WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653
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Article CFD and DEM Analysis of Cyclone Separator Performance: Implications of Cylinder-to Ratios for Sustainable Engineering(Springer Heidelberg, 2025) Ayli, Ece; Kocak, EyupThis research addresses a common industrial challenge: efficiently separating particles from gas using cyclone separators, a critical component for various applications in sustainable engineering. While several studies have focused on airflow within these separators, this research introduces a novel approach by combining two advanced simulation methods (CFD and DEM) to analyze how different cone heights in a cyclone separator impact its performance. This combined methodology enables the examination of particle movement within the separator, a critical aspect often overlooked in previous studies. By visualizing particle dynamics and analyzing them with DEM, the research underscores the importance of considering particle behavior for obtaining accurate results. Overall, this study enhances our understanding of cyclone separators through state-of-the-art simulations and empirical testing. By elucidating the complex airflow and the influence of geometric design on performance, practical recommendations are provided for the development of more efficient cyclone separators. These improvements can lead to enhanced particle separation and reduced energy consumption, offering significant benefits across multiple industries. The findings reveal that as the conical height-to-total height ratio (h/hc) increases, indicating a more pointed cone, there is a substantial increase in efficiency alongside a minimal and tolerable rise in pressure drop. For instance, at a velocity of 25 m/s, increasing the h/hc ratio from 0.33 to 3 results in a 0.7% reduction in pressure drop and a 14% efficiency increase, contributing to more sustainable operational practices.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 Citation - WoS: 2Citation - Scopus: 2Machine Learning-Driven Approach for Reducing Tool Wear in Die-Sinking Electrical Discharge Machining(Springer Heidelberg, 2025) Cogun, Can; Ayli, EceThis study examines the use of machine learning (ML) techniques to optimize the basic machining parameters and protrusion dimensions that affect tool shape degeneration in die-sinking electric discharge machining (EDM). The primary objective is to decrease errors and enhance prediction and optimization effectiveness. This study introduces a completely novel tool geometry model aimed at minimizing tool shape degeneration, which, to our knowledge, has not been previously documented in the literature. Additionally, this research represents the first instance of employing ML techniques to generate data for addressing this specific type of problem, further advancing the field of die-sinking EDM. The pivotal machining parameters include discharge current, pulse time and machining depth. Three ML approaches are implemented in this investigation: Artificial Neural Network (ANN), Adaptive-Network-Based Fuzzy Inference System (ANFIS), and Support Vector Machine (SVM). In comparison with experimental outcomes, the ANN technique exhibited superior predictive ability with an coefficient of determination (R2) of 0.99985 and an Mean Relative Error (MRE) of 0.854%. Four distinct EDM machining scenarios are presented and machining parameters and protrusion dimensions are optimized using the ANN technique to decrease tool shape degeneration. Optimizing the machining parameters and diagonal dimensions of the protrusion substantially reduced tool shape degeneration. This research demonstrates the effectiveness of ANN in optimizing machining parameters and improving tool performance in die-sinking EDM. A significant reduction in total wear area of 66.7% was achieved with a considerably lower time cost through the optimized ANN network. While the study demonstrates promising results, its reliance on specific datasets for training may limit the generalizability of the model to broader machining scenarios.Article Citation - WoS: 52Citation - Scopus: 58Numerical Investigation on the Performance of a Small Scale Solar Chimney Power Plant for Different Geometrical Parameters(Elsevier Sci Ltd, 2020) Yapici, Ekin Ozgirgin; Ayli, Ece; Nsaif, OsamaIn 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.