Optimalizace těžby s ohledem na ověřené a predikované koncentrace alkálií v cementářské surovině Mokrá v návaznosti na normativní limity vyráběných cementů.

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Authors

Donocik, Roman

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Vysoká škola báňská - Technická univerzita Ostrava

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ÚK/Sklad diplomových prací

Signature

201500072

Abstract

The dissertation is the problem of the occurrence of alkali elements in the deposit of raw materials for cement following the process of refining for the production of clinker with an impact on normative values of cement product line. The main pillar of this work is the fact that the concentration of alkali elements in the deposit appears to be directly proportional to some other oxides represented by limestones and shales. Generating the correlation context the, prerequisite for this dissertation. The work will be supported by longtime laboratory analysis that connect parallel extraction and subsequent experience across a very diverse range of petrographic deposit. Historically not always been the focus on the analysis of alkali in the deposit. Consequently arose from the viewpoint of alkali for more than 40 year history of mining at the deposit unexplored places. Finding good correlations with other oxides we can achieve highly probable derivation of the alkali content in these places unspecified in the deposit. Thus, a comprehensive course of isolines across deposit will be the necessary guide for technological preparation of raw materials in the medium and long-term mining plans. The work will also cover current trends in low-alkaline cements in the devolved requirements for the extraction of composition of raw materials. Guarantee of stability and balance of supply suitable raw material is a necessary prerequisite for declaring the relevant normative product range of cement. For low-alkaline products will be central limit the alkali content, to which our complex knowledge of deposit will be a main prerequisite.

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Import 07/01/2015

Subject(s)

limestones deposit, alkali, alkaline reaction, correlation, statistics, clinker burning, regression, optimization of mining

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