Rock Mechanics
Ekin Koken
Abstract
In this study, several soft computing analyses are performed to build some predictive models to estimate the uniaxial compressive strength (UCS) of the pyroclastic rocks from central Anatolia, Turkey. For this purpose, a series of laboratory studies are conducted to reveal physico-mechanical rock properties ...
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In this study, several soft computing analyses are performed to build some predictive models to estimate the uniaxial compressive strength (UCS) of the pyroclastic rocks from central Anatolia, Turkey. For this purpose, a series of laboratory studies are conducted to reveal physico-mechanical rock properties such as dry density (ρd), effective porosity (ne), pulse wave velocity (Vp), and UCS. In soft computing analyses, ρd, ne, and Vp are adopted as the input parameters since they are practical and cost-effective non-destructive rock properties. As a result of the soft computing analyses based on the classification and regression trees (CART), multiple adaptive regression spline (MARS), adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANN), and gene expression programming (GEP), five robust predictive models are proposed in this study. The performance of the proposed predictive models is evaluated by some statistical indicators, and it is found that the correlation of determination (R2) value for the models varies between 0.82 – 0.88. Based on these statistical indicators, the proposed predictive models can be reliably used to estimate the UCS of the pyroclastic rocks.
E. Koken; E. Başpınar Tuncay
Abstract
Andesites with a satisfactory quality have been mainly considered as dimension stones worldwide. However, practical approaches are required to evaluate the dimension stone quality due to the increasing demand for natural resources. This study presents detailed laboratory investigations on andesitic rocks ...
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Andesites with a satisfactory quality have been mainly considered as dimension stones worldwide. However, practical approaches are required to evaluate the dimension stone quality due to the increasing demand for natural resources. This study presents detailed laboratory investigations on andesitic rocks in NE Uşak, Turkey. For laboratory studies, representative rock blocks are obtained from unweathered (W0) to highly weathered (W3) rock masses. Laboratory test results demonstrate that progressive rock weathering has remarkable influences on the dry density (ρd), effective porosity (ne), pulse wave velocity (Vp), uniaxial compressive strength (UCS), flexural strength (FS), and Böhme abrasion value (AWR) of the andesitic rocks. Of the above parameters, ne seems to be the most affected rock property due to progressive rock weathering. Furthermore, based on the three-parameter Weibull distribution, andesitic rocks are evaluated for their use as cladding stones. A quantitative approach called the suitability index (SI) is proposed to quantify the quality of cladding stones for andesitic rocks, considering six different evaluation criteria (C1–C6). Two examples of SI calculations reveal the implementation of the proposed approach. The suitability of the proposed approach is also checked by Monte Carlo analysis, showing that the use of SI is suitable to quantify the cladding stone quality for the investigated andesitic rocks. However, the proposed approach should be improved by incorporating the mineralogical and textural characteristics into the SI calculations. Moreover, it should also be attempted to different andesitic rocks in order to observe the similarities or difficulties of quantifying the quality of cladding stones.
