Köken, Ekin
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Ekin Köken
Koken, E.
Köken, E.
Koken, Ekin
Koken, E.
Köken, E.
Koken, Ekin
Job Title
Arş. Gör.
Email Address
ekin.koken@agu.edu.tr
Main Affiliation
02.07. Malzeme Bilimi ve Nanoteknoloji Mühendisliği
02. Mühendislik Fakültesi
01. Abdullah Gül University
02. Mühendislik Fakültesi
01. Abdullah Gül University
Status
Current Staff
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WoS Researcher ID
Sustainable Development Goals
13
CLIMATE ACTION
0
Research Products
15
LIFE ON LAND
0
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
10
REDUCED INEQUALITIES
0
Research Products
2
ZERO HUNGER
0
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6
CLEAN WATER AND SANITATION
0
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14
LIFE BELOW WATER
0
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11
SUSTAINABLE CITIES AND COMMUNITIES
0
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16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
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5
GENDER EQUALITY
0
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9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
3
Research Products
7
AFFORDABLE AND CLEAN ENERGY
0
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4
QUALITY EDUCATION
0
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1
NO POVERTY
0
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
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3
GOOD HEALTH AND WELL-BEING
0
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
1
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Documents
31
Citations
165
Scholarly Output
40
Articles
34
Views / Downloads
1/2
Supervised MSc Theses
0
Supervised PhD Theses
0
WoS Citation Count
127
Scopus Citation Count
157
WoS h-index
8
Scopus h-index
8
Patents
0
Projects
0
WoS Citations per Publication
3.18
Scopus Citations per Publication
3.93
Open Access Source
22
Supervised Theses
0
| Journal | Count |
|---|---|
| Materials | 4 |
| Geotechnical and Geological Engineering | 3 |
| Konya Journal of Engineering Sciences | 3 |
| Archives of Mining Sciences | 2 |
| Journal of Mining and Environment | 2 |
Current Page: 1 / 6
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40 results
Scholarly Output Search Results
Now showing 1 - 10 of 40
Article Integrated Quantitative Modelling for the Dimension Stone Quality Evaluation: Implications for Sustainable Resource Management(Springer Heidelberg, 2025) Koken, Ekin; Strzalkowski, Pawel; Strzałkowski, PawełThe growing demand for dimensional stones in construction and monument conservation requires fast, repeatable and scientifically valid quality assessment procedures. The present study, in this context, established a solid foundation for quantifying the quality of dimension stones by adopting two quantitative methods: the Suitability Index (SI) and Dimension Stone Field Performance Coefficient (DSFPC). Both methods were coded in the MATLAB environment and implemented for 20 different rock types used in various dimension stone applications in Turkey. Evaluations based on the above-mentioned methods demonstrate that the DSFPC provides a more conservative assessment than the SI method. Additionally, engineering interpretations derived from the SI and DSFPC approaches are compared with recently published classification systems developed for the dimension stone industry. Focusing on this comparison, it is concluded that the adopted methods offer a more holistic evaluation framework compared to the approaches based solely on a single input parameter, such as effective porosity (ne), uniaxial compressive strength (UCS), or B & ouml;hme abrasion value (BAV) of rocks. Furthermore, it is concluded that the adopted methods complement each other by yielding supportive outcomes. The coded methods can be adapted to other lithological series and integrated with spatial information systems to support decision-making in mining and construction sectors. From this point of view, the present study may be considered a case study supporting holistic approaches to sustainable resource management in the dimension stone industry.Article Citation - WoS: 1Assessment of Installed Power for Inclined Belt Conveyors Using Genetic Algorithm and Artificial Neural Networks(Konya Teknik Univ, 2022) Koken, EkinIn this study, the installed power (P inst , kW) of several inclined belt conveyors operating in the mining industry of Turkey was investigated through two soft computing algorithms (i.e., genetic expression programming (GEP) and artificial neural networks (ANN)). For this purpose, the most crucial belt (i.e., belt length (L), belt width (W), belt inclination (alpha)), operational (i.e., belt speed (Vb) b ) and throughput (Q)) and infrastructural (belt weight (Wb) b ) and idler weight (Wid)) id )) features of 42 belt conveyors were collected for each investigated belt conveyor. The collected data was transformed into a comprehensive dataset for soft computing analyses. Based on the GEP and ANN analyses, two robust predictive models were proposed to estimate the P inst . The performance of the proposed models was evaluated using several statistical indicators, and the statistical evaluations demonstrated that the models yielded a correlation of determination (R2) 2 ) greater than 0.95. Nevertheless, the ANN-based model has slightly overperformed in predicting the P inst values. In conclusion, the proposed models can be reliably used to estimate the P inst for the investigated conveyor belts. In addition, the mathematical expressions of the proposed models were given in the present study to let users implement them more efficiently.Article Citation - WoS: 5Citation - Scopus: 6Size Reduction Characterization of Underground Mine Tailings: A Case Study on Sandstones(Springer, 2021) Koken, EkinThe production of construction and building materials starts with reducing the size of natural, industrial, and waste materials. In addition to strength and durability considerations of natural resources recommended by various institutions, size reduction characterization, specific to rock aggregates, has a vital role in their size-related quality. In this study, various sandstones extracted from underground mines located in northwestern Turkey were investigated for size reduction characterizations. Several mineralogical, textural, and physico-mechanical properties were determined for each rock type. Crushability tests were carried out using a laboratory-scale cone crusher for different feeding size fractions, namely + 11.20 - 16.00 mm (size I), + 9.52 - 16.00 mm (size II), and + 6.30 - 16.00 mm (size III). Based on the crushability tests, crushed particles were analyzed, focusing on production yield, size, and shape properties. Each crushability test was also explored for energy consumption arising from varying rock properties of the sandstones. The laboratory test results demonstrated that the degree of rock crushability (DRC) and specific energy consumption (E-cs, kJ/kg) were associated with the Brazilian tensile strength (BTS, MPa) and apparent porosity (n(e), %) of the sandstones. The results also showed that the degree of sorting in mineral constituents, quantified as the sorting coefficient (S-c), affected the DRC. However, mineralogical features of the sandstones have no significant impact on DRC andE(cs). Variations in feeding gradation, irrespective of whether mineralogical, textural, or physico-mechanical properties, have remarkable effects on product flakiness and yields for specific size fractions. In light of the findings obtained, the present study provides knowledge on how the sandstones behave under cone crushing operations.Article Kalabak Tepe Kireçtaşlarının Nihai Taşıma Gücünün Farklı Analiz Yöntemleri ile Araştırılması(2024) Kıncal, Cem; Koken, Ekin; Koca, Tümay Kadakci; Kuruoglu, MehmetFarklı kütle özelliklerine sahip kayaç kütlelerinin taşıma gücünü en doğru şekilde tahmin eden yöntemlerin seçiminde karşılaştırmalı çalışmalar önem kazanmaktadır. Hangi yöntemin daha sağlam sonuçlar verdiği dayandıkları parametrelerle ilişkili olmaktadır. Bu çalışmada, Miyosen yaşlı Kalabak Tepe (İzmir) kireçtaşlarının taşıma gücü incelemesi değişik yöntemler uygulanarak gerçekleştirilmiştir. Kayaç kütle özellikleri Genelleştirilmiş Hoek-Brown yenilme ölçütü dikkate alınarak belirlenmiştir. Taşıma gücü için uygun yöntemlerin belirlenmesinde arazi modeli ve süreksizliklerin konumları dikkate alınmıştır. Kayacın kütle dayanım parametreleriyle birlikte limit analiz veya sonlu elemanlar yöntemlerinin taşıma gücü analizlerinde kullanılması uygun bir yaklaşım olmaktadır. Sonlu elemanlar yöntemiyle kireçtaşlarının nihai taşıma gücü, limit analiz yöntemlerinden elde edilenlerle karşılaştırılmıştır. Sonuç olarak, bazı limit analiz yöntemlerinden elde edilen sonuçlar, sonlu elemanlar ve diğer limit analiz yöntemlerinden elde edilenlerden daha yüksek bulunmuştur. Yöntemler arasındaki bulgu farklılıkları detaylıca tartışılarak yöntemlerin pratik kullanımına ışık tutulmuştur.Article Citation - Scopus: 2Soft Computing Implementations for Evaluating Los Angeles Abrasion Value of Rock Aggregates From Kütahya, Turkey(Szechenyi Istvan University, 2024) Köken, E.The Los Angeles abrasion value (LAAV) of rocks is a critical mechanical aggregate property for designing road infrastructures and concrete quality. However, the determination of this critical aggregate property is labour-intensive and time-consuming and thus, in the literature, there are many predictive models to estimate the LAAV for different rock types. However, most of them are based on classical regression analyses, limiting their broader usage. In this study, several soft computing analyses are performed to develop robust predictive models for the evaluation of LAAV of rocks in the Ilıca region (Kütahya – Turkey). The main motivation for implementing soft computing analyses is that precise predictive models might be useful when exploring suitable rock types that are manufactured in crushing–screening plants. For this purpose, a comprehensive laboratory schedule was established to obtain some inputs for the evaluation of LAAV. As a result of the soft computing analyses, four robust predictive models are developed based on artificial neural networks (ANN), multiple adaptive regression spline (MARS), adaptive neuro-fuzzy inference system (ANFIS) and gene expression programming (GEP) methodologies. The performance of the proposed models is investigated by some statistical indicators such as R2 and RMSE values and scatter plots. As a result, the ANFIS-based predictive model turns out to be the best alternative to estimate the LAAV of the investigated rocks. © 2025 Elsevier B.V., All rights reserved.Article Citation - WoS: 4Citation - Scopus: 5Evaluation of Soft Computing Methods for Estimating Tangential Young Modulus of Intact Rock Based on Statistical Performance Indices(Springer, 2022) Koken, Ekin; Kadakci Koca, TumayThe tangential Young modulus (E-ti) of intact rock is a critical parameter in engineering geological design calculations and rock mass classification systems. The E-ti of various rock types has been successfully estimated by many studies based on numerous soft computing methods in recent years. However, these studies mainly involve a single analysis method or are valid for a limited number of samples. For this reason, this study aimed to compare artificial neural networks (ANN), adaptive neural fuzzy inference system (ANFIS), and Gene expression programming (GEP) methods to estimate the E-ti of various rock types based on 147 datasets collected from the published literature. As a result of the soft computing analyses, three different predictive models were proposed in this study. In the proposed prediction models, rock properties such as dry density (rho(d)), effective porosity (n(e)), P-wave velocity (V-p), and uniaxial compressive strength (UCS) were used. The estimation performance of the proposed models was examined through several performance indices such as coefficient of determination (R-2), root mean square error (RMSE), the variance accounted for (VAF), and mean absolute percent error (MAPE). As a result of statistical analyses, it was determined that the ANFIS model presents a better prediction performance (R-2 = 0.967) than the other methods in the training datasets. On the other hand, the accuracy of the ANFIS model decreased significantly in the test datasets (R-2 = 0.803). Furthermore, the GEP model presented the lowest predictive performance. Finally, considering the overall estimation accuracy of the proposed models, it was concluded that the proposed ANN model with an R-2 of 0.94 could reliably be used to estimate the E-ti of investigated rocks.Article Citation - WoS: 8Citation - Scopus: 12Assessment of Rock Aggregate Quality Through the Analytic Hierarchy Process (AHP)(Springer, 2020) Koken, Ekin; Top, Soner; Ozarslan, AhmetThe present study aimed to assess rock aggregate quality through the Analytic Hierarchy Process (AHP). In the context of the AHP analyses, four rock types (i.e., andesite, basalt, granodiorite, and gabbro), five evaluation criteria, and several technical requirements/suggestions for coarse aggregates related to bituminous paving mixtures were considered. In order to set over the evaluation criteria, detailed laboratory studies were conducted. For this purpose, various mineralogical, physical, and mechanical aggregate properties were determined for each rock type concerning their weathering grades. As a result of the laboratory studies, it was determined that the rock weathering processes have substantial negative impacts on the rock aggregate properties considered in this study. The AHP analysis results indicated that that different rock types have several advantages concerning various evaluation criteria. Based on the general evaluation point (EP) of the rocks, the gabbros were found to have the highest rock aggregate quality (EP = 0.393). In contrast, the andesites had the lowest quality (EP = 0.069). Besides, the basalts (EP = 0.271) and granodiorites (EP = 0.267) presented approximately the same quality for their use in bituminous pavement mixtures. It was also demonstrated that the AHP, with its specific methodology, can be utilized to represent different environmental and mechanical conditions by changing the relative weight of the evaluation criteria. In this way, the pros and cons of different rock types could be revealed quantitatively, which enables related engineers to select proper rock types for their use under different environmental and mechanical conditions. From this point of view, the present study could be declared a case study noted for combining theoretical and practical approaches on bituminous paving mixtures as a sign of rock aggregate quality.Article Geological-Geochemical Signatures of Opal Occurrences in Keciborlu (Isparta-Turkey)(Pamukkale Univ, 2022) Baspinar Tuncay, Ebru; Koken, Ekin; Kuscu, Mustafa; Cengiz, Oya; Aydemir, Fatih; Raimov, Rahmen; Tuncay, Ebru BaspınarSilica-rich solutions, considered as the final products of acidic volcanism, which started from the Late Miocene to throughout the Plio-Quaternary around Isparta, are effective along the main fault observed around the Keciborlu (Isparta) sulfur deposit. Therefore, opal occurrences are intensively observed along this fault zone. Opal occurrences are in various colors such as gray, beige, yellowish, reddish, blackish. Opals with a massive structure, observed as bands, are sharp -edged, conchoidal diffraction, translucent, matte, oily glossy surface opals are iron oxidized. Some opals contain brecciated rock fragments. The locations of the opal occurrences in the field were determined in this study. Using representative samples, structural and textural properties of opals were determined by thin section, scanning electron microscopy analyses, and mineral paragenesis was analyzed via x-ray diffraction and Fourier transform infrared spectroscopy analyses. Geochemical findings revealed chemical compositions. Based on the thin-section studies, it was observed that the opalized samples lost their primary properties due to the effect of hydrothermal solutions and they became iron oxidized, laminated, and argillized. In addition, they contain opaque minerals such as magnetite and hematite. Different micro textures such as amorphous, granular, desert rose, and lepisphere quartz associations were observed in SEM images. In the XRD and FTIR analyzes, it was determined that most of the opals were Opal CT and some of them were defined as Opal C type. Based on the geochemical analyses considering Ba <120 ppm and Ca >200 ppm, the remarkable changes in loss on ignition values, and the relative relationship between C/T ratio and Ga, such hydrothermal alterations in opals the Keciborlu opals were found to have the magmatic origin.Conference Object Citation - WoS: 1Estimation of Cohesion for Intact Rock Materials Using Regression and Soft Computing Analyses(IOP Publishing Ltd, 2024) Koken, E.; Strzalkowski, P.; Kazmierczak, U.; Strzałkowski, P.Shear strength parameters such as cohesion (c) and internal friction angle (phi) are among the most critical rock properties used in the geotechnical design of most engineering projects. However, the determination of these properties is laboring and requires special equipment. Therefore, this study introduces several predictive models based on regression and artificial intelligence methods to estimate the c of different rock types. For this purpose, a comprehensive literature survey is carried out to collect quantitative data on the shear strength properties of different rock types. Then, regression and soft computing analyses are performed to establish several predictive models based on the collected data. As a result of these analyses, five different predictive models (M1-M5) were established. Based on the performance of the established predictive models, the artificial neural network-based predictive model (model 5, M5) was the most suitable choice for evaluating the c for different rock types. In addition, mathematical expressions behind the M5 model are also presented in this study to allow users to implement it more efficiently. In this regard, the present study can be declared a case study showing the applicability of regression and soft computing analyses to evaluate the c of different rock types. However, the number of datasets used in this study should be increased to get more comprehensive predictive models in future studies.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, 2025) 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.
