Applied Earth Science: Transactions of the Institutions of Mining and Metallurgy

The genesis of the Enkafela Mn deposit and associated processes were investigated using field mapping, mineralogical and geochemical analyses by XRD, ICP-MS/AES and XRF. The geology is constituted by limestone, evaporites/gypsum, conglomerates and basalt. The orebody is hosted in the limestone and has two distinctive manganese layers: a massive bottom and powdery top. Pyrolusite, romanechite and birnessite are the major ore minerals. The geochemical results indicate elevated MnO (av. 70.25 wt-%), Ba (>10, 000 ppm), Sr (>10, 000 ppm) and depleted Fe₂O₃ (av. 0.37 wt-%) and other metals. The massive orebody has higher (172.9 ppm) REE content than the powdery ore (7.84 ppm). Chondrite normalised REE plot shows LREE enrichment for both orebodies. The massive manganese layer shows enrichment in Ce and no Eu anomaly. The powdery manganese is depleted in Ce and Eu. The geochemical and mineralogical studies indicate that the manganese mineralisation has dual sources: hydrogenous and hydrothermal sources (for the massive orebody), and hydrothermal (for the powdery). The data suggest that there was active submarine hydrothermal activity in Dallol associated with the regional geodynamic events while the area was inundated by the Red Sea during the Pleistocene.

The mineralogical, chemical, physical and thermal analyses of the representative clays from North Africa (Algeria, Morocco and Tunisia) have been studied for their potential use in traditional ceramic industry. The clay fractions of the Moroccan and Algerian clays are essentially composed of illite (38 and 21%, respectively) and kaolinite (17 and 12%, respectively) as predominant minerals, with subordinate I/Sm mixed-layer (10 and 3%, respectively). The non-clay minerals are quartz, calcite, dolomite and occasionally plagioclase and haematite. Tunisian clays are composed of similar proportions of kaolinite (15%), smectite (15%), illite (12%) and palygorskite (9%), whereas their associated minerals are quartz (30%), calcite (15%) and rarely plagioclase (4%). The chemical data show agreement with estimated mineralogical compositions. All the samples contain large amounts of iron (>5.6%) and earth-alkaline oxides (>6.9%), and high values of LOI (>12%). Algerian clays show high plasticity (PI = 40%), requiring particular attention and careful temperature control during drying to avoid the deformation and the formation of cracks in the ceramic bodies, whereas the Tunisian and Moroccan clays (PI = 18% and 16%, respectively) show acceptable behaviour in shaping and drying. The average grain-size distribution demonstrates a substantial amount of the silt and clay fractions in raw materials which are therefore suitable for easy shaping of paste without any special need for further adjustments. Indeed, the amount of fraction upper 63 µm is lower less than 2%. The main transformations during firing are influenced by the abundance of components such as Fe₂O₃, CaO, MgO, K₂O and Na₂O and observed above 1000°C with the appearance of new crystalline phases, especially mullite, spinel, plagioclase, diopside and haematite. The technical parameters of fired pieces (firing shrinkage, water absorption and flexural strength) fall within the ceramic international standards (ISO).

Geotechnical logging of drillcore typically includes joint roughness due to its importance in rock mass characterisation. Here we propose digitising the measurement of roughness via a tomography scan. Image processing steps are described for relating the scan to a simple profilometric definition of roughness. The approach is amenable to directional statistical visualisation on a stereoplot.

In this study, by using the algorithm of the U-statistic and fractal methods and combining them with each other, a new combined method as U values fractal model (U-N and U-A) is introduced. Then, the proposed method is employed to determine the boundaries of background and anomalous populations. Results show that in U-N and U-A fractal models, the first fracture boundary is much clearer and more accurate than previous fractal models (C-N and C-A) in the same condition. In U-N model, due to the nature of the U method algorithm, there is a discontinuity as exact threshold between background and anomaly that in U-A model, this does not exist due to the homogenization of U values. In this method, the exact threshold between background and anomaly is determined by U-statistic method and by its combination with the fractal method, in each population, sub-populations are identified more accurately and simply than concentration fractal model.