Determination of regressive relation binding the theoretical and observed final values of curvatures for geological and mining conditions the one of JSW coal mines
The aim of this paper is obtainment of dependence between practical and theoretical values of curvatures which were calculated at a given level of forecast's safety. The practical curvatures were determined on the basis of results of geodetic measurements conducted on observation points situated in form of line. Values of theoretical curvatures were determined by the usage of EDN – OPN computer program, applying the Budryk – Knothe theory assuming the typical values of its parameters (a = 0.8; tgβ = 2.0; B = 0.32r). Then calculated an unreliability of forecast of curvatures' final values. The regression relation between the observed and theoretical final values of curvatures was determinate assuming the probability of 50% that the measured value will not exceed the predicted value. The values of standard deviation are between 22.84 [m−1 10−6], when all final values of measured and theoretical curvatures are simultaneously taken into account in an linear regression analysis, and 25.32 [m−1 10−6], when a linear regression is carried out for the curvatures measured after the exploitation of the third longwall. The lower value of standard deviation (16.38 [m−1 10−6]) was obtained when a linear regression was made for the curvatures observed after the exploitation of the first longwall. On the basis of the undertaken analysis it can be concluded that for the geological and mining conditions prevailing in the area of measuring line, a regression relation between the measured and theoretical values of curvatures can be expressed by some equation. However, the predicted curvatures are characterized by the calculation error.
Białek, Jan; Mielimąka, Ryszard; and Orwat, Justyna
"Determination of regressive relation binding the theoretical and observed final values of curvatures for geological and mining conditions the one of JSW coal mines,"
Journal of Sustainable Mining: Vol. 14
, Article 2.
Available at: https://doi.org/10.46873/2300-3960.1231
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