Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Citation - WoS: 1Numerical Investigation for Enhancement of Heat Transfer in the Cooling Water Jacket of CI Engine(Taylor & Francis inc, 2025) Altug, Hakan; Yapici, Ekin OzgirginDiesel engines are essential in heavy industries and agriculture, especially in vehicles like tractors that operate under challenging conditions, often causing engine faults. Effective thermal management systems are vital for faultless operation preventing overheating, extending engine life, reducing emissions, and improving efficiency. The core of these systems is the water jacket around the cylinder head, which regulates temperatures, facilitates lubrication, prevents friction-related faults, increase durability and thermal performance of the engine. Computational Fluid Dynamics techniques are crucial for analyzing engine thermal behavior and designing cooling systems with complex flows. This study simulates the engine block's temperature distribution under extreme conditions to prevent overheating and improve thermal performance. Geometrical modifications, such as optimizing outlet water ports are employed to achieve enhanced thermal performance by reducing the temperature of coolant. 3D model of the engine block is developed using STAR CCM+ to calculate water temperatures, flow rates and outlet pressures. Numerical validation is conducted with a test bench, and three geometric improvements are analyzed for temperature distribution and heat transfer coefficient. Results showed that, 6.2% improvement on thermal performance is achieved based on the average coolant temperatures and 10% enhancement is achieved in terms of heat transfer coefficient values.Article Citation - WoS: 1Citation - Scopus: 1Design and Experimental Verification of a Posture Correction System: Development of an Artificial Neural Network To Predict the Effectiveness of the Developed System To Correct Poor Posture(Taylor & Francis inc, 2024) Yildiz, Eren; Das, MemikThis research aims to address designing an experiment to evaluate the impact of a developed posture correction system. Also, the correct posture learning habits of users can be estimated with an artificial neural network (ANN) structure that predicts the poor posture count (PPC) in the last session of the experiment using the information received from the users and the developed system. The developed system aims to collect data from different individuals about their sitting posture information. An ANN analysis tool is developed to predict the individuals' habits of learning the correct posture. This setup is based on a flex sensor and has the capability of collecting posture information data and warning the user when the posture is not correct. A three-session experiment was conducted on 12 healthy participants to investigate his/her posture habits. The data was analyzed to determine the average PPC value. It was observed that PPC decreased by 56.27% from session one to session three, and the average improvement evaluation (IE) value after each session was found to be positive. In addition to experimental analysis, the collected posture data was used to train and validate an ANN architecture capable of predicting PPC values. The developed device is effective in improving posture habits and has the potential to predict PPC values with the ANN architecture.Article Adaptive Estimation of Autoregression Models Under Long-Tailed Symmetric Distribution(Taylor & Francis inc, 2024) Yentur, Begum; Akkaya, Aysen D.; Bayrak, Ozlem TurkerNon-normal innovations in autoregression models frequently occur in practice. In this situation, least squares (LS) estimators are known to be inefficient and non-robust, and maximum likelihood (ML) estimators need to be solved numerically, which becomes a daunting task. In the literature, the modified maximum likelihood (MML) estimation technique has been proposed to obtain the estimators of model parameters. While an explicit solution can be found via this method, the requirement of knowing the shape parameter becomes a drawback, especially in machine learning. In this study, we use the adaptive modified maximum likelihood (AMML) methodology, which combines the MML with Huber's M-estimation so that this assumption is relaxed. The performance of the method in terms of efficiency and robustness is analyzed via simulation and compared to LS, MML and ML estimates that are obtained numerically via the Expectation Conditional Maximization (ECM) algorithm. Test statistics are proposed for the crucial parameters of the model. The results show that the AMML estimators are preferable in most of the settings according to the mean squared error (MSE) criterion and the test statistics based on AMML method are more robust than the others. Furthermore, both real life and synthetic data examples are given.Article Citation - Scopus: 1Pyrrolizine-3 Synthesis and Evaluation of Photophysical Properties(Taylor & Francis inc, 2024) Tasgin, Dilek Isik; Bayraktar, Irem; Isik Tasgin, DilekWe describe a synthetic approach for pyrrolizine-3-one derivatives and their photophysical properties. These compounds are prepared by a series of reactions employing the substituted pyrroles in one-pot, two-step oxidation, and intramolecular cyclization processes. The photophysical properties of the synthesized compounds were studied by using UV-Vis and fluorescence spectroscopy in different solvents. Maximum absorbance peaks were observed around 306-416 nm and maximum fluorescence emission around 603-614 nm and 465-498 nm for pyrrolyl and N-methyl pyrrolyl substituents, respectively. The introduction of a pyrrolyl substituent had a significant impact on the Stokes shifts (192-206 nm) and quantum yield values ranged from 0.002 to 0.046.Article Citation - WoS: 7Citation - Scopus: 3Artificial Neural Networks for the Wavelet Analysis of Lane-Emden Equations: Exploration of Astrophysical Enigma(Taylor & Francis inc, 2024) Aeri, Shivani; Baleanu, Dumitru; Kumar, RakeshThe equations of Lane-Emden (LE) can be visualized in various phenomena of astrophysics, fluid mechanics, polymer science and material science, thus the main concern of the present study is to put a novel effort to resolve these equations by utilizing the artificial neural networking approach incorporation with Vieta-Lucas wavelets called as VLW-ANN method. This unique combination of neural networking and Vieta-Lucas wavelets has been prepared to reduce the computational challenges as well as to overcome the obstacles while dealing with singularity. Many examples of the LE variety are solved by this approach. The effectiveness, accuracy and simplicity of the VLW-ANN scheme are demonstrated by a comparative study between the VLW-ANN results and existing results. Additionally, the results are shown in tables and figures, which give a more favorable impression of the scheme's dependability. VLW-ANN scheme will provide interesting results for other non-linear models.Article Citation - WoS: 18Citation - Scopus: 19Effects of Electrolytic Copper and Copper Alloy Electrodes on Machining Performance in Electrical Discharge Machining (Edm)(Taylor & Francis inc, 2022) Esen, Ziya; Simsek, Ulke; Cogun, CanThe most important cost element of electric discharge machining (EDM) is the production of tool electrode (shortly electrode). In the EDM process, copper and its alloys are often used as electrode materials. The machining with EDM without increasing the costs can be achieved by selecting the proper electrode with low production and material costs as well as high workpiece material removal rate (MRR), low electrode wear rate (EWR), and relative wear (RW = MRR/EWR). In this study, the EDM performance outputs, namely, MRR and RW were experimentally investigated for electrolytic copper, CuCr1Zr (with and without aging treatment) and CuCo2Be alloy electrode materials for varying machining parameters. The performance outputs were affected by the electrode material and the applied aging treatment. The aged CuCr1Zr alloy electrodes had higher electrical conductivity and better machining performance than the as-received alloy. The CuCo2Be alloy electrodes exhibited moderate to high MRR; however, their RW was the highest. Although the electrolytic copper has moderate MRR performance compared to the investigated alloys, its low cost increased its performance index, making it a more suitable electrode material for EDM applications.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: 7Citation - Scopus: 10Combined Use of Ultrasonic-Assisted Drilling and Minimum Quantity Lubrication for Drilling of Niti Shape Memory Alloy(Taylor & Francis inc, 2023) Namlu, Ramazan Hakki; Lotfi, Bahram; Kilic, S. Engin; Yilmaz, Okan Deniz; Akar, SametThe drilling of shape-memory alloys based on nickel-titanium (Nitinol) is challenging due to their unique properties, such as high strength, high hardness and strong work hardening, which results in excessive tool wear and damage to the material. In this study, an attempt has been made to characterize the drillability of Nitinol by investigating the process/cooling interaction. Four different combinations of process/cooling have been studied as conventional drilling with flood cooling (CD-Wet) and with minimum quantity lubrication (CD-MQL), ultrasonic-assisted drilling with flood cooling (UAD-Wet) and with MQL (UAD-MQL). The drill bit wear, drilling forces, chip morphology and drilled hole quality are used as the performance measures. The results show that UAD conditions result in lower feed forces than CD conditions, with a 31.2% reduction in wet and a 15.3% reduction in MQL on average. The lowest feed forces are observed in UAD-Wet conditions due to better coolant penetration in the cutting zone. The UAD-Wet yielded the lowest tool wear, while CD-MQL exhibited the most severe. UAD demonstrated a & SIM;50% lower tool wear in the wet condition than CD and a 38.7% in the MQL condition. UAD is shown to outperform the CD process in terms of drilled-hole accuracy.Article Citation - WoS: 4Citation - Scopus: 4On the Boundary Value Problem in the Nonlinear Theory of Dipolar Elastic Materials(Taylor & Francis inc, 2020) Carrera, Erasmo; Baleanu, Dumitru; Marin, MarinIn our study, we formulate the boundary value problem in the context of the nonlinear theory of dipolar, porous, and elastic materials. For this problem, some existence and uniqueness results are proven. The results are natural generalizations of the results obtained by Langenbach for the classical elastic bodies.Article Citation - WoS: 12Citation - Scopus: 9Best Proximity Point Results for Contractive and Cyclic Contractive Type Mappings(Taylor & Francis inc, 2021) Karapinar, Erdal; Kanta Dey, Lakshmi; Hiranmoy, GaraiThe essential importance of the best proximity point theory is that "best proximity point theory" appears in the coincidence of "metric fixed point theory" and "optimization theory." So finding best proximity points of mappings satisfying different type of contractive conditions in different structures is one of the fascinating research topics. For this, in this article, we first introduce a new type of proximal property of a pair of subsets of a metric space, which we designate as proximal weakly compact pair. After this, we come up with some new type of proximal contractive and proximal cyclic contractive mappings. Then we investigate the existence of best proximity point(s) in these newly originated mappings in the setting of proximal weakly compact pair of subsets in a metric space.
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