Yazar "Karpuz, Celal" seçeneğine göre listele

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  • Küçük Resim
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    Estimating rock mass properties using Monte Carlo simulation: Ankara andesites
    (Pergamon-Elsevier Science Ltd, 2010) Sarı, Mehmet; Karpuz, Celal; Ayday, Can
    In the paper, a previously introduced method (Sari, 2009) is applied to the problem of estimating the rock mass properties of Ankara andesites. For this purpose, appropriate closed form (parametric) distributions are described for intact rock and discontinuity parameters of the Ankara andesites at three distinct weathering grades. Then, these distributions are included as inputs in the Rock Mass Rating (RMR) classification system prepared in a spreadsheet model. A stochastic analysis is carried out to evaluate the influence of correlations between relevant distributions on the simulated RMR values. The model is also used in Monte Carlo simulations to estimate the possible ranges of the Hoek-Brown strength parameters of the rock under investigation. The proposed approach provides a straightforward and effective assessment of the variability of the rock mass properties. Hence, a wide array of mechanical characteristics can be adequately represented in any preliminary design consideration for a given rock mass. (C) 2010 Elsevier Ltd. All rights reserved.
  • Küçük Resim
    Öğe
    Rock variability and establishing confining pressure levels for triaxial tests on rocks
    (2006) Sarı, Mehmet; Karpuz, Celal
    [No abstract available]
  • Küçük Resim
    Öğe
    Stochastic modeling of accident risks associated with an underground coal mine in Turkey
    (ELSEVIER SCIENCE BV, 2009) Sarı, Mehmet; Selçuk, Ayşe Sevtap; Karpuz, Celal; Düzgün, Hafize Şebnem
    In this study, a methodology is proposed towards development of all uncertainty model that includes randomness in the occurrence of days-lost accidents in a coal mine. The accident/injury data consists of 1390 days-lost accident cases recorded at GLI-Tuncbilek underground lignite mine from January 1994 to December 2002. In the first step of proposed methodology, the frequency and the severity of the accidents have been modeled statistically by fitting appropriate distributions. The test done by BestFit software yields a chi-square value of 21.53 (p = 0.089) with 14 degrees of freedom and estimates the parameter of lambda for Poisson distribution as 12.87 accidents/month. For the severity component, a lognormal distribution is fitted to days-lost data and chi-square goodness-of-fit test calculates a value of 40.44 (p = 0.097) with 30 degrees of freedom. The parameters of lognormal distribution are estimated as a mean of 14.3 days and standard deviation of 23.1 days, respectively. Then, two distributions are basically combined by Monte Carlo simulation in order to construct relative risk levels in yearly base referring to the final cumulative distribution. Finally, a simple forecasting modeling is carried out in order to quantitatively predict the expected risk levels by using decomposition technique in time series analysis. Stochastic model estimates that although, there Would be substantial reduction in the expected number of accidents in the near future, the higher level of risks still should be a concern for the mine management.