Köken, Ekin

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Name Variants
Ekin Köken
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
Status
Current Staff
Website
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
INDUSTRY, INNOVATION AND INFRASTRUCTURE Logo

3

Research Products

12

RESPONSIBLE CONSUMPTION AND PRODUCTION
RESPONSIBLE CONSUMPTION AND PRODUCTION Logo

1

Research Products
This researcher does not have a Scopus ID.
Documents

31

Citations

158

Scholarly Output

40

Articles

34

Views / Downloads

135/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

120

Scopus Citation Count

152

WoS h-index

8

Scopus h-index

7

Patents

0

Projects

0

WoS Citations per Publication

3.00

Scopus Citations per Publication

3.80

Open Access Source

22

Supervised Theses

0

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JournalCount
Materials4
Geotechnical and Geological Engineering3
Konya Journal of Engineering Sciences3
Archives of Mining Sciences2
Journal of Mining and Environment2
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Scholarly Output Search Results

Now showing 1 - 10 of 40
  • Article
    Citation - WoS: 5
    Citation - Scopus: 6
    Size Reduction Characterization of Underground Mine Tailings: A Case Study on Sandstones
    (Springer, 2021) Koken, Ekin
    The 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, Mehmet
    Farklı 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: 2
    Soft 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
    Integrated Quantitative Modelling for the Dimension Stone Quality Evaluation: Implications for Sustainable Resource Management
    (Springer Heidelberg, 2025) Koken, Ekin; Strzalkowski, Pawel
    The 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: 1
    Assessment of Installed Power for Inclined Belt Conveyors Using Genetic Algorithm and Artificial Neural Networks
    (Konya Teknik Univ, 2022) Koken, Ekin
    In 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: 4
    Citation - Scopus: 5
    Assessment of Los Angeles Abrasion Value (LAAV) and Magnesium Sulphate Soundness (MWL) of Rock Aggregates Using Gene Expression Programming and Artificial Neural Networks
    (Polska Akad Nauk, Polish Acad Sciences, 2022) Koken, Ekin
    It has been acknowledged that two important rock aggregate properties are the Los Angeles abrasion value (LAAV) and magnesium sulphate soundness (Mwl). However, the determination of these properties is relatively challenging due to special sampling requirements and tedious testing procedures. In this stu-dy, detailed laboratory studies were carried out to predict the LAAV and Mwl for 25 different rock types located in NW Turkey. For this purpose, mineralogical, physical, mechanical, and aggregate properties were determined for each rock type. Strong predictive models were established based on gene expression programming (GEP) and artificial neural network (ANN) methodologies. The performance of the proposed models was evaluated using several statistical indicators, and the statistical analysis results demonstra-ted that the ANN-based proposed models with the correlation of determination (R2) value greater than 0.98 outperformed the other predictive models established in this study. Hence, the ANN-based predictive models can reliably be used to predict the LAAV and Mwl for the investigated rock types. In addition, the suitability of the investigated rock types for use in bituminous paving mixtures was also evaluated based on the ASTM D692/D692M standard. Accordingly, most of the investigated rock types can be used in bituminous paving mixtures. In conclusion, it can be claimed that the proposed predictive models with their explicit mathematical formulations are believed to save time and provide practical knowledge for evaluating the suitability of the rock aggregates in pavement engineering design studies in NW Turkey.
  • Article
    Citation - WoS: 10
    Citation - Scopus: 15
    Investigating the Effects of Feeding Properties on Rock Breakage by Jaw Crusher Using Response Surface Method and Gene Expression Programming
    (Elsevier, 2021) Koken, Ekin; Lawal, Abiodun Ismail
    The present study investigates the effects of feeding properties on rock comminution by a laboratory-scale jaw crusher. For this purpose, detailed crushability tests were carried out on four different rock types to assess their degree of rock crushability (DRC). Various feeding sizes (9.5 - 19 mm) and quantities (500 - 1500 g) were adopted to reveal the choke feeding intensity during crushing actions. The efficiency of feeding properties was investigated through the response surface methodology (RSM). The RSM results demonstrated that the characterized feeding size (F-80, mm) dominates the general size reduction, whereas the feeding quantity (m(f), g) is associated with the crushing energy consumption and product flakiness. Therefore, the choke feeding intensity has a direct relation to the m(f) and F-80. In addition, novel gene expression programming (GEP) models were employed to generate empirical formulations to predict the DRC parameters. The established GEP models have a satisfactory estimation capability. Therefore, the DRC of the investigated rocks can be optimized through the proposed GEP models based on the coupling variables of m(f) and F-80. (C) 2021 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights reserved.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 2
    Estimating Uniaxial Compressive Strength of Pyroclastic Rocks Using Soft Computing Techniques
    (Shahrood Univ Technology, 2024) Koken, Ekin
    In this study, several soft computing analyses are performed to build some predictive models to estimate the uniaxial compressive strength (UCS) of the pyroclastic rocks from central Anatolia, Turkey. For this purpose, a series of laboratory studies are conducted to reveal physico-mechanical rock properties such as dry density (rho d), effective porosity (ne), pulse wave velocity (Vp), and UCS. In soft computing analyses, rho d, ne, and Vp are adopted as the input parameters since they are practical and cost-effective non-destructive rock properties. As a result of the soft computing analyses based on the classification and regression trees (CART), multiple adaptive regression spline (MARS), adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANN), and gene expression programming (GEP), five robust predictive models are proposed in this study. The performance of the proposed predictive models is evaluated by some statistical indicators, and it is found that the correlation of determination (R2) value for the models varies between 0.82 - 0.88. Based on these statistical indicators, the proposed predictive models can be reliably used to estimate the UCS of the pyroclastic rocks.
  • Conference Object
    An Experimental Investigation on Rock Crushability Using Jaw and Cone Crushers
    (Baski, 2019) Köken, E.; Bilen, Mehmet; Özarslan, Ahmet; Baris, Kemal
    This study covers the investigation of rock crushability using laboratory-scale cone and jaw crushers for five types of hardrocks. For this purpose, physico?mechanical properties of the investigated rocks are determined. Aggregate samples with a particle size range of 10.00 - 14.00 mm are prepared for crushability tests. After performing crushability tests, crushed particles are sieved and considering sieve analysis results, crushability indices are identified for each rock and crusher type. The performance of the crushers concerning their experimental setup is investigated by Taggart method. It is achieved from crushability tests that, the performance of the cone crusher is approximately two times better than the one of the jaw crusher for their experimental setups. The crushing time (Tc) seems to increase with increasing in rock strength properties. Furthermore, remarkable relationships are obtained between several rock properties and crushability test results. It can be claimed that crushability of rocks are dependent upon crusher type, setup of crushing process, rock strength as well as the mineral hardness. Considering these types of variables, higher achieving benefits of aggregate production could be satisfied at lower costs. © 2020 Elsevier B.V., All rights reserved.
  • Article
    Citation - WoS: 8
    Citation - Scopus: 8
    Guidelines for Natural Stone Products in Connection With European Standards
    (MDPI, 2023) Strzalkowski, Pawel; Koken, Ekin; Sousa, Luis
    The selection of ornamental stones for specific applications requires technical guidance since it should be based on the durability, service life, and aesthetic value of the stones. In most cases, these fundamentals provide quantitative data on the usability and performance of ornamental stones. The present study attempts to put forward a quantitative classification system for natural stone products concerning critical rock properties. For this purpose, fundamental physical and mechanical rock properties are listed based on European standards. Then, minimum limit values are proposed for different applications of natural stone products based on retrospective analyses of numerous ornamental stone applications. The suggested limit values based on several physical and mechanical rock properties can guide relevant engineers to initially consider possible rock types for use as natural stones in a wide range of applications. In this context, it is believed that the present study contributes to the natural stone industry by discussing the minimum limit values for the consideration of a wide range of rock types possibly usable in the dimension stone industry.