Refinement of genetic and structural models of the Úrkút manganese ore deposit (W-Hungary, Europe) using statistical evaluation of archive data

2012 ◽  
Vol 4 (3) ◽  
Author(s):  
Lóránt Bíró ◽  
Márta Polgári ◽  
Tivadar Tóth ◽  
Tamás Vigh
Keyword(s):  
Tectonic Activity ◽  
Mathematical Treatment ◽  
Manganese Ore ◽  
Large Set ◽  
Ore Deposit ◽  
Ore Body ◽  
Significant Difference ◽  
Ore Characterization ◽  
Archive Data ◽  
Ore Types

AbstractAlthough the Úrkút manganese ore deposit in western placecountry-regionHungary has been exploited for at least 90 years, there are still numerous open questions concerning ore genetics as well as structure and geometry of the ore body. A large set of available archive data for the deposit have been reviewed and evaluated in order to solve some of the most crucial problems. For processing, besides diverse GIS approaches, univariate and multivariate statistical methods were used on the created unified database. The main aims of the mathematical treatment were giving a classification scheme for the wide spectrum of Mn-ores based on their chemical composition (Mn, Fe, Si, P) as well as evaluation of their spatial distribution. For the ore characterization and understanding the genetic processes, cluster and discriminant function analyses were used. Results of the multivariate treatment verified the existence of different ore types and provided an exact chemical definition for all of them. It alsoinferred that the main geochemical processes that took place in ore genesis were similar for all sample groups (ore types) with significantly different weights in each case.A 3D evaluation of the Úrkút mine heading map system shows that the ore body covers the footwall surface as a stratiform sheet throughout the study area. Palaeo-relief studies suggest a significant difference between the footwall and hanging wall morphologies which clearly implies tectonic activity following ore deposition. The deposit was affected by an E-W compression stress field near the Aptian-Albian transition causing folding of the Mn deposit.

Geomechanical assessment of mining conditions in the Khingansk manganese ore body

2014 ◽  
Vol 50 (1) ◽  
pp. 10-17 ◽  
Author(s):  
I. Yu. Rasskazov ◽  
B. G. Saksin ◽  
M. I. Potapchuk ◽  
V. I. Usikov
Keyword(s):  
Manganese Ore ◽  
Ore Body ◽  
Mining Conditions

scholarly journals IDENTICAL WORD MEANING “INTERPRETATION AND TRANSLATION” IN THE CONTEXT OF CORPUS-BASED SENTENCES

2020 ◽  
Vol 2 (3) ◽  
pp. 189-195
Author(s):  
Mega Febriani Sya ◽  
Ninuk Lustyantie ◽  
Miftahulkhairah Anwar
Keyword(s):  
Speech Acts ◽  
First Language ◽  
Word Meaning ◽  
Occurrence Rate ◽  
Large Set ◽  
Frequency Of Occurrence ◽  
Significant Difference ◽  
Meaning Interpretation ◽  
Authentic Data ◽  
Data Collection Procedure

For students whose first language is not a native English speaker, at first glance they will interpret the words "translation" and "interpretation" with the same meaning. Both are indeed similar and both function to transfer one language to another. This study aims to identify the frequency of occurrence of the words "translation" and "interpretation" in several situations in different speech contexts. The method used in this study is the corpus method, to see a large set of authentic data which provides clearer information about the frequency of occurrence of the words "translation" and "interpretation" in several actual contexts of different speech acts. The data collection procedure on the corpus and its analysis uses the facilities provided by the corpus page, namely "chart". The results show that the comparison of the frequency of occurrence of the words "translation" and "interpretation" in the context of different speech shows a significant difference, the word interpretation has a higher occurrence rate of 4282 times than translation, which appeared 1405 times.   The meaning of this finding is that the word interpretation is more widely used in the context of formal academic sentences because interpretation does not only have a meaning for itself but can also function as a continuation of meaning from the translation.  

scholarly journals Smectite appearance in the footwall of the Úrkút manganese ore deposit, Bakony Mts., Hungary

2019 ◽  
Vol 62 (1) ◽  
pp. 100-118
Author(s):  
Máté Zsigmond Leskó ◽  
Richárd Zoltán Papp ◽  
Boglárka Anna Topa ◽  
Ferenc Kristály ◽  
Tamás Vigh ◽  
...  
Keyword(s):  
Flow System ◽  
Manganese Carbonate ◽  
Manganese Ore ◽  
Ore Formation ◽  
Ore Deposit ◽  
Oceanic Anoxic Event ◽  
The Past ◽  
Anoxic Event ◽  
Core Storage ◽  
The Relationship

The Úrkút manganese ore deposit (Transdanubian Range, Hungary) is one of the largest manganese accumulations to be formed during the Toarcian Oceanic Anoxic Event. In the past 60 years, the area was investigated intensively. The core storage facility of the manganese mine had more than 20,000 sample pieces. Most of these samples have never been investigated. During this study, which is the first widespread clay mineral study in the footwall of the Úrkút manganese ore deposit, we investigated 40 samples from seven boreholes (footwall rocks, black/gray shales below and above the first ore bed, and manganese carbonate ores). Although previous studies assumed that smectite is associated only with the ore beds, our research revealed its appearance in the footwall (Pliensbachian) as well. Simultaneously, tripoli (the local name of completely bleached chert) can also be found in the footwall. Based on the investigated samples, a sharp geochemical difference was detected between Pliensbachian and Toarcian sediments. In this paper, we try to trace the relationship between the smectite content of the footwall and the ore bed and compare these results with the observed geochemical changes. Based on the new data, we assume that the ore accumulation was caused by a flow system (upwelling-controlled ore formation).

Sandaozhuang Open-Pit Quality Block Modeling Based on Engineering Geological Profile

2014 ◽  
Vol 962-965 ◽  
pp. 959-963
Author(s):  
Ying Sun ◽  
Shu Ai Ma ◽  
Lang Huang ◽  
Huan Ming Zhou ◽  
Dong Tao Hu ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Boundary Curve ◽  
Open Pit ◽  
Quality Model ◽  
Block Model ◽  
Body Contour ◽  
Ore Deposit ◽  
Model Based ◽  
Ore Body ◽  
Contour Model

Block model is the precondition of open-p it mine o ptimization boundary design and mining design. In this paper , after studying the ore deposit model that using the optimization boundary, p ut forward to establish ore deposit quality block model based on the proposed Sandaozhuang engineering geological profile . Using prospecting line profile CAD drawings that o btained during the exploration phase, us e two-dimensional coordinate conversion three-dimensional coordinates, the profile boundary curve smoothing, apply D elaunay triangulation and other technology to establish ore body contour model. Establish the ore body quality model based on the ore body contour model, use i nverse distance weighted method in geostatistics for the assignment of ore body quality model, get the Sandaozhuang open pit quality block model. And ba sed on this to estimate the reserves , lay the foundation for the follow work of the mine.

Hyperspectral drill-core imaging for ore characterization

2020 ◽  
Author(s):  
Laura Tusa ◽  
Mahdi Khodadadzadeh ◽  
Margret Fuchs ◽  
Richard Gloaguen ◽  
Jens Gutzmer
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
High Resolution ◽  
Hyperspectral Imaging ◽  
Mineral Exploration ◽  
Electromagnetic Spectrum ◽  
Drill Core ◽  
Ore Characterization ◽  
Ore Types ◽  
Drill Cores

<p>Mineral exploration campaigns represent an essential step in the discovery and evaluation of ore deposits required to fulfil the global demand for raw materials. Thousands of meters of drill-cores are extracted in order to characterize a specific exploration target. Hyperspectral imaging is recently being explored in the mining industry as a tool to complement traditional logging techniques and to provide a rapid and non-invasive analytical method for mineralogical characterization. The method relies on the fact that minerals have different spectral responses in specific portions of the electromagnetic spectrum. Sensors covering the visible to near-infrared (VNIR) and short-wave infrared (SWIR) are commonly used to identify and estimate the relative abundance of minerals such as phyllosilicates, amphiboles, carbonates, iron oxides and hydroxides as well as sulphates (Clark, 1999). The distribution of these mineral phases can frequently be used as a proxy for the distribution of ore minerals such as sulphides. Typical core imaging systems can acquire hyperspectral data from a whole drill-core tray in a matter of seconds. Available sensors record data in several hundreds of contiguous spectral bands at spatial resolutions around 1 mm/pixel.</p><p>​​In this work, we apply a local high-resolution mineralogical analysis, such as SEM-MLA (Kern et al., 2018), for a precise and exhaustive mineral mapping of some selected small samples. We then upscale these mineralogical data acquired from thin sections to drill-core scale by integrating hyperspectral imaging and machine learning techniques. Our proposed method is composed of two main steps. In the first step, after initially co-registering the hyperspectral and high-resolution mineralogical data and making a training set, a machine learning model is trained. In the second step, we apply the learned model to obtain mineral abundance and association maps over entire drill-cores.</p><p>​​The mapping is further used for the calculation of other mineralogical parameters essential to exploration and further mining stages such as modal mineralogy, mineral association, alteration indices, metal grade estimates and hardness. The proposed methodological framework is illustrated on samples collected from a porphyry type deposit, but the procedure is easily adaptable to other ore types. Therefore, this approach can be integrated in the standard core-logging routine, complementing the on-site geologists and can serve as background for the geometallurgical analysis of numerous ore types.  </p><p>​​</p><p>​​Clark, R. N., 1999, “Spectroscopy of rocks and minerals, and principles of spectroscopy,” in Remote sensing for the earth sciences: Manual of remote sensing, vol. 3, John Wiley & Sons, Inc, pp. 3–58.</p><p>​​Gandhi, S. M. and Sarkar, B. C., 2016, “Drilling,” in Essentials of Mineral Exploration and Evaluation, pp. 199–234.</p><p>​​Kern, M., Möckel, R., Krause, J., Teichmann, J., Gutzmer, J., 2018. Calculating the deportment of a fine-grained and compositionally complex Sn skarn with a modified approach for automated mineralogy. Miner. Eng. 116, 213–225.</p>

Waves incident on a circular harbour

1985 ◽  
Vol 401 (1821) ◽  
pp. 349-371 ◽  
Keyword(s):  
Resonant Frequency ◽  
Wave Amplitude ◽  
Single Frequency ◽  
Mathematical Treatment ◽  
Total Flow ◽  
Internal Resonances ◽  
Through Flow ◽  
Significant Difference ◽  
Flow Through ◽  
Incident Waves

The wave amplitude inside a harbour that is subject to incident waves is greatly affected by the frequency of the incident waves. If the harbour entrance is small it is expected that the internal resonances of the harbour will be excited at the appropriate incident frequencies. Published arguments concerning the magnitude of the resonances are, however, not conclusive. In this paper a circular harbour with a small entrance is studied with the use of a rigorous mathematical treatment. It is found that as the harbour entrance decreases in size the magnitude of resonance owing to a single frequency increases slowly (logarithmically). However, this increase is too slow to make a significant difference. The magnitude of resonance in relation to a continuous spectrum input increases, but for the Helmholtz mode only. Again the increase is slow (logarithmic). These results are found to be in agreement with the work of J. Miles ( J. Fluid Mech. 46, 241-265 (1971)). In many approximate calculations it is assumed that the total flow through the gap will effectively determine the flow near a resonant frequency. This is correct near the Helmholtz resonance, but incorrect near the higher resonances where the through-flow is small.

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