Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Assessment of the Quality of Tuffs in Central Anatolia, Turkey: A Quantitative Classification Approach(Acad Sci Czech Republic Inst Rock Structure & Mechanics, 2025-12-03) Koken, Ekin; Ince, IsmailThe growing global demand for dimension stones necessitates efficient and accurate evaluation methods to ensure their optimal use in various industries. To assess their suitability for various dimension stone applications, this study investigates tuffs from Central Anatolia, Turkey. For this purpose, the fundamental physical and mechanical properties of the tuffs were determined in laboratory studies, and a detailed durability assessment was conducted for each rock type. The analysis results indicate that most of the examined rocks are of low quality and more suitable for non-load-bearing applications. Based on the collected data, fuzzy clustering techniques were applied to develop a new classification system, categorising the tuffs into four classes (Class A-D) according to their potential applications. Additionally, a user-friendly MATLAB-based software tool was also developed to facilitate the implementation of the proposed classification system.Article Citation - WoS: 1Citation - Scopus: 1Development of Comprehensive Predictive Models for Evaluating Böhme Abrasion Value (BAV) of Dimension Stones Using Non-Destructive Testing Methods(MDPI, 2024-12-25) Koken, EkinDue to the global demand for dimension stones, fast and reliable evaluation tools are essential for assessing the quality of dimension stones. For this reason, this study aims to develop comprehensive tools for estimating the abrasion resistance of various dimension stones from Turkey. Non-destructive rock properties, including dry density (rho d), water absorption by weight (wa), and pulse wave velocity (Vp), were determined to build a comprehensive database for soft computing analyses. Three predictive models were established using multivariate adaptive regression spline (MARS), M5P, and artificial neural networks (ANN) methodologies. The performance of the models was assessed through scatter plots and statistical indicators, showing that the ANN-based model outperforms those based on M5P and MARS. The applicability of the models was further validated with independent data from the existing literature, confirming that all models are suitable for estimating varying B & ouml;hme abrasion values (BAVs). A MATLAB-based software tool, called B & ouml;hme abrasion calculator (v1.00), was also developed, allowing users to estimate BAV values by inputting adopted non-destructive rock properties. This tool is available upon request, supporting the dimension stone industry and fostering future research in this field.