Detail publikačního výsledku

Statistical Estimate of Uniaxial Compressive Strength of Rock Based on Shore Hardness

ZÁVACKÝ, M.; ŠTEFAŇÁK, J.; HORÁK, V.; MIČA, L.

Originální název

Statistical Estimate of Uniaxial Compressive Strength of Rock Based on Shore Hardness

Anglický název

Statistical Estimate of Uniaxial Compressive Strength of Rock Based on Shore Hardness

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The paper presents the use of advanced stochastic simulation techniques for estimating the strength behavior of rock materials. The Shore Rebound hardness was measured on fifty rock specimens coming from eleven different geological localities in Czech Republic. The dry unit weight of every tested rock material was determined also. Uniaxial compressive strength of rock was evaluated then by conducting the compression test on every specimen. Empirical distribution of Shore hardness and dry unit weight variables obtained from laboratory tests was approximated by the best fitted theoretical probability distribution. The stochastic simulation using Latin Hypercube Sampling was conducted based on those distributions. Two different equations used for estimating the compressive strength of rock on the basis of Shore hardness in practice was used as model functions. Comparison and statistical evaluation of uniaxial compressive strength of rock determined by compression test and those obtained as a result of stochastic simulation is discussed. The description of probability distribution of uniaxial strength is obtained as a result of introduced analysis, which can be used as input for fully probabilistic design models of rock materials.

Anglický abstrakt

The paper presents the use of advanced stochastic simulation techniques for estimating the strength behavior of rock materials. The Shore Rebound hardness was measured on fifty rock specimens coming from eleven different geological localities in Czech Republic. The dry unit weight of every tested rock material was determined also. Uniaxial compressive strength of rock was evaluated then by conducting the compression test on every specimen. Empirical distribution of Shore hardness and dry unit weight variables obtained from laboratory tests was approximated by the best fitted theoretical probability distribution. The stochastic simulation using Latin Hypercube Sampling was conducted based on those distributions. Two different equations used for estimating the compressive strength of rock on the basis of Shore hardness in practice was used as model functions. Comparison and statistical evaluation of uniaxial compressive strength of rock determined by compression test and those obtained as a result of stochastic simulation is discussed. The description of probability distribution of uniaxial strength is obtained as a result of introduced analysis, which can be used as input for fully probabilistic design models of rock materials.

Klíčová slova

Rock mechanics, Shore Scleroscope, Rebound hardness, Uniaxial compressive strength of rock, Stochastic simulation techniques, Latin Hypercube Sampling, Test of goodness of fit, Probability distribution

Klíčová slova v angličtině

Rock mechanics, Shore Scleroscope, Rebound hardness, Uniaxial compressive strength of rock, Stochastic simulation techniques, Latin Hypercube Sampling, Test of goodness of fit, Probability distribution

Autoři

ZÁVACKÝ, M.; ŠTEFAŇÁK, J.; HORÁK, V.; MIČA, L.

Rok RIV

2018

Vydáno

20.06.2017

Nakladatel

Elsevier

Místo

Ostrava

Kniha

ISRM European Rock Mechanics Symposium EUROCK 2017

ISSN

1877-7058

Periodikum

Procedia Engineering

Svazek

191

Číslo

191

Stát

Spojené království Velké Británie a Severního Irska

Strany od

248

Strany do

255

Strany počet

8

URL

Plný text v Digitální knihovně

BibTex

@inproceedings{BUT139186,
  author="Martin {Závacký} and Jan {Štefaňák} and Vladislav {Horák} and Lumír {Miča}",
  title="Statistical Estimate of Uniaxial Compressive Strength of Rock Based on Shore Hardness",
  booktitle="ISRM European Rock Mechanics Symposium EUROCK 2017",
  year="2017",
  journal="Procedia Engineering",
  volume="191",
  number="191",
  pages="248--255",
  publisher="Elsevier",
  address="Ostrava",
  doi="10.1016/j.proeng.2017.05.178",
  url="http://www.sciencedirect.com/science/article/pii/S1877705817323184"
}

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