Yazar "Atici, Umit" seçeneğine göre listele

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  • Küçük Resim Yok
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    Investigation of ultrasonics sound waves (P and S) behaviour under different pressure for igneous rocks
    (2010) Atici, Umit
    An ultrasonic sound wave has been used in rock mechanics to determine rock properties for many years. Because it is a relatively simple, low-cost and non-destructive testing method compared to others. Water content, porosity, and cracks in the rocks structure are some of the most important parameters for P and S-wave speed. In Rocks, under uniaxial compression stress, the account of space inside the compressed rock is reduced while an ultrasonic sound waves speed is increased. However, after a certain level of compression; with the formation of micro-cracks, ultrasonic sound wave velocity is decreased. To determine the maximum ultrasonic wave speed in rocks, 11 different igneous rocks for dry and water saturated samples using Pundid Pulus test device were tested under 7 different loads (0, 0.5, 1, 5, 10, 15 and 20 kN). In order to investigate the changes in ultrasonic sound velocities, the density of rocks, water absorption ratio by weight and volume, porosity values are compared with Ultrasonic wave speed.
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    Öğe
    INVESTIGATION OF ULTRASONICS SOUND WAVES (P AND S) BEHAVIOUR UNDER DIFFERENT PRESSURE FOR IGNEOUS ROCKS.
    (INT SCIENTIFIC CONFERENCE SGEM, 2010) Atici, Umit
    An ultrasonic sound wave has been used in rock mechanics to determine rock properties for many years. Because it is a relatively simple, low-cost and non-destructive testing method compared to others. Water content, porosity, and cracks in the rocks structure are some of the most important parameters for P and S-wave speed. In Rocks, under uniaxial compression stress, the account of space inside the compressed rock is reduced while an ultrasonic sound waves speed is increased. However, after a certain level of compression; with the formation of micro-cracks, ultrasonic sound wave velocity is decreased. To determine the maximum ultrasonic wave speed in rocks, 11 different igneous rocks for dry and water saturated samples using Pundid Pulus test device were tested under 7 different loads (0, 0.5, 1, 5, 10, 15 and 20 kN). In order to investigate the changes in ultrasonic sound velocities, the density of rocks, water absorption ratio by weight and volume, porosity values are compared with Ultrasonic wave speed.
  • Küçük Resim Yok
    Öğe
    Modelling of the Elasticity Modulus for Rock Using Genetic Expression Programming
    (HINDAWI LTD, 2016) Atici, Umit
    In rock engineering projects, statically determined parameters are more reflective of actual load conditions than dynamic parameters. This study reports a new and efficient approach to the formulation of the static modulus of elasticity E-s applying gene expression programming (GEP) with nondestructive testing (NDT) methods. The results obtained using GEP are compared with the results of multivariable linear regression analysis (MRA), univariate nonlinear regression analysis (URA), and the dynamic elasticity modulus (E-d). The GEP model was found to produce the most accurate calculation of E-s The proposed approach is a simple, nondestructive, and practical way to determine E-s for anisotropic and heterogeneous rocks.
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    Predicting compressive strength using the texture coefficient with soft computing techniques for rocks
    (2022) Çomaklı, Ramazan; Atici, Umit
    Rock strength plays one of the most dominant roles for mining, geology, and civil engineering in terms of planning, excavation, and safety. Compressive strength (fc), which is the most used strength type, requires time, cost, and standard size specimens are needed to find it in the laboratory. In this study, Regression Analysis (RA), Neural Networks (NNs), Gene-Expression Programming (GEP), and Adaptive Network-based Fuzzy Inference System (ANFIS) were used for predicting using both textural and mechanical properties which are detected with a dimensionless sample or directly in the field. For this purpose, a data set consists of 136 data value (46 magmatic, 77 sedimentary and 13 metamorphic rocks) was used, and three different feature sets were constructed. The comparison of the estimated results with each other was performed by training, testing, and checking of these models. The comparisons and results of the statistical analyses indicate that soft computing techniques represent significantly effective methods to calculate fc even in situations when input and output values are not related to each other, and it is possible to create statistically suitable and valid mathematical models by everyone using GEP.