The value of uniaxial compressive strength (DCS) is used for every classification system of rock mass. Generally, NX type core is used for determining rock material's DCS. However, sometimes is very hard to obtain a suitable core for realizing the test. For this situation, other experimental studies should be carried out. Added to that, understanding the effect of discontinuities on strength of rock material, it should be made tests in situ. Because of the reasons given above that Schmidt hammer test is used for determining hardness of rock material both in laboratory and in situ. The correlation between DCS and Schmidt hardness has been investigated and proposed by some researchers. Although there are analytical and statistical techniques for the assessment of this correlation they are not sufficient for linguistic appreciations as "soft", "hard", "weak" and alike. Fuzzy sets and logic are the tools for substitution of personal expertise with verbal and incomplete numerical data. The main purpose of this paper is to set up a fuzzy model between desired parameters to provide almost the same results but in fuzzy domain. Hence, it is possible to treat of obscure and uncertain appreciations. The defuzzification of the results compares well with the analytical formulations.


In order to understand the compressive strength of discontinuities of a rock mass, the rebound number determined by Schmidt hammer is a well recognised method. This hammer is applied vertical to the discontinuities during experiments (Ulusay & Sonmez 2002). Hence, Schmidt hammer gives an important opportunity for understanding the compressive strength of discontinuity and the intact rock's uniaxial compressive strength (DCS) in situ. On the other hand, Grasso et al. (1992) has implied that however there is some important limitations about the use of this experiments, it is possible to apply this procedure to the NX type cores for laboratory experiments. Additionally, Singh & Gahrooee (1989) proposed the ratio between DCS and JCS that is used for understanding the degree of degeneration which is an input parameter of rock mass rating (RMR) that was proposed by Bieniawski (1989). The main objective of this study is to acquire fuzzy correlation for estimating UCS of rock taking into account the Rand y. The results are compared with the result of the nomogram (Fig. 1), hence it is possible to see after the correlation between desired parameters that it is possible to achieve nearly same result by using fuzzy model but in fuzzy domain.


After proposing fuzzy logic by Zadeh (1965), many scientific researches should have been checked especially for having uncertain data and linguistic approaches. Classical methodologies may not solve the estimation problem especially when the vagueness of the parameter increases. The most important drawbacks of binary logic are that there is no contradiction and excluding the mid-points (Sen 2002). Every item must be considered as black or white in non-fuzzy logic, however fuzzy logic gives vital opportunity in order to get the every color of life.

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