- Tytuł:
- Cerchar abrasivity index prediction using multi-proxy data. A case study from the Sagdere Formation (Denizli Molasse Basin, Turkey)
- Autorzy:
- Dogruoz, Cihan
- Powiązania:
- https://bibliotekanauki.pl/articles/1853856.pdf
- Data publikacji:
- 2020
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
ścieralność
węgiel brunatny
górotwór
cerchar abrasivity index
fuzzy inference system
Denizli Molasse Sagdere Formation
multiple regression - Opis:
- The prediction of rock cuttability to produce the lignite deposits in underground mining is important in excavation. Moreover, the certain geographic locations of rock masses for cuttability tests are also significant to apply and compare the rock cuttability parameters. In this study, sediment samples of two boreholes (Hole-1 and Hole-2) from the Sagdere Formation (Denizli Molasse Basin) were applied to find out the cerchar abrasivity index (CAI), rock quality designations (RQD), uniaxial compressive strengths, Brazilian tensile strengths and Shore hardnesses. The Sagdere Formation deposited in the terrestrial to shallow marine conditions consists mainly of conglomerates, sandstones, shales, lignites as well as reefal limestones coarse to fine grained. A dataset from the fine grained sediments (a part of the Sagdere Formation) have been created using rock parameters mentioned in the study. Dataset obtained were utilized to construct the best fitted statistical model for predicting CAI on the basis of multiple regression technique. Additionally, the relationships among the rock parameters were evaluated by fuzzy logic inference system whether the rock parameters used in the study can be correlated or not. When comparing the two statistical techniques, multiple regression method is more accurate and reliable than fuzzy logic inference method for the dataset in this study. Furthermore, CAI can be predicted by using UCS, BTS, SH and RQD values based on this study.
- Źródło:
-
Archives of Mining Sciences; 2020, 65, 4; 787-801
0860-7001 - Pojawia się w:
- Archives of Mining Sciences
- Dostawca treści:
- Biblioteka Nauki
Artykuł