal and offshore mineral resource management globally. The findings provide critical insights into balancing economic growth with environmental preservation, setting a benchmark for responsible heavy mineral extraction in dynamic coastal environments.
Exploitation
Mohammad Hossein Jalalian; Raheb Bagherpour; Mehrbod Khoshouei; S. Najmedin Almasi
Abstract
Diamond wire cutting is a common method to extract dimension stones, which depends on various factors, including the mechanical and physical properties of the stone, cutting specifications, and operational characteristics. Specific energy, production rate, efficiency, and wear of diamond beads are some ...
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Diamond wire cutting is a common method to extract dimension stones, which depends on various factors, including the mechanical and physical properties of the stone, cutting specifications, and operational characteristics. Specific energy, production rate, efficiency, and wear of diamond beads are some of the criteria that influence economic and environmental optimization of diamond wire cutting operations. In this study, the specific energy of the diamond wire cutting process was measured for 11 samples of Granite stones. By analyzing the impact of parameters such as stone density, porosity, and cutting rate on energy consumption, a linear regression model was developed with a correlation coefficient (R2) of 0.944 to predict specific energy for different types of stones. Statistical analyses, including ANOVA, have confirmed that the model accurately predicts specific energy values. Data from three new stone samples were used to validate the model, and their predicted energy values were compared with actual values. The model presented achieved an R2 value of 0.827, demonstrating its high accuracy. The results indicate that energy consumption in dimension stone cutting operation can be accurately predicted and characterized indirectly using high precision stone properties and operational parameters. This method can accurately and indirectly monitor energy consumption and cutting machine performance during the dimension stone cutting operation and can be used to optimize economic and environmental aspects of this process.
