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    The analysis of radial displacements occurring near the face of a circular opening in weak rock mass
    (Pergamon-Elsevier Science Ltd, 2010) Basarir, H.; Genis, M.; Ozarslan, A.
    The effect of opening size, rock properties and stress conditions on the radial displacements ahead and behind of the advancing face of a circular opening is one of the most important topics in civil and mining engineering. In this paper we develop a prediction system for radial displacements around the face of an opening by combining rock mass rating classification system, a three dimensional finite difference code and multiple regression modeling. Predictive equations and response surfaces for rock mass response are proposed. By using these equations and response surfaces, it is possible to assess radial displacements around the face and to construct the longitudinal deformation profile of a circular opening with different diameters excavated in weak rock mass under different stress conditions. The predictive equations were validated by means of statistical tests and analytical solution. Proposed response surfaces and equations can provide the basis of guiding the design and construction of underground openings. (C) 2010 Elsevier Ltd. All rights reserved.
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    Prediction of the performance of impact hammer by adaptive neuro-fuzzy inference system modelling
    (Pergamon-Elsevier Science Ltd, 2011) Kucuk, K.; Aksoy, C. O.; Basarir, H.; Onargan, T.; Genis, M.; Ozacar, V.
    Impact type excavators are widely used for excavations, performed in weak-laminated-foliated-anisotropic rocks. Therefore the prediction of the performance of impact hammer is very important in many mining and civil engineering projects. This paper describes the construction of adaptive neuro-fuzzy inference system model for predicting the performance of impact hammer type excavator by considering rock and excavating machine properties such as block punch strength index, geological strength index system and impact hammer power. Extensive field and laboratory studies were conducted in the tunnel construction route of the second stage of Izmir Metro Project, which excavated in laminated-foliated flysch rocks. The results of the constructed adaptive neuro-fuzzy inference system and traditional multiple regression models were compared. Although the prediction performance of traditional multiple regression model is high, it is seen that adaptive neuro-fuzzy inference model exhibits better prediction performance according to statistical performance indicators. By means of the developed model, the performance of impact type excavators can be predicted in terms of net excavation based on the selected rock and machine properties. (C) 2010 Elsevier Ltd. All rights reserved.