Errors in average strength estimates of sedimentary rock masses in South Yakutia based on geometric induction sounding data

№1 (2023)

Neradovskii L.G.

УДК 550.370+552.08
https://doi.org/10.47148/1609-364X-2023-1-48-62

AbstractAbout the AuthorReferences
The probabilistic model developed to describe the engineering and geological conditions for the operation of buildings and infrastructure in the city of Neryungri has been verified. The model is a power-function equation which correlates, by regression relationships, laboratory-determined compressive strength of saturated frozen sandstone samples with attenuation of the high-frequency harmonic field of a vertical magnetic dipole in warm permafrost composed of sandstone. The attenuation values were obtained by geometric electromagnetic induction sounding at a frequency of 1.125 MHz. The model verification was conducted at a fixed frequency on a section of the Amur-Yakutsk Railway located at a significant distance from Neryungri. The railway here is underlain by low-temperature dolomite masses. The statistical analysis indicates that the relative errors of the dolomite saturated strength estimates from the geometric EM induction data with a 73.0% probability do not exceed 20%. With this level of accuracy close to that of laboratory tests according to GOST 25100–2020, it is reasonable to suggest that the probabilistic model can be used region-wide in southern Yakutia to predict saturated strength of foundation materials composed of sandstone and dolomite. It can provide an effective solution for market-based construction and mining industries, as increasing anthropogenic and climatic impacts are anticipated to cause thawing and saturation of sedimentary rock masses.
Leonid G. Neradovskii
Doctor of Technical Sciences, Senior Researcher at the Laboratory of Engineering Geocryology
Melnikov Permafrost Institute SB RAS
36, Merzlotnaya St., Yakutsk, 677010, Russia
е-mail: leoner@mpi.ysn.ru
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Key words: sandstone, dolomite, strength, geometric EMI sounding, high-frequency vertical magnetic dipole field, attenuation coefficient, probabilistic model, prediction error

Section: Modeling geo objects and geo-processes