Yazar "Ahmed, Mohammed Yadgar" seçeneğine göre listele

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    An evaluation on effects of surface explosion on underground tunnel; availability of ABAQUS Finite element method
    (Pergamon-Elsevier Science Ltd, 2022) Keskin, Inan; Ahmed, Mohammed Yadgar; Taher, Nichirvan Ramadhan; Gor, Mesut; Abdulsamad, Balen Zrar
    Tunnels are a paramount infrastructure due to the vast array of their uses. Despite all the safety measures taken during the design stages, tunnels still possess the weakness of being vulnerable to the effect of ground surface explosions, as the impact of such events can potentially cause the collapse of the whole structure, or parts of it, and hence leads to loss of lives. This paper utilizes Finite Element Methods (FEM) by using Abaqus/CAE software to examine the behavior of the underground circle-shaped tunnel when subjected to an impact load generated by ground-surface explosions. First, the FEM model was validated using the results of the experimental results available in the literature. After obtaining a reasonable agreement between the results of the FEM simulation and the experimental test model, then the software was used to determine the effect of the ground-surface explosion on an underground circle-shaped tunnel. The results exhibited that there is a good agreement between the surface crater size of the validation model and the crater size of the experimental test. Moreover, the intensity of explosion pressure on subsurface soil of the validation model on FEM gives the same result as obtained from the experimental test. The FEM simulation result indicated that the concrete lining and embedded steel rebar cage of the tunnel attain almost the same pressure profiles during the explosion period. In addition, air pressure was increased during the explosion period, which is in agreement with what has been proven in the literature.
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    Prediction of electrical conductivity using ANN and MLR: a case study from Turkey
    (Springer Int Publ Ag, 2020) Keskin, TUlay Ekemen; Ozler, Emre; Sander, Emrah; Dugenci, Muharrem; Ahmed, Mohammed Yadgar
    The study areas are located in Turkey (Kastamonu, Bartin, Karabuk, Sivas) and contain very different rock types, various mining and agricultural activity opportunities. So, the areas have groundwaters that have different chemical compositions and electrical conductivity (EC) values. The EC can be measured using EC meter, and it must be measured in situ. But, the measurement of EC in situ is laborious, time-consuming, expensive, and difficult in arduous terrain environments. In recent years, machine learning models have been a primary focus of interest for a lot of study by providing often highly accurate forecast for solutions of such problems. The aim of the study is to forecast EC of groundwater using artificial neural networks (ANN) and multiple linear regressions (MLR). Twelve different hydrochemical parameters, which affect the EC, such as major/minor ions and trace elements, were used in the analysis. Multilayer feed-forward ANN trained with backpropagation in Python machine learning libraries was used in this study. In order to obtain the most appropriate ANN architecture, trial-and-error procedure was used and different numbers of hidden layers, neurons, activation functions, optimizers, and test sizes were constructed. This study also tests the usability of input parameters in EC prediction studies. As a result, comparisons between the measured and predicted values indicated that the machine learning models could be successfully applied and provide high accuracy and reliability for EC and similar parameters forecasting.
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    A simulation on soil structure interaction with ABAQUS; effect on the behavior of a concrete building of soil layers and earthquake properties
    (Gazi Univ, 2024) Ahmed, Mohammed Yadgar; Keskin, Inan
    In this article, the effect of soil properties and earthquakes on a structure built in a multi-layer foundation soil is studied using Abaqus/CAE. Single foundations are one of the most common types of foundations traditionally required to support buildings in earthquake-prone regions. Most researchers work on the dynamic interaction between the foundation and the soil, which can affect the response of the building during earthquakes due to the type of earthquake and the properties of the soil layer. In this paper, four different earthquakes were applied to a reinforced concrete building constructed in two-layer soils with very different soil properties, and a discussion on soil-structure interaction was opened using Abaqus software. In the analysis, a layered soil is simulated with 4 different models (soft-hard, hard-soft). Through these analyses, the influence of the different soil layers (soft and hard), the building displacement and the frequency content of the earthquake were studied. According to the result of the analysis, it is important to consider the earthquake characteristics, the soil properties, and the type of foundation in the dynamic soil-structure interaction.