WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653
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Article Citation - WoS: 3Citation - Scopus: 4Numerical Analysis of a Commercial Display Cabinet With Air Curtain(Gazi Univ, Fac Engineering Architecture, 2011) Caliskan, Sinan; Altunok, Taner; Altunok, Taner; Baskaya, Senol; Gungunes, H. Murat; Makine MühendisliğiMaintaining food temperatures below critical values is the important maximising the high quality display life of chilled foods. Air curtains are especially used in stores and retailer supermarkets as barrier systems to seperate inner and outer spaces from each other. For both air quality and energy saving, it is crucial that the air transfer between these two spaces are at minimum. Minimization of air transfer between inner and outer spaces, not only decreases heat transfer but also stabilizes the humidity balance. In this study, numerical analysis of a commercial display cabinet has been carried out. For this purpose PHOENICS, a computational fluid dynamics code, is utilized. Optimum jet system conditions for each of the one jet, two jet and there jet systems has been modified according to temperature change of the air, and comparisons among them have been made. The results indicate that, the results the both CFD analysis and experimental results are almost equal and refrigeration systems with three jets is required to obtain the necessary temperature values to keep products fresh in display cabinets, especially because they can distribute temperature in a homogeneous way, meaning that the temperature value is the best ideal system at every point in the cabinet with three jets.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 - Scopus: 1Experimental and Numerical Analysis of Flow Over a Pickup Truck(Begell House inc, 2021) Ince, Ibrahim Timucin; Mercan, Hatice; Onur, NevzatThe drag forces and the overall drag coefficient of a typical pickup truck are investigated experimentally and the 3D numerical analysis is performed. A detailed 1/4-scale model is constructed and experiments are performed at Reynolds numbers around 2 x 10(6) in the Ankara Wind Tunnel (ART). The experimental study is divided into two stages: in the first stage the pressure distribution along the symmetry axis is measured and in the second stage the drag forces and overall drag coefficient are measured at five different wind speeds. The measured data are compared with the 3D numerical simulation performed in FLUENT. The turbulence standard, realizable, and RNG k-epsilon models, the standard and SST k-omega models, and finally the RSM are compared for three near-wall treatments: standard wall function, nonequilibrium wall function, and enhanced wall function. The comparison revealed that for lower velocities the best turbulence model-wall treatment couple is the realizable k-epsilon model with Reynolds stress model with standard wall function, whereas for higher velocities the standard k-epsilon turbulence model is observed to be more compatible with experimental data. The highest pressure value is measured in front of the pickup truck and the lowest pressure value is evaluated at the rim where the windshield and the roof meet.Article Citation - WoS: 6Citation - Scopus: 6Mitigating Cavitation Effects on Francis Turbine Performance: a Two-Phase Flow Analysis(Pergamon-elsevier Science Ltd, 2025) Altintas, Burak; Ayli, Ece; Celebioglu, Kutay; Aradag, Selin; Tascioglu, YigitDue to their ability to operate over a wide range of flow rates and generate high power, Francis turbines are the most widely used of hydroturbine type. Hydraulic turbines, are designed for specific flow and head conditions tailored to site conditions. However, Francis turbines can also be operated outside of design conditions due to varying flow and head values. Operation outside of design conditions can lead to cavitation. In this study, singlephase steady-state an alyses were conducted initially to examine cavitation in detail, followed by two-phase transient analyses. The results obtained from these analyses were compared to determine the cavitation characteristics of the designed turbine. The steady-state simulation results indicate the occurrence of cavitation, including traveling bubble and draft tube cavitation, under overload operating conditions. However, these cavitation characteristics are not observed in the two-phase transient simulation results under the same operating conditions. Additionally, the turbine efficiency is predicted to be higher in the transient simulation results. This is attributed to the frozen rotor interface used in the steady-state simulations, which over predicts flow irregularities. The reduced flow irregularities in the transient results have resulted in lower cavitation and losses, leading to higher predicted turbine efficiency.Article Enhancing Efficiency of an Old Hydropower Plant Turbine Through a Mutual Runner Design and Component Optimization(Sage Publications Ltd, 2025) Seydim, Sila; Yildirim, Gozde; Ulucak, Oguzhan; Buyuksolak, Fevzi; Ejder, Beril; Kantar, Ece Nil; Celebioglu, KutayThis paper presents a systematic approach to the rehabilitation process of Sar & imath;yar HEPP, a hydroelectric power plant that has been operational for more than 50 years. Units 1 and 2 (U1-U2) were originally designed with a head of 93 m and a turbine power of 48.5 MW, while Units 3 and 4 (U3-U4) were designed with a lower head of 76.5 m but the same turbine power of 48.5 MW. A methodology combining reverse engineering and CFD analysis is developed to identify and evaluate the critical parameters that have an impact on the existing turbine performance. A hybrid design is proposed to replace the existing two different types of turbines, which reduces manufacturing costs and design time. The performance of the new hybrid design is evaluated in detail with CFD analysis. For both existing and hybrid design, steady and unsteady analyses are performed. For all of the situations hill charts are obtained and the comparison of the old and new hybrid design is discussed in detail. The results show that the new design has improved the efficiency of the turbine and the power plant, resulting in a 14.2% efficiency increase in U1-U2 and a 21% system efficiency improvement in U3-U4. This study provides a guide to designers and practitioners for the rehabilitation of hydroelectric power plants.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: 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: 4Citation - Scopus: 6Case Study on Thermal Optimization of Oil Immersed Transformer Used in Solar Power Plant Based on Genetic Algorithm and Computational Fluid Dynamics(Vinca inst Nuclear Sci, 2023) Iskender, Ires; Yukselen, EmirTransformers are one of the most capital investments in the solar power generation. Their safe and stable operations in the electrical networks are important. The main failure factor of transformers is the high temperature generated by the losses during operation, which increases the probability of insulation damage that significantly affects the useful life of transformer. Considering the importance of oil temperature and its effects on the life of the transformer, a numerical method is developed in this paper to optimize the cooling system of the transformer. In this regard, genetic algorithm is used as an optimization method to minimize the total cost of the cooling system while maintaining the required thermal conditions of the transformer. A comprehensive parametric study is carried out among the effective cooling geometry parameters using 3-D electromagnetic and thermal models of the photovoltaic transformer to evaluate and analyze the temperature distribution. The accuracy and feasibility of the proposed method is established by comparing the numerical results with those obtained from the experimental test. The results of the proposed method are found to be in a good agreement with the experimental and simulation results.Article Citation - WoS: 13Citation - Scopus: 14A Novel Cfd-Ann Approach for Plunger Valve Optimization: Cost-Effective Performance Enhancement(Elsevier Sci Ltd, 2024) Kaak, Abdul Rahman Sabra; Celebiog, Kutay; Bozkus, Zafer; Ulucak, Oguzhan; Ayli, Ece; Çelebioğlu, KutayThis 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).Article Citation - WoS: 5Citation - Scopus: 6Prediction of the Heat Transfer Performance of Twisted Tape Inserts by Using Artificial Neural Networks(Korean Soc Mechanical Engineers, 2022) Kocak, Eyup; Ayli, EceA numerical study is undertaken to investigate the effect of twisted tape inserts on heat transfer. Twisted tapes with various aspect ratios and single, double, and triple inserts are placed inside a tube for Reynolds numbers ranging from 8000 to 12000. Numerical results show that the tube with a twisted tape and different numbers of tape is more effective than the smooth tube in terms of thermo-hydraulic performance. The highest heat transfer is achieved with the triple insert, with the highest turning number and an increment of 15 %. Then, an artificial neural network (ANN) model with a three-layer feedforward neural network is adopted to obtain the Nusselt number on the basis of four inputs for a heated tube with a twisted insert. Several configurations of the neural network are examined to optimize the number of neurons and to identify the most appropriate training algorithm. Finally, the best model is determined with one hidden layer and thirteen neurons in the layer. Bayesian regulation is chosen as the training algorithm. With the optimized algorithm, excellent precision for measuring the output is provided, with R2 = 0.97043. In addition, the optimized ANN architecture is applied to similar studies in the literature to predict the heat transfer performance of twisted tapes. The developed ANN architecture can predict the heat transfer enhancement performance of similar problems with R2 values higher than 0.93.