Abstract

High-quality core samples are necessary for the laboratory uniaxial compressive strength determinations. However, such core samples cannot always be obtained from weak, thinly bedded and block-in-matrix rocks, particularly from agglomerates and conglomerates. For this reason, the development of predictive models for the mechanical properties of rocks, mechanical indices or petrographical characteristics seems to be an attractive study area in rock engineering. Predictive models, generally, include simple and multivariate regression techniques, fuzzy logic and neural network approaches. In the present study, a fuzzy triangular chart for the prediction of uniaxial compressive strength of the Ankara agglomerates from their petrographical composition is suggested. A simple image classification method is used to determine the percentages of constituents of the agglomerate core samples. The Ankara agglomerates are mainly composed of tuff which is a cementing material, and pink and black andesite blocks ranging from few millimetres to about a meter. The classification chart developed in this study for the Ankara agglomerates includes 25 sub-triangle characterizing different petrographical composition expressed by if–then fuzzy rules. Based on the petrographical composition and uniaxial compressive strength values, a total of 15 membership function graphs were produced using if–then rules. Employing the membership functions and triangular petrographical composition chart, a fuzzy triangular chart for the prediction of uniaxial compressive strength of the agglomerates was obtained. To control performance of prediction capacity of the triangle, the variance accounts for (VAF) and the root mean square error (RMSE) indices were calculated as 96.76% and 9.37, respectively. It is noted that the fuzzy triangular chart exhibited a very high prediction capacity.

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