Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Conference Object Citation - Scopus: 1On the Variation in Several Rock Properties due to Magnesium Sulfate Weathering Tests ‒ A Case Study for Limestones(International Multidisciplinary Scientific Geoconference, 2019-06-20) Köken, E.Contributions to the behavior of rock materials under various conditions provide a practical knowledge about issues relating the performance and long-term serviceability of rocks. In this study, various limestones with varying textural features were investigated in terms of their resistance against magnesium sulfate weathering tests. For this purpose, initial physico-mechanical properties of limestones were determined. Then, rock materials were subjected to magnesium sulfate weathering tests (up to 20 cycles) and the variation in physico-mechanical properties were determined for each rock type. As a result of laboratory tests, compared to initial rock properties, effective porosity (ne, %) increased in the range of 3% ‒ 14% and 12% ‒ 35% after 10th and 20th magnesium sulfate weathering cycles, respectively. Uniaxial compressive strength of rocks (UCS, MPa) decreased by 9% ‒ 24% after 10th cycles and by 32% – 58% after 20th cycles. Brazilian tensile strength of rocks (BTS, MPa) decreased in the range of 7% ‒ 19% and 20% ‒ 49% after 10th and 20th cycles, respectively. Similar to the variations in UCS and BTS, Tangential Young Modulus (Eti, GPa) also decreased at a rate of 13% ‒ 28% and 23% ‒ 64% after 10th and 20th cycles, respectively. However, the values of Tangential Poisson’s Ratio (vti) fluctuated with progressive accelerated weathering cycles, which could be linked to varying axial and lateral strain rates at 50% of UCS values for the limestones investigated. Furthermore, the variation in crack initiation stress σCI (MPa) due to progressive magnesium sulfate tests were also evaluated considering two strain-based methods and the findings showed that σCI of limestones slowly decreased with increasing weathering test cycles. It could be claimed that cyclic magnesium sulfate tests performed on rock materials would be beneficial for assessing the long-term serviceability of rocks. In this context, mud-supported limestones seem to have a greater resistance against magnesium sulfate weathering tests compared to the grain-supported ones. However, the number of samples should be increased in order to achieve a comprehensive understanding about the degradation processes of limestones. © 2021 Elsevier B.V., All rights reserved.Article Citation - Scopus: 7A Comparative Study to Estimate the Mode I Fracture Toughness of Rocks Using Several Soft Computing Techniques(Murat Yakar, 2023-10-05) Köken, E.; Kadakci Koca, Tümay; Koca, Tümay KadakciFracture toughness is an important phenomenon to reveal the actual strength of fractured rock materials. It is, therefore, crucial to use the fracture toughness models principally for simulating the performance of fractured rock medium. In this study, the mode-I fracture toughness (KIC) was investigated using several soft computing techniques. For this purpose, an extensive literature survey was carried out to obtain a comprehensive database that includes simple and widely used mechanical rock parameters such as uniaxial compressive strength (UCS) and Brazilian tensile strength (BTS). Several soft computing techniques such as artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), gene expression programming (GEP), and multivariate adaptive regression spline (MARS) were attempted to reveal the availability of these methods to estimate the KIC. Among these techniques, it was determined that ANN presents the best prediction capability. The correlation of determination value (R2) for the proposed ANN model is 0.90, showing its relative success. In this manner, the present study can be declared a case study, indicating the applicability of several soft computing techniques for the evaluation of KIC. However, the number of samples for different rock types should be increased to improve the established predictive models in future studies. © 2023 Elsevier B.V., All rights reserved.