Makine Mühendisliği Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/263
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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 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: 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.Article Citation - WoS: 1Citation - Scopus: 1Performance Determination of Axial Wind Tunnel Fan With Reverse Engineering, Numerical and Experimental Methods(Asme, 2022) Ayli, Ece; Kocak, EyupIn today's technology, in case of the need for rehabilitation, renovation, or damage, it is necessary to recover the problems quickly with a cost-effective approach. In the case of destructive failure, or misdesign of the devices, replacing the problematic part with the new design is crucial. In order to substitute the related part with the efficient one, reverse engineering (RE) methodology is utilized. In this paper, from the perspective of engineering implementation and based on the idea of reverse engineering, axial wind tunnel fan is rehabilitated using numerical and experimental methods. The current study is focused on an axial pressurization fan placed into Cankaya University Mechanical Engineering Laboratory wind tunnel that has firm guaranteed specifications of 5.55 m(3)/s airflow capacity. The measurements performed during experiments showed that the fan provides less than 60% airflow compared with firm guaranteed specifications. In order to determine the problems of the existing fan, a reverse engineering methodology is developed, and the noncontact data acquisition method is used to form a computer aided drawing (CAD) model. A computational fluid dynamics (CFD) methodology is developed to analyze existing geometry numerically, and results are compared with an experimental study to verify numerical methodology. According to the results, the prediction accuracy of the numerical method can attain 92.95% and 96.38% for flowrate and efficiency, respectively, at the maximum error points.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 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 Citation - WoS: 4Citation - Scopus: 4Investigation of Aerodynamic and Aeroacoustic Behavior of Bio-Inspired Airfoils With Numerical and Experimental Methods(Sage Publications Ltd, 2024) Kocak, Eyup; Aradag, Selin; Guzey, Kaan; Ayli, Ulku EceThis 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 (& lambda;) of the serration are varied between 1.25 and 2.5, 20 < & lambda; < 60, respectively. The corresponding Reynolds numbers are between 1 and 3 x 10(5). The angle of attack for each configuration is changed between 4 & DEG; and 16 & DEG;. 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 & DEG;, 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 & DEG; (after stall), when the angle of attack is increased, serration adversely affects aerodynamic performance.Article Citation - WoS: 4Citation - Scopus: 4Critical Decision Making for Rehabilitation of Hydroelectric Power Plants(Taylor & Francis inc, 2023) Westerman, Jerry; Celebioglu, Kutay; Ayli, Ece; Ulucak, Oguzhan; Aradag, SelinDue 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 m(3)/s, achieving an efficiency of 94.07%, while the design point exhibits an efficiency of 93.27% with a flow rate of 38.6 m(3)/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.Article Citation - WoS: 9Citation - Scopus: 10Solar Chimney Power Plant Performance for Different Seasons Under Varying Solar Irradiance and Temperature Distribution(Asme, 2021) Tareq, Maisarh; Ozgirgin, Ekin; Ayli, Ulku EceOne 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). Recently, with the advancement in computer technology, the use of computational fluid dynamics (CFD) methodology for studying SCPP has become an extensive, robust, and powerful technique. In light of the above, in this study, numerical simulations of an 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. The amount of solar radiation and surrounding weather (ambient temperature) were analyzed, and the effects of the irradiance and air temperature on the output power of the SCPP were studied. Ambient temperature is considered as one of the most important factors that influence collector efficiency in a negative or a positive manner. Solar irradiance is considered to be the most important factor that has an impact on SCPP performance. The investigation includes the study of the relationship between solar insolation and ambient temperatures during the daytime since the difference between the minimum and maximum power values and the performance are very important considering seasonal changes. According to the results, power values are dependent on the amount of solar radiation as well as the ambient temperature, and the importance of selection of location thus climate for an SCPP is found to affect the design of the SCPP.