Makine Mühendisliği Bölümü

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Citation Count: Koçak, Eyüp; Aylı, Ece; Türkoğlu, Haşmet (2022). "A Comparative Study of Multiple Regression and Machine Learning Techniques for Prediction of Nanofluid Heat Transfer", JOURNAL OF THERMAL SCIENCE AND ENGINEERING APPLICATIONS, Vol. 14, No. 6.
A Comparative Study of Multiple Regression and Machine Learning Techniques for Prediction of Nanofluid Heat Transfer
(2022) Koçak, Eyüp; Aylı, Ece; Türkoğlu, Haşmet; 283455; 265836; 12941
The aim of this article is to introduce and discuss prediction power of the multiple regression technique, artificial neural network (ANN), and adaptive neuro-fuzzy interface system (ANFIS) methods for predicting the forced convection heat transfer characteristics of a turbulent nanofluid flow in a pipe. Water and Al2O3 mixture is used as the nanofluid. Utilizing fluent software, numerical computations were performed with volume fraction ranging between 0.3% and 5%, particle diameter ranging between 20 and 140 nm, and Reynolds number ranging between 7000 and 21,000. Based on the computationally obtained results, a correlation is developed for the Nusselt number using the multiple regression method. Also, based on the computational fluid dynamics results, different ANN architectures with different number of neurons in the hidden layers and several training algorithms (Levenberg-Marquardt, Bayesian regularization, scaled conjugate gradient) are tested to find the best ANN architecture. In addition, ANFIS is also used to predict the Nusselt number. In the ANFIS, number of clusters, exponential factor, and membership function (MF) type are optimized. The results obtained from multiple regression correlation, ANN, and ANFIS were compared. According to the obtained results, ANFIS is a powerful tool with a R-2 of 0.9987 for predictions.
Citation Count: Kaak, Abdul Rahman Sabra...et al. (2024). "A novel CFD-ANN approach for plunger valve optimization: Cost-effective performance enhancement", Flow Measurement and Instrumentation, Vol. 97.
A novel CFD-ANN approach for plunger valve optimization: Cost-effective performance enhancement
(2024) Kaak, Abdul Rahman Sabra; Çelebioğlu, Kutay; Bozkuş, Zafer; Ulucak, Oğuzhan; Aylı, Ece; 265836
This paper introduces a novel computational fluid dynamics-artificial neural network (CFD-ANN) approach that has been devised to enhance the efficiency of plunger valves. The primary emphasis of this research is to achieve an optimal equilibrium between hydraulic flow and geometric configuration. This study is a novel contribution to the field as it explores the flow dynamics of plunger valves using Computational Fluid Dynamics (CFD) and proposes a unique methodology by incorporating Machine Learning (ML) for performance forecasting. An artificial neural network (ANN) architecture was developed using a thorough comprehension of flow physics and the impact of geometric parameters acquired through computational fluid dynamics (CFD). Using optimization, the primary aspects of the Artificial Neural Network (ANN), including the learning algorithm and the number of hidden layers, have been modified. This refinement has resulted in the development of an architecture exhibiting a remarkably high R2 value of 0.987. This architectural design was employed to optimize the plunger valve. By utilizing Artificial Neural Networks (ANN), a comprehensive analysis comprising 1000 distinct configurations was effectively performed, resulting in a significant reduction in time expenditure compared to relying on Computational Fluid Dynamics (CFD). The result was a refined arrangement that achieved maximum head loss, subsequently verified using computational fluid dynamics (CFD) simulations, resulting in a minimal discrepancy of 2.66%. The efficacy of artificial neural networks (ANN) becomes apparent due to their notable cost-efficiency, along with their capacity to produce outcomes that are arduous and expensive to get through conventional optimization research utilizing computational fluid dynamics (CFD).
Citation Count: Özgirgin Yapıcı, Ekin; Aylı, Ece; Türkoğlu, Haşmet (2024). "Analysis of heat transfer enhancement of passive methods in tubes with machine learning", Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Vol. 238, No. 8, pp. 3613-3633.
Analysis of heat transfer enhancement of passive methods in tubes with machine learning
(2024) Özgirgin Yapıcı, Ekin; Aylı, Ece; Türkoğlu, Haşmet; 31329; 265836; 12941
This study investigates the efficacy of machine learning techniques and correlation methods for predicting heat transfer performance in a dimpled tube under varying flow conditions, including the presence of nanoparticles. A comprehensive numerical analysis involving 120 cases was conducted to obtain Nusselt numbers and friction factors, considering different dimple depths and velocities for both pure water and water-Al2O3 nanofluid at 1%, 2%, and 3% volume concentrations. Utilizing the data acquired from the numerical simulations, a correlation equation, SVM ANN architectures were developed. The predictive capabilities of the statistical approach, ANN, and SVM models for Nusselt number distribution and friction factor were meticulously assessed through mean average percentage error (MAPE) and correlation coefficients (R2). The research findings reveal that machine learning techniques offer a highly effective approach for accurately predicting heat transfer performance in a dimpled tube, with results closely aligned with Computational Fluid Dynamics (CFD) simulations. Particularly noteworthy is the superior performance of the ANN model, demonstrating the most precise predictions with an error rate of 2.54% and an impressive R2 value of 0.9978 for Nusselt number prediction. In comparison, the regression model achieved an average error rate of 6.14% with an R2 value of 0.8623, and the SVM model yielded an RMSE value of 2.984% with an R2 value of 0.9154 for Nusselt number prediction. These outcomes underscore the ANN model’s ability to effectively capture complex patterns within the data, resulting in highly accurate predictions. In conclusion, this research showcases the promising potential of machine learning techniques in accurately forecasting heat transfer performance in dimpled tubes. The developed ANN model exhibits notable superiority in predicting Nusselt numbers, making it a valuable tool for enhancing thermal system analyses and engineering design optimization.
Citation Count: Aylı, Ece; Ulucak, Oğuzhan (2020). "ANN and ANFIS Performance Prediction models for Francis type Turbines", Journal of Thermal Sciences and Technology, Vol. 40, No. 1, pp. 87-97.
ANN and ANFIS Performance Prediction models for Francis type Turbines
(2020) Aylı, Ece; Ulucak, Oğuzhan; 265836
Turbines can be operated under partial loading conditions due to the seasonal precipitation fluctuations and due to the needed electrical demand over time. According to this partial working need, designers generate hill chart diagrams to observe the system behavior under different flow rates and head values. In order to generate a hill chart, several numerical or experimental studies have been performed at different guide vane openings and head values which are very time consuming and expensive. In this study, the efficiency prediction of Francis turbines has been performed with ANN and ANFIS methods under different operating conditions and compared with simulation results. The obtained results indicate that it is possible to obtain a hill chart using ANFIS method instead of a costly experimental or numerical tests. ANN and ANFIS parameters which effect the output, have been optimized with trying 100 different cases. 75% of the numerical data set is used for training and 25 % is used for validation as testing data. To asses and compare the performance of multiple ANN and ANFIS models several statistical indicators have been used. Insight to the performance evaluation, it is seen that ANFIS can predict the efficiency distribution with higher accuracy than the ANN model. The developed ANFIS model predicts the efficiency with 1.41% mean average percentage error and 0.999 R-2 value. To the best of the author's knowledge, this is the first study in the literature that ANN and ANFIS are used in order to predict the efficiency distribution of the turbines at different loading conditions.
Citation Count: Ayli, Ece, "Cavitation in Hydraulic Turbines", International Journal of Heat and Technology, Vol. 37, No. 1, pp. 334-344, (March 2019).
Cavitation in Hydraulic Turbines
(Edizioni Ets, 2019) Aylı, Ece; 265836
Hydroenergy is one of the richest and most useful renewable energy sources in the world. Hydropower is a vital source as it is the clean energy source, sustainable and last but not least it is also cost-effective. One of the most important parameters that affect the performance of the hydraulic machines is the cavitation phenomenon, which is defined as the formation of the vapor bubbles in the liquid through any hydraulic turbine. In this paper, hydraulic machines, cavitation, types of cavitation are briefly described. After theoretical studies, analytical and numerical researches about cavitation in hydraulic machinery are discussed extensively. With those studies which are summarized in this paper covers a lot of ground about cavitation on the other hand further studies are needed about cavitation in hydro turbines. Numerical methods provide sufficient predictions for cavitation. However, numerical results should be verified by experimental measurements and detection methods to decide what intensity and which shape of cavitation is hazardous and vital, where the local pressure is lower than the vapor pressure and at which static pressure cavities start to grow and collapse.
Citation Count: Celebioglu, Kutay...et.al. (2023). "Critical decision making for rehabilitation of hydroelectric power plants", Energy Sources, Part A: Recovery, Utilization and Environmental Effects, Vol.45, No.4, pp.10073-10106.
Critical decision making for rehabilitation of hydroelectric power plants
(2023) Celebioglu, Kutay; Aylı, Ece; Ulucak, Oguzhan; Aradağ, Selin; Westerman, Jerry; 265836
Due to their diminishing performance, reliability, and maintenance requirements, there has been a rise in the demand for the restoration and renovation of old hydroelectric power facilities in recent decades. Prior to initiating a rehabilitation program, it is crucial to establish a comprehensive understanding of the power plant’s current state. Failure to do so may result in unnecessary expenses with minimal or no improvements. This article presents a systematic rehabilitation methodology specifically tailored for Francis turbines, encompassing a methodological approach for condition assessment, performance testing, and evaluation of rehabilitation potential using site measurements and CFD analysis, and a comprehensive decision-making process. To evaluate the off-design performance of the turbines, a series of simulations are conducted for 40 different flow rate and head combinations, generating a hill chart for comprehensive evaluation. Various parameters that significantly impact the critical decision-making process are thoroughly investigated. The validity of the reverse engineering-based CFD methodology is verified, demonstrating a minor difference of 0.41% and 0.40% in efficiency and power, respectively, between the RE runner and actual runner CFD results. The optimal efficiency point is determined at a flow rate of 35.035 m3/s, achieving an efficiency of 94.07%, while the design point exhibits an efficiency of 93.27% with a flow rate of 38.6 m3/s. Cavitation is observed in the turbine runner, occupying 27% of the blade suction area at 110% loading. The developed rehabilitation methodology equips decision-makers with essential information to prioritize key issues and determine whether a full-scale or component-based rehabilitation program is necessary. By following this systematic approach, hydroelectric power plants can efficiently address the challenges associated with aging Francis turbines and optimize their rehabilitation efforts.
Citation Count: Çelebioğlu, Kutay...et al. "Exploring the potential of artificial intelligence tools in enhancing the performance of an inline pipe turbine", Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering.
Exploring the potential of artificial intelligence tools in enhancing the performance of an inline pipe turbine
(2024) Çelebioğlu, Kutay; Aylı, Ece; Çetintürk, Hüseyin; Taşçıoğlu, Yiğit; Aradağ, Selin; 265836
In 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.
Citation Count: Aylı, Ece. "Investigation of a Francis Turbine Performance Using CFD and Site Efficiency Measurements", İstanbul: Hefat 2020.
Investigation of a Francis Turbine Performance Using CFD and Site Efficiency Measurements
(2020) Aylı, Ece; 265836
Citation Count: Güzey, Kaan;...et.al. (2023). "Investigation of aerodynamic and aeroacoustic behavior of bio-inspired airfoils with numerical and experimental methods", Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science,
Investigation of aerodynamic and aeroacoustic behavior of bio-inspired airfoils with numerical and experimental methods
(2023) Güzey, Kaan; Aylı, Ülkü Ece; Koçak, Eyup; Aradağ, Selin; 265836; 283455
This article presents numerical and experimental studies on the aerodynamic and aeroacoustic characteristics of the NACA0012 profile with owl-inspired leading-edge serrations for aeroacoustic control. The leading-edge serrations under investigation are in a sinusoidal profile with two main design parameters of wavelength and amplitude. The noise-suppressing ability of sinusoidal serrations is a function of several parameters such as amplitude, wavelength, inflow speed, angle of attack, which are examined in this study. Amplitude (A) and wavelength (λ) of the serration are varied between 1.25 and 2.5, 20 < λ < 60, respectively. The corresponding Reynolds numbers are between 1 and 3 × 105. The angle of attack for each configuration is changed between 4° and 16°. Forty different configurations are tested. According to the results, owl-inspired leading-edge serrations can be used as aeroacoustic control add-ons in blade designs for wind turbines, aircraft, and fluid machinery. Results show that the narrower and sharper serrations have a better noise reduction effect. Overall sound pressure level (SPL) reduces up to 20% for the configuration with the largest amplitude and smaller wavelength. The results also showed that serration amplitude had a distinct effect on aeroacoustic performance, whereas wavelength is a function of amplitude. At the smaller angle of attack values, AOA < 8°, the lift and drag coefficients are almost the same for both clean and wavy profiles. On the other hand, typically for angle of attack values more than 12° (after stall), when the angle of attack is increased, serration adversely affects aerodynamic performance.
Citation Count: Koçak, Eyüp; Aylı İnce, Ülkü Ece; Türkoğlu, Haşmet. "Kanat Profili-Silindir Konfigürasyonunun aerodinamik ve aeroakustik performansının sayısal analizi", 14. Ulusal Tesisat Mühendisliği Kongresi, pp. 908-914, 2019.
Kanat Profili-Silindir Konfigürasyonunun aerodinamik ve aeroakustik performansının sayısal analizi
(2019) Koçak, Eyüp; Aylı İnce, Ülkü Ece; Türkoğlu, Haşmet; 265836
Fanlar, rüzgâr ve su türbinleri gibi birçok akım makinesinde ve uçak gövdesi bileşenlerindeakışınfiziğinin ve akustik performansının anlaşılmasında,kanat profili-silindir konfigürasyonlarının akış performansındanyararlanılmaktadır. Silindirin arkasında meydana gelen kayma tabakası ayrılmaları ve Von Karman girdapları, kanat girişinde parçalanmakta ve birçok küçük yapılar 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 yükseldiğinigöstermiştir
Citation Count: Aylı, E.; Koçak, E.; Türkoğlu, H. (2023). "Machine Learning Based Developing Flow Control Technique Over Circular Cylinders", Journal of Computing and Information Science in Engineering, Vol.23, No.2.
Machine Learning Based Developing Flow Control Technique Over Circular Cylinders
(2023) Aylı, Ece; Koçak, Eyup; Türkoğlu, Haşmet; 265836; 283455; 12941
This 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 R2(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.
Citation Count: Aylı, Ece (2020). "Modeling of mixed convection in an enclosure using multiple regression, artificial neural network, and adaptive neuro-fuzzy interface system models", Proceedings of the iMeche, PartC, Journal of Mechanical Engineering Science, Vol. 234, No. 15, pp. 3078-3093.
Modeling of mixed convection in an enclosure using multiple regression, artificial neural network, and adaptive neuro-fuzzy interface system models
(2020) Aylı, Ece; 265836
In this study, the heat transfer characteristics of laminar combined forced convection through a horizontal duct are obtained with the help of the numerical methods. The effect of the geometrical parameters of the cavity and Reynolds number on the heat transfer is investigated. New heat transfer correlation for hydrodynamically fully developed, laminar combined forced convection through a horizontal duct is proposed with an average error of 6.98% and R-2 of 0.8625. The obtained correlation results are compared with the artificial neural network and adaptive neuro-fuzzy interface system models. Due to the obtained results, good agreement is identified between the numerical results and predicted adaptive neuro-fuzzy interface system results. In conclusion, it is seen that adaptive neuro-fuzzy interface system can predict the Nusselt number distribution with a higher accuracy than the developed correlation and the artificial neural network model. The developed adaptive neuro-fuzzy interface system model predicts the Nusselt number with 1.07% mean average percentage error and 0.9983 R-2 value. The effect of the different training algorithms and their ability to predict Nusselt number distribution are examined. According to the results, the Bayesian regulation algorithm gives the best approach with a 2.235% error. According to the examination that is performed in this study, the adaptive neuro-fuzzy interface system is a powerful, robust tool that can be used with confidence for predicting the thermal performance.
Citation Count: Aylı İnce, Ülkü Ece...et al. "Numerıcal Acoustıc Investıgatıon Of Rod-Aırfoıl Confıguratıon Usıng Ffowcs-Wıllıams-Hawkıngs Equatıons", Uluslarası Isı Bilimi ve Tekniği Kongresi, Kocaeli, 2019.
Numerical Acoustic Investigation of Rod-Airfoil Configuration Using Ffowcs-Williams-Hawkings Equations
(2019) Aylı İnce, Ülkü Ece; Koçak, E.; Türkoğlu, H.; 265836
Citation Count: Kocak, E., Ayli, E., Türkoglu, H., Numerical Analysis of Aerodynamic and Aeroacoustic Characteristics of Subsonic Rectangular Cavity with Different Aspect Ratios, 5th International Anatolian Energy Symposium, 24-26 March, Trabzon, Turkey, 2020.
Numerical Analysis of Aerodynamic and Aeroacoustic Characteristics of Subsonic Rectangular Cavity with Different Aspect Ratios
(2020) Koçak, Eyup; Aylı, Ece; Türkoğlu, Haşmet; 283455; 265836; 12941
Citation Count: Deniz, A.; Aylı, Ece. "Numerical Analysis of Mixed Convection in a Channel with Open Cavity", İstanbul: 5th International Conference on Advances in Mechanical Engineering.
Numerical Analysis of Mixed Convection in a Channel with Open Cavity
(2019) Deniz, A.; Aylı, Ece; 265836
Citation Count: Yapici, Ekin Ozgirgin; Ayli, Ece; Nsaif, Osama (2020). "Numerical investigation on the performance of a small scale solar chimney power plant for different geometrical parameters". JOURNAL OF CLEANER PRODUCTION. Vol. 276.
Numerical investigation on the performance of a small scale solar chimney power plant for different geometrical parameters
(2020) Özgirgin Yapıcı, Ekin; Nsaif, Osama; Aylı, Ece; 265836; 31329
In recent decades, demand for energy has been significantly increased, and considering environmental impacts and the degrading nature of fossil fuels, clean and emission-free renewable energy production has attracted a great deal of attention. One of the most promising renewable energy sources is solar energy due to low cost and low harmful emissions, and from the 1980s, one of the most beneficial applications of solar energy is the utilization of solar chimney power plants (SCPP). A SCPP is a simple and reliable system that consists of three main components; a solar collector, a chimney (tower) and a turbine to utilize electrical energy. Recently, by the advancement in computer technology, the use of CFD methodology for studying SCPP has become an extensive, robust and powerful technique. In light of the above, in this study, numerical simulations of a SCPP through three-dimensional axisymmetric modeling is performed. A numerical model is created using CFD software, and the results are verified with an experimental study from the literature. After ensuring good agreement with the experiments, chimney's and collector's geometric parameters effects and different configurations effects on SCPP performance, simultaneously and additively is investigated. The study introduces an insight to the performance enhancement methods and finding the best configuration of a SCPP model, which will be the basis of a detailed prototyping process. Based on the numerical results, the best configuration of the SCPP has been found as the diverging chimney which enhances the generated power. The results of the study showed that the chimney height and collector radius increase has a positive effect on the power output and efficiency of the system, but when construction and material costs are also considered, each has an optimal value. The maximum impact on the performance is found to be by the chimney tower radius and the collector height and inclination are found to have optimum values considering performance. According to the obtained results, the best performance for the SCPP was obtained with 3.5 m chimney height, 30 cm tower diameter, 400 cm of collector diameter with 6 cm height and zero inclination angle. By the correct selection of the dominant performance parameter which can be done by correctly interpreting the results of this study, "the best" design of a SCPP real scale prototype considering maximum power requirement can be done. (C) 2020 Elsevier Ltd. All rights reserved.
Citation Count: Yapici, Ekin Ozgirgin; Ayli, Ece; Nsaif, Osama (2020). "Numerical investigation on the performance of a small scale solar chimney power plant for different geometrical parameters". JOURNAL OF CLEANER PRODUCTION. Vol: 276.
Numerical investigation on the performance of a small scale solar chimney power plant for different geometrical parameters
(2020) Yapici, Ekin Ozgirgin; Ayli, Ece; Nsaif, Osama; 31329; 265836
In recent decades, demand for energy has been significantly increased, and considering environmental impacts and the degrading nature of fossil fuels, clean and emission-free renewable energy production has attracted a great deal of attention. One of the most promising renewable energy sources is solar energy due to low cost and low harmful emissions, and from the 1980s, one of the most beneficial applications of solar energy is the utilization of solar chimney power plants (SCPP). A SCPP is a simple and reliable system that consists of three main components; a solar collector, a chimney (tower) and a turbine to utilize electrical energy. Recently, by the advancement in computer technology, the use of CFD methodology for studying SCPP has become an extensive, robust and powerful technique. In light of the above, in this study, numerical simulations of a SCPP through three-dimensional axisymmetric modeling is performed. A numerical model is created using CFD software, and the results are verified with an experimental study from the literature. After ensuring good agreement with the experiments, chimney's and collector's geometric parameters effects and different configurations effects on SCPP performance, simultaneously and additively is investigated. The study introduces an insight to the performance enhancement methods and finding the best configuration of a SCPP model, which will be the basis of a detailed prototyping process. Based on the numerical results, the best configuration of the SCPP has been found as the diverging chimney which enhances the generated power. The results of the study showed that the chimney height and collector radius increase has a positive effect on the power output and efficiency of the system, but when construction and material costs are also considered, each has an optimal value. The maximum impact on the performance is found to be by the chimney tower radius and the collector height and inclination are found to have optimum values considering performance. According to the obtained results, the best performance for the SCPP was obtained with 3.5 m chimney height, 30 cm tower diameter, 400 cm of collector diameter with 6 cm height and zero inclination angle. By the correct selection of the dominant performance parameter which can be done by correctly interpreting the results of this study, "the best" design of a SCPP real scale prototype considering maximum power requirement can be done. (C) 2020 Elsevier Ltd. All rights reserved.
Citation Count: Nsaif, O...et al. "Numerical Study of the Influence of Chimney Configurations in a Solar Chimney Power Plant", Uluslararası Isı Bilimi ve Tekniği Kongresi, Kocaeli, 2019.
Numerical Study of the Influence of Chimney Configurations in a Solar Chimney Power Plant
(2019) Nsaif, O.; Al-Rawe, M.; Özgirgin, E.; Aylı İnce, Ülkü Ece; 265836
Citation Count: Aylı İnce, Ülkü Ece; Bayer, Özgür (2020). "Optımızatıon of Vortex Promoter Parameters to Enhance Heat Transfer Rate in Electronıc Equıpment", Journal of Thermal Sicence and Energy Applications, Vol. 12, No. 2.
Optımızatıon of Vortex Promoter Parameters to Enhance Heat Transfer Rate in Electronıc Equıpment
(2020) Aylı İnce, Ülkü Ece; Bayer, Özgür; 265836
In this paper, optimization of the location and the geometry of a vortex promoter located above in a finned surface in a channel with eight heat sources is investigated for a Reynolds number of 12,500 < Re < 27,700. Heat transfer rates and the corresponding Nusselt number distributions are studied both experimentally and numerically using different vortex promoter geometries (square, circular, and triangular) in different locations to illustrate the effect of vortex promoter on the fluid flow. Optimization study considered a range of following parameters: blockage ratio of 0.30<(y/C) < 0.45 and interpromoter distance ratio of 0.2277 <(x/L) < 0.3416. Results show that fins over which rectangular and circular promoters are integrated perform better in enhancing the heat transfer. According to the numerical and experimental results, higher blockage ratios cause significantly higher heat transfer coefficients. According to the observations, as the interpromoter distances increase, shedding gains strength, and more turbulence is created. All vortex promoters enhance heat transfer resulting in lower temperature values on the finned surface for different (y/C) and (x/L) values and Reynolds numbers. The use of promoters enhances the heat transfer, and the decrease in the maximum temperature values is recorded on the finned surface changing between 15% and 27%. The biggest decrease in maximum surface temperature value is 500 K-364 K and observed in circular promoter case with (y/C) = 0.43, (x/L) = 0.3416, and Reynolds numbers of 22,200.
Citation Count: Aylı, Ece. "Passive and Active Control of Acoustic Resonance in Cavity Flows using FWH Equations", İstanbul: Passive and Active Control of Acoustic Resonance in Cavity Flows using FWH Equations 01-03 July 2020.
Passive and Active Control of Acoustic Resonance in Cavity Flows using FWH Equations
(2020) Aylı, Ece; 265836
In the aerospace industry, interior storage carriages, that carry items such as weapons and bombs form cavities. The turbulence-cavity interaction causes significant vibration, sound pressure levels, resonance, and structural problems. Therefore, control methods are can be useful to reduce drag, minimize pressure fluctuations and SPL levels. This work studies the passive flow control methods to reduce the noise induced by the flow over the cavity. For this purpose, cavity leading, and trailing edge wall modifications were made such as inclination, placing a block upstream of the cavity, blowing from the cavity walls. Broadband nature of the noise sources is captured generally with DNS or LES approach. Large Eddy Simulations (LES) is used to compute the flow field to reduce computational cost. ANSYS Fluent software is utilized to solve compressible, two-dimensional, transient subsonic cavity flow. For the determination of sound pressure levels, Ffowcs-Williams–Hawkings (FW-H) integral method is used.

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