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In recent years, mine site closure and rehabilitation have emerged as significant global challenges. The escalating number of abandoned mines, exemplified by over 60,000 in Australia in 2017, underscores the urgency. Growing public concerns and governmental focus on environmental issues are now jeopardising sustainable mining practices. This paper assesses the role of unmanned aerial vehicles (UAVs) in mine closure, exploring sensor technology, artificial intelligence (AI), and mixed reality (MR) applications. Prior research validates UAV efficacy in mining, introducing various deployable sensors. Some studies delve into AI's use for UAV data analysis, but a comprehensive review integrating AI algorithms with MR methods for mine rehabilitation is lacking. The paper discusses data acquisition methods, repeatability, and barriers toward fully autonomous monitoring systems for mine closure projects. While UAVs prove adaptable with various sensors, constraints such as battery life and payload capacity impact effectiveness. Although UAVs hold potential for AI testing in mine closure studies, these applications have been overlooked. AI algorithms are pivotal for creating autonomous systems, reducing operator intervention. Moreover, MR's significance in mine closure is evident, emphasising its application in the mining industry. Ultimately, a hybrid UAV–AI–MR technology is not only viable but essential for achieving successful mine closure and sustainable mining practices in the future. [ABSTRACT FROM AUTHOR]

The degree of difficulty in crushing an ore depends on the composition of the ore itself. Due to different types and compositions of ores, the crushing mechanism of ores during the crushing process is also different. In order to quantitatively analyze the impact crushing characteristics of mineral components in ores, this paper takes pure mineral quartz, pyrrhotite, and pyrite as the research objects and uses the universal drop weight impact crushing test equipment and standard test methods developed by the JK Mineral Research Center of the University of Queensland, Australia, to conduct JK drop weight tests on these three pure mineral samples. The results show that the particle size distribution of impact crushing products is wide, covering all particle sizes from "0" to close to the feed particle size, and the yield distribution of each product particle size is relatively uniform. There are critical values and "energy barrier" effects for the impact-specific crushing energy. The impact-specific crushing energy has a significant impact on the particle size composition and crushing effect of the crushing product, and there is an interactive effect between the impact-specific crushing energy and the feed particle size and mineral type. The impact crushing resistance of the sample can be characterized by using Mohs hardness, impact crushing characteristic parameters, impact crushing resistance level, and the yield limit value t10 of the characteristic crushing particle size. The overall characterization results have good consistency. [ABSTRACT FROM AUTHOR]

High-precision vector magnetic field detection has been widely used in the fields of celestial magnetic field detection, aeromagnetic detection, marine magnetic field detection and geomagnetic navigation. Due to the large amount of data, the 3D inversion of high-precision magnetic gradient vector data often involves a large number of computational requirements and is very time-consuming. In this paper, a 3D magnetic gradient tensor (MGT) inversion method is developed, based on using a convolutional neural network (CNN) to automatically predict physical parameters from the 2D images of MGT. The information of geometry, depth and parameters such as magnetic inclination (I), magnetic declination (D) and magnetization susceptibility of magnetic anomalies is extracted, and a 3D model is obtained by comprehensive analysis. The method first obtains sufficient MGT data samples by forward modeling of different magnetic anomalies. Then, we use an improved CNN with shear layers to achieve the prediction of each magnetic parameter. The reliability of the algorithm is verified by numerical simulations of synthetic models of multiple magnetic anomalies. MGT data of the Tallawang magnetite diorite deposit in Australia are also predicted by using this method to obtain a slab model that matches the known geological information. The effects of sample size and noise level on the prediction accuracy are discussed. Compared with single-component prediction, the results of multi-component joint prediction are more reliable. From the numerical model study and the field data validation, we demonstrate the capability of using CNNs for inversing MGT data. [ABSTRACT FROM AUTHOR]

Sampling, sample preparation, and assay protocols aim to achieve an acceptable estimation variance, as expressed by a relatively low nugget variance compared to the sill of the variogram. With gold ore, the typical heterogeneity and low grade generally indicate that a large sample size is required, and the effectiveness of the sampling protocol merits attention. While sampling protocols can be optimised using the Theory of Sampling, this requires determination of the liberation diameter (dℓAu) of gold, which is linked to the size of the gold particles present. In practice, the liberation diameter of gold is often represented by the most influential particle size fraction, which is the coarsest size. It is important to understand the occurrence of gold particle clustering and the proportion of coarse versus fine gold. This paper presents a case study from the former high-grade Crystal Hill mine, Australia. Visible gold-bearing laminated quartz vein (LV) ore was scanned using X-ray computed micro-tomography (XCT). Gold particle size and its distribution in the context of liberation diameter and clustering was investigated. A combined mineralogical and metallurgical test programme identified a liberation diameter value of 850 µm for run of mine (ROM) ore. XCT data were integrated with field observations to define gold particle clusters, which ranged from 3–5 mm equivalent spherical diameter in ROM ore to >10 mm for very high-grade ore. For ROM ore with clusters of gold particles, a representative sample mass is estimated to be 45 kg. For very-high grade ore, this rises to 500 kg or more. An optimised grade control sampling protocol is recommended based on 11 kg panel samples taken proportionally across 0.7 m of LV, which provides 44 kg across four mine faces. An assay protocol using the PhotonAssay technique is recommended. [ABSTRACT FROM AUTHOR]

Small Shelly Fossils (SSFs) from the Cambrian are widely distributed and well known across different paleocontinents of the world. However, middle Cambrian SSFs from North China Platform have only rarely been documented until now. In this paper, we presented the first report on SSFs from bioclastic and oolitic limestones of the Zhangxia and Hsuzhuang formations of Henan province, North China. The carbonate-hosted fauna includes brachiopods (Micromitra sp., M. modesta, Eoobolus sp., and Schizopholis sp.), helcionellids (Oelandiellaaccordionata and O. aliciae), hyolithids, Hyolithellus sp., Chancelloriaeros, sponge spicules, echinoderm ossicles, and chancelloriid sclerites. In terms of preservation, the brachiopod shell valves of M. modesta appeared to be homogeneous, consisting of tightly packed phosphate grains. Eoobolus sp. is composed of primary layer and secondary baculate, both of which consist of tightly compacted phosphate grains. Schizopholis sp. has multiple-lamellar phosphatized microstructures that distinctly differ from the other brachiopods recovered from the Longwanggou section. A similar multiple-lamellar microstructure was also revealed in conchs of Hyolithellus, with tightly compacted phosphate grains. The argillaceous shell of Oelandiellaaccordionata and O. aliciae, and the calcitic inner molds of hyolith did not preserve any shell structure. The helcionellids O. accordionata and O. aliciae and the brachiopod M. modesta were reported for the first time from North China. The fauna is most similar to the middle Cambrian faunas of Australia, in the brachiopod and mollusk components; it is also similar in composition of brachiopods and mollusks to coeval faunas from South China. The new fauna of SSFs in the Yiyang Longwanggou Section indicated that the Hsuzhuang and Zhangxia formations are late Drumian to middle Guzhuangian in age, most likely correlating with the Murrawong Creek Formation of Australia. [ABSTRACT FROM AUTHOR]