Aylı, Ülkü Ece
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Name Variants
Ayli, Ece
Aylı, Ece
Aylı İnce, Ülkü Ece
Ayli, Ulku Ece
Aylı, Ece
Aylı İnce, Ülkü Ece
Ayli, Ulku Ece
Job Title
Doç. Dr.
Email Address
eayli@cankaya.edu.tr
Main Affiliation
06.06. Makine Mühendisliği
Makine Mühendisliği
06. Mühendislik Fakültesi
01. Çankaya Üniversitesi
Makine Mühendisliği
06. Mühendislik Fakültesi
01. Çankaya Üniversitesi
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Files
Sustainable Development Goals
11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
3
GOOD HEALTH AND WELL-BEING
2
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
3
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
14
LIFE BELOW WATER
0
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
1
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
1
NO POVERTY
0
Research Products
4
QUALITY EDUCATION
0
Research Products
5
GENDER EQUALITY
0
Research Products
10
REDUCED INEQUALITIES
0
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
15
LIFE ON LAND
0
Research Products
7
AFFORDABLE AND CLEAN ENERGY
18
Research Products
13
CLIMATE ACTION
2
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
Research Products
2
ZERO HUNGER
0
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output
45
Articles
35
Views / Downloads
2921/705
Supervised MSc Theses
2
Supervised PhD Theses
0
WoS Citation Count
213
Scopus Citation Count
233
WoS h-index
8
Scopus h-index
8
Patents
0
Projects
0
WoS Citations per Publication
4.73
Scopus Citations per Publication
5.18
Open Access Source
11
Supervised Theses
2
| Journal | Count |
|---|---|
| Journal of Thermal Science and Engineering Applications | 3 |
| Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science | 3 |
| Journal of Thermal Engineering | 3 |
| 5th International Anatolian Energy Symposium | 2 |
| Journal of Computing and Information Science in Engineering | 2 |
Current Page: 1 / 7
Scopus Quartile Distribution
Competency Cloud
33 results
Scholarly Output Search Results
Now showing 1 - 10 of 33
Article Citation - WoS: 2Citation - Scopus: 1Exploring the Potential of Artificial Intelligence Tools in Enhancing the Performance of an Inline Pipe Turbine(Sage Publications Ltd, 2024) Celebioglu, Kutay; Ayli, Ece; Cetinturk, Huseyin; Tascioglu, Yigit; Aradag, SelinIn this study, investigations were conducted using computational fluid dynamics (CFD) to assess the applicability of a Francis-type water turbine within a pipe. The objective of the study is to determine the feasibility of implementing a turbine within a pipe and enhance its performance values within the operating range. The turbine within the pipe occupies significantly less space in hydroelectric power plants since a spiral casing is not used to distribute the flow to stationary vanes. Consequently, production and assembly costs can be reduced. Hence, there is a broad scope for application, particularly in small and medium-scale hydroelectric power plants. According to the results, the efficiency value increases on average by approximately 1.5% compared to conventional design, and it operates with higher efficiencies over a wider flow rate range. In the second part of the study, machine learning was employed for the efficiency prediction of an inline-type turbine. An appropriate Artificial Neural Network (ANN) architecture was initially obtained, with the Bayesian Regularization training algorithm proving to be the best approach for this type of problem. When the suitable ANN architecture was utilized, the prediction was found to be in good agreement with CFD, with an root mean squared error value of 0.194. An R2 value of 0.99631 was achieved with the appropriate ANN architecture.Article Citation - WoS: 3Citation - Scopus: 6A Comprehensive Review of Cyclone Separator Technology(Wiley, 2024) Ayli, Ece; Kocak, EyupThis review article examines the working principles, optimal dimensions, effects of key parameters, and the results of experimental/numerical studies on cyclone separators. Investigations have been conducted on the effects of parameters such as vortex finder diameter, conical part diameter, cyclone separator diameter, cylinder height, inlet height, inlet width, vortex finder length, and cyclone total length on efficiency, performance, and pressure drop. Furthermore, the article explores current modifications and efforts to improve efficiency. These modifications include adding water nozzles, inserting ribs, employing double-stage cyclones, incorporating additional inlets, using finned cylinder bodies, adding extra top inlets, introducing liquid jets, employing helical roof inlets, adding laminarizers, incorporating internal spiral vanes, and employing slotted vortex finders. While serving as a guide to optimize the design and performance of cyclone separators, this article emphasizes new and innovative approaches to enhance their industrial applicability. By compiling studies conducted from conceptual birth to the present, the aim of this article is to serve as a guidebook.Article Citation - WoS: 8Citation - Scopus: 8Supervised Learning Method for Prediction of Heat Transfer Characteristics of Nanofluids(Korean Soc Mechanical Engineers, 2023) Kocak, Eyup; Ayli, EceThis study focuses on the alication and investigation of the predictive ability of artificial intelligence in the numerical modelling of nanofluid flows. Numerical and experimental methods are powerful tools from an accuracy point of view, but they are also time- and cost-consuming methods. Therefore, using soft-computing techniques can improve such CFD drawbacks by patterning the CFD data. After obtaining the aropriate ANN and ANFIS architecture using the CFD data, many new data can be created without requiring numerical and experimental methods. In the scope of this research, the FCM-ANFIS and ANN methods are used to predict the thermal behaviour of the turbulent flow in a heated pipe with several nanoparticles. A parametric CFD study is carried out for water-TiO2, water-CuO, and water-SiO2 nanofluid through a pipe. The Reynolds number is varied between 7000 and 15000, and the nanofluid concentration is varied between 0.25 % and 4 %. The effects of using nanofluid on local values of Nusselt number and shear stress distribution were investigated. Numerical results indicate that with the increasing nanoparticle volume fraction of nanofluid, the average Nusselt number increases, but the required pumping power also increases. The obtained soft computing results demonstrate that the FCM clustering ANFIS has given better results both in training and testing when it is compared to the ANN architecture with an R-2 of 0.9983. Regarding this, the FCM-ANFIS is an excellent candidate for calculating the Nusselt number in heat transfer problems.Article Dikdörtgen Kesitli Kanatçıkların Isı Transferine Olan Etkisi: Derleme Makalesi(2018) Aylı, Ece; İnce, EnderBirçok mühendislik probleminde ısı transferi oranları önemli bir etkiye sahiptir. Otomotiv, havalandırma, elektronik soğutma, hava aracı gibi birçok endüstriyel uygulama alanında ısı artımı, ekipmanlarda fazla ısınmaya neden olarak sistem hatalarına, kısa makine ömrüne, güvenilirliğin düşmesine ve bakım ihtiyacının artmasına neden olmaktadır. Bu tip problemlerin önüne geçilmesinde pasif soğutma teknikleri sıklıkla kullanılmaktadır. Bu derleme makalesinde yüksek verim ve düşük maliyet ile ısı transferi iyileştirmesi sağlayan pasif soğutma tekniklerinden olan dikdörtgen kanatçıklar araştırılmıştır. Ayrıca dikdörtgen kanatçıkların eğimli, delikli, aralıklı, hizalı ve kaydırılmış olarak kullanılmasının ısı transferine olan etkilerinin araştırıldığı birçok makale de özetlenmiştir. Kanatçıklı yapılar ile ısı transferini arttırmak için tasarımcılar, kanatçık uzunluğu, kanatçık şekli, kanatçık genişliği, kanatçık sayısı, kanatçıklar arası mesafeler gibi birçok parametreyi optimize etmek mecburiyetindedir. Bu optimizasyon sürecinde deneyim sahibi olmayan bir tasarımcı, ısı transferini arttırmak yerine, tasarladığı kanatçıklı yapı ile gelen havanın ısınan hava ile karışmasını engelleyip ısı transferi üzerinde tam tersi etki yaratabilmektedir. Bu derleme makalesi ıs transferiini dikdörtgen kanatçık kullanarak maksimize etmek isteyen tasarımcılar için bir rehber niteliğindedir ve literatürde bu konu ile yapılmış geniş bir spektrumu taramaktadır.Article Citation - WoS: 2Numerical Investigation of Rod-Airfoil Configuration Aeroacoustic Characteristics Using Ffowcs-Williams Equations(Yildiz Technical Univ, 2021) Kocak, Eyup; Turkoglu, Hasmet; Ayli, EceThe rod-airfoil configuration is a fundamental study to understand sound generation processes and the acoustic phenomena in the application of turbines, fans, and airfoils. In the present research, the noise that is originated by the rod-airfoil configuration is examined using numerical methods which are Large Eddy Simulation (LES), and Reynolds Averaged Navier Stokes (RANS) models, coupled with an FFOWCS-WILLIAMS-HAWKINGS (FW-H) technique. For the RANS method, k-omega SST and Spalart Allmaras (S-A) turbulence models are utilized in order to investigate the capability of different models for the analysis of the aeroacoustic flow field. The ANSYS FLUENT solver is chosen to carry out the numerical simulations. The examined rod and chord diameter Reynolds numbers are 48000 and 480000, respectively and the Mach number is 0.2. Results are obtained for both in the near field and acoustic far-field. The obtained numerical results are verified with an experimental study from the literature, and the results of both approaches are compared with each other and the experiment. Comparisons are performed for mean velocity profiles in the rod and airfoil wakes, pressure spectra and power spectral density. The results obtained show that LES is preferable for this problem as it is capable of capturing the flow separation, reattachments, vortex street, and various length scales of turbulence. Although both RANS and LES methods provide a consistent flow field with experimental methods, the RANS approach overestimates the vortex shedding frequency and Strouhal number. The RANS model predicts the flow field well; however, it overestimates the noise spectra. The LES model predicts satisfactory acoustic spectra.Article Kanat Profili-Silindir Konfigürasyonunun Aerodinamik ve Aeroakustik Performansının Sayısal Analizi(2021) Türkoğlu, Haşmet; Ayli, Ece; Koçak, EyupFanlar, rüzgâr ve su türbinleri gibi birçok akım makinesinde ve uçak gövdesi bileşenlerinde akışın fiziğinin ve akustik performansının anlaşılmasında, kanat profilisilindir konfigürasyonlarının akış performansından yararlanılmaktadır. Silindirin arkasında meydana gelen kayma tabakası ayrılmaları ve Von Karman girdapları, kanat girişinde parçalanmakta ve birçok küçük yapı meydana getirmektedir. Ortaya çıkan akış-katı yüzey etkileşimine bağlı olarak gürültü ve titreşim meydana gelmektedir. Akım makinelerinde geniş bant gürültüsünün en önemli sebebi, türbülanslı akış ve stator kanat giriş ucu etkileşimidir. Bundan dolayı akım makineleri gürültüsünün analizi için, kanat profili-silindir konfigürasyonu modellemesi yapılır. Bu çalışmada, kanat profili dairesel silindirin iz bölgesine yerleştirilerek sayısal simülasyonlar yapılmıştır. Simülasyonlar için Large Eddy Simulation (LES) metodu kullanılmıştır. Sayısal sonuçlar literatürdeki deneysel çalışmalar ile karşılaştırılarak sonuçlar doğrulandıktan sonra, farklı çaplardaki silindirler için simülasyonlar yapılarak, silindir çapının girdap oluşum bölgesi, akış birleşme noktası, akış ayrılma noktası, basınç dağılımı ve ses basınç seviyesi üzerindeki etkileri incelenmiştir. Elde edilen sonuçlar, Strouhal sayısındaki artış ile ses basınç seviyelerinin yükseldiğini göstermiştir.Article Citation - WoS: 6Citation - Scopus: 7Machine Learning Based Developing Flow Control Technique Over Circular Cylinders(Asme, 2023) Turkoglu, Hasmet; Ayli, Ece; Kocak, EyupThis paper demonstrates the feasibility of blowing and suction for flow control based on the computational fluid dynamics (CFD) simulations at a low Reynolds number flows. The effects of blowing and suction position, and the blowing and suction mass flowrate, and on the flow control are presented in this paper. The optimal conditions for suppressing the wake of the cylinder are investigated by examining the flow separation and the near wake region; analyzing the aerodynamic force (lift and drag) fluctuations using the fast Fourier transform (FFT) to separate the effects of small-scale turbulent structures in the wake region. A method for stochastic analysis using machine learning techniques is proposed. Three different novel machine learning methods were applied to CFD results to predict the variation in drag coefficient due to the vortex shedding. Although, the prediction power of all the methods utilized is in the acceptable accuracy range, the Gaussian process regression (GPR) method is more accurate with an R-2(coefficient of determination) > 0.95. The results indicate that by optimizing the blowing and suction parameters like mass flowrate, slot location, and the slot configuration, up to 20% reduction can be achieved in the drag coefficient.Article Citation - WoS: 4Citation - Scopus: 4Performance Optimization of Finned Surfaces Based on the Experimental and Numerical Study(Asme, 2023) Ayli, Ece; Kocak, Eyup; Turkoglu, HasmetThis paper presents the findings of numerical and experimental investigations into the forced convection heat transfer from horizontal surfaces with straight rectangular fins at Reynolds numbers ranging from 23,600 to 150,000. A test setup was constructed to measure the heat transfer rate from a horizontal surface with a constant number of fins, fin width, and fin length under different flow conditions. Two-dimensional numerical analyses were performed to observe the heat transfer and flow behavior using a computer program developed based on the openfoam platform. The code developed was verified by comparing the numerical results with the experimental results. The effect of geometrical parameters on heat transfer coefficient and Nusselt number was investigated for different fin height and width ratios. Results showed that heat transfer can be increased by modifying the fin structure geometrical parameters. A correlation for Nusselt number was developed and presented for steady-state, turbulent flows over rectangular fin arrays, taking into account varying Prandtl number of fluids such as water liquid, water vapor, CO2, CH4, and air. The correlation developed predicts the Nusselt number with a relative root mean square error of 0.36%. This research provides valuable insights into the effects of varying Prandtl numbers on the efficiency of forced convection cooling and will help in the design and operation of cooling systems. This study is novel in its approach as it takes into account the effect of varying Prandtl numbers on the heat transfer coefficient and Nusselt number and provides a correlation for the same. It will serve as a valuable reference for engineers and designers while designing and operating cooling systems.Article An Innovative Showcase of Similarity Methods for Accelerated Turbine Design Processes and Cost-Effective Solutions(Taylor & Francis Ltd, 2025) Kantar, Ece Nil; Ayli, Ece; Celebioglu, KutayThis study aims to design a containerized Francis-type turbine for installation on drinking water pipelines equipped with pressure-reducing equipment, enabling energy recovery from untapped hydraulic resources. The turbine, designed to operate unmanned and housed within a container, represents an innovative approach to harnessing residual energy in drinking water pipelines. The research methodology leverages similarity laws derived from a previously developed high-efficiency turbine facility as a foundation for the preliminary design. This approach diverges from conventional turbine design methods, offering significant time and cost efficiencies. It should be noted that similarity laws were used only for the preliminary dimensioning of the scale turbine. Following this initial design, design optimizations were carried out based on CFD, focusing on components such as the runner, to enhance performance and achieve the required power output without cavitation at the specified flow rate and head. The results demonstrate that the application of similarity laws expedites the design process while maintaining high efficiency, effectively addressing the unique constraints of the operational environment. Additionally, the study provides a comprehensive analysis of the advantages and limitations of employing similarity in turbine design. In conclusion, this research not only exemplifies a novel turbine design methodology that ensures operational similarity but also serves as a practical guide for reducing costs and design timelines in small hydropower applications.This now clearly states that similarity was used for the preliminary dimensioning, followed by optimization based on CFD.Article Citation - WoS: 4Citation - Scopus: 4Artificial Neural Networks for Predicted Bending Properties of Additively Manufactured Pyramidal Lattice Truss Core Sandwich Structures(Elsevier, 2025) Karagozlu, Cem Onat; Ayli, Ece; Tanabi, Hamed; Sabuncuoglu, BarisAn Artificial Neural Network (ANN) model is developed to predict the mechanical behavior of pyramidal lattice truss core sandwich structures under bending load. The development process aims to optimize material use, enhance structural efficiency, and reduce analysis time for the developed ANN model. Key phases include specimen fabrication via additive manufacturing, experimental testing in four-point bending, and validation of the finite element model (FEM). Experimental tests on five specimens validated FEM simulations with a 4.5 % error rate. The ANN, trained on FEM data, accurately predicts reaction forces and stress components (sigma,, sigma 2, tau,2). Comparison of training algorithms (LM, Levenberg-Marquardt, BR, Bayesian Regularization, SCG, Scaled Conjugate Gradient) highlights LM's superior performance in convergence and MSE reduction (max. MSE value: 2.287), while BRexcels in generalization and robustness. Scaled Conjugate Gradient's performance was lower than the others. The ANN demonstrates high accuracy within the training range but shows limitations in extrapolation. Overall, this ANN model offers engineers a rapid and precise tool for predicting the mechanical behavior of these sandwich structures, reducing reliance on time-consuming FEM simulations and facilitating efficient design optimization across various engineering applications.
