Makine Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/263

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Citation - WoS: 3
Citation - Scopus: 3
A Comparative Study of Effects of Additive Particle Size and Content on Wetting Behavior and Brazing Performance of C/SiC Composite
(Springer, 2023) Saltik, Simge; Esen, Ziya; Esen, Ziya; Dericioglu, Arcan F.; 52373; Ortak Dersler Bölümü
This study has focused on the influence of size and content of SiC particle incorporation on the wetting behavior of the Ticusil brazing filler alloy and on its brazing performance in C/SiC composite/Ti6Al4V alloy joints. The effect of the size and content of additive SiC particles on the variation of molten brazing filler alloy contact angle was recorded at various brazing time and temperatures. Moreover, the microstructural evolution and mechanical properties of the additive containing C/SiC composite/Ti6Al4V alloy joints produced by the brazing method were investigated. The contact angles in both brazing filler alloys containing nano- and micro-sized SiC particles exhibited a sudden decrease with time during isothermal holding as observed in as-received brazing filler alloys. As the quantity of the SiC particles increased in the brazing alloy, the recorded contact angle values including the final, stable contact angle increased, while the time for the drastic contact angle change also increased remarkably. Compared to as-received counterparts, the addition of 2 wt.% nano-sized SiC and 1 wt.% micro-sized SiC particles improved the shear strength of the joints by 35 and 8%, respectively. Although the recorded contact angle values were close to each other in brazing alloys containing SiC particles with different sizes (37 and 42 degrees for 1 wt.% micro-sized and 2 wt.% nano-sized additions), higher increment was achieved in the mechanical performance of the joints with nano-sized SiC additive due to more homogeneous reinforcement effect of the nanoparticles. The results indicated that the optimum brazing filler alloy contact angle for the highest shear strength is similar to 40 degrees for both nano- and micron-sized additive containing Ticusil filler alloy.
Citation - WoS: 13
Citation - Scopus: 14
A Comparative Study of Multiple Regression and Machine Learning Techniques for Prediction of Nanofluid Heat Transfer
(Asme, 2022) Kocak, Eyup; Türkoğlu, Haşmet; Ayli, Ece; Turkoglu, Hasmet; 283455; 265836; 12941; Makine Mühendisliği
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 - WoS: 5
Citation - Scopus: 5
A 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; 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 - WoS: 7
Citation - Scopus: 8
A novel zero-dead-volume sample loading interface for microfluidic devices: flexible hydraulic reservoir (FHR)
(Iop Publishing Ltd, 2018) Hatipoglu, Utku; Yıldırım, Ender; Cetin, Barbaros; Yildirim, Ender; 158278; 31835; Makine Mühendisliği
Infusing minute amounts of valuable liquids such as samples to microfluidic chips by using common pumping schemes such as syringe pumps often result in an excessive dead-volume. We present a simple yet effective sample loading interface, which helps by pumping the sample to the chip by using the hydraulic pressure generated by the syringe pump. Results show that sample volumes as low as 25 mu l can be delivered at flow rates ranging between 10-30 mu l min(-1). Maximum dead volume ratio was observed to be 3% when infusing 200 mu l of sample at 10 mu l min(-1).
Citation - WoS: 5
Citation - Scopus: 5
A study on the μwire-EDM of Ni55.8Ti shape memory superalloy: an experimental investigation and a hybrid ANN/PSO approach for optimization
(Springer Heidelberg, 2023) Akar, Samet; Akar, Samet; Seyedzavvar, Mirsadegh; Boga, Cem; 315516; Makine Mühendisliği
The unique properties of high hardness, toughness, strain hardening, and development of strain-induced martensite of nickel-titanium superalloys made the micro-wire electro discharge machining (mu wire-EDM) process one of the main practical options to cut such alloys in micro-scale. This paper presents the results of a comprehensive study to address the response variables of Ni55.8Ti superalloy in mu wire-EDM process, including the kerf width (KW), material removal rate (MRR), arithmetic mean surface roughness (R-a) and white layer thickness (WLT). To this aim, the effects of pulse on-time (T-on), pulse off-time (T-off), discharge current (I-d) and servo voltage (SV) as input parameters were investigated using the experiments conducted based on Taguchi L-27 orthogonal array. The results were employed in the analysis of variance (ANOVA) to examine the significance of input parameters and their interactions with the output variables. An optimization approach was adopted based on a hybrid neural network/particle swarm optimization (ANN/PSO) technique. The ANN was employed to achieve the models representing the correlation between the input parameters and output variables of the mu wire-EDM process. The weight and bias factor matrices were obtained by ANN in MATLAB and together with the feed forward/backpropagation model and developed functions based on PSO methodology were used to optimize the input parameters to achieve the minimum quantities of KW, R-a and WLT and the maximum value of MRR, individually and in an accumulative approach. The results represented a maximum accumulative error of nearly 8% that indicated the precision of the developed model and the reliability of the optimization approach. At the optimized level of input parameters obtained through the accumulative optimization approach, the KW, R-a, and WLT remained nearly intact as compared with the levels of responses obtained in the individual optimization approach, while there was a sacrifice in the machining efficiency and reduction in the MRR in the mu wire-EDM process of Nitinol superalloy.
Citation - WoS: 12
Analysis and characterization of an electrostatically actuated in-plane parylene microvalve
(Iop Publishing Ltd, 2011) Yildirim, E.; Yıldırım, Ender; Kulah, H.; 31835; 120121; Makine Mühendisliği
This paper presents analysis and implementation of a simple electrostatic microvalve designed for use in parylene-based lab-on-a-chip devices. The microvalve utilizes an in-plane collapsing diaphragm. To investigate the pull-in behavior of the diaphragm and flow characteristics, a thorough analysis is carried out using the finite element method. Microvalves with different diaphragm radii are fabricated using surface micromachining techniques. Pull-in tests are carried out under the no-flow condition with air, oil and water as the working fluid. Test results show that the pull-in occurs around 20 V for 450 mu m radius diaphragms with oil and air. However, it is not possible to observe pull-in up to 100 V (both ac and dc) for the case of water as the working fluid, due to its relatively high dielectric constant and conductivity. The flow tests show that no leakage flow was observed up to 4 kPa inlet pressure under 85 V actuation potential. The leakage ratio becomes 17% at 10 kPa inlet pressure. It is observed that the leakage can be reduced controllably by increasing the actuation potential, enabling the precise control of the flow rate.
Citation - WoS: 2
Citation - Scopus: 2
Analysis and simplified modelling of simulation of tests for medium-duty truck collision with twin anti-ram bollards
(Taylor & Francis Ltd, 2020) Akyurek, Turgut; Akyürek, Turgut; 48511; Makine Mühendisliği
An actual test of medium-duty truck collision with twin anti-ram bollards of steel tube is analysed and simulated with different mass-spring-damper models to study bollard design requirements. Test data is obtained from test report of a medium-duty truck crashed into two fixed twin bollards at speed 78.3 km/h. Maximum impact load and impact height at that time is important in the analysis. Bollard height should be close to or larger than the vehicle's centre of gravity height to avoid climbing of the truck on the bollard. However, increasing impact height yields also increase in failure risk of bollard. Foundation is also critical in success of the bollard in successfully stopping the vehicle. The bollard should be fixed to the frame embedded in the concrete foundation so that the deformation in concrete be minimised. The bollard should be so stiff to stop the vehicle while most of the impact energy is absorbed by the vehicle through deformation of its frontal sections. A single-degree freedom linear mass-spring-damper model is the simplest model, but its results are not in line with test data. Single-degree non-linear model simulates the peak load but not the load history. However, using engine mass instead of truck mass in the single-degree model provides acceptable impact force data for the bollard. Two-degree freedom mass-spring damper linear model seems to simulate both truck's and bollard's deformation in a good manner. Non-linear analysis simulates the collision in a more realistic way, but it requires more data to be determined with testing.
Citation - WoS: 2
Citation - Scopus: 2
Analysis of heat transfer enhancement of passive methods in tubes with machine learning
(Sage Publications Ltd, 2024) Yapici, Ekin Ozgirgin; Türkoğlu, Haşmet; Ayli, Ece; Turkoglu, Hasmet; 31329; 265836; 12941; Makine Mühendisliği
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 - WoS: 2
Citation - Scopus: 2
Critical decision making for rehabilitation of hydroelectric power plants
(Taylor & Francis inc, 2023) Celebioglu, Kutay; Ayli, Ece; Ulucak, Oguzhan; Aradag, 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 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.
Citation - WoS: 3
Citation - Scopus: 6
Enhanced gradient crystal-plasticity study of size effects in a beta-titanium alloy
(Iop Publishing Ltd, 2017) Demiral, Murat; Demiral, Murat; Nowag, Kai; Roy, Anish; Ghisleni, Rudy; Michler, Johann; Silberschmidt, Vadim V.; Makine Mühendisliği
A calibrated model of enhanced strain-gradient crystal plasticity is proposed, which is shown to characterize adequate deformation behaviour of bcc single crystals of a beta-Ti alloy (Ti-15-3-3-3). In this model, in addition to strain gradients evolving in the course of deformation, incipient strain gradients, related to a component's surface-to-volume ratio, is accounted for. Predictive capabilities of the model in characterizing a size effect in an initial yield and a work-hardening rate in small-scale components is demonstrated. The characteristic length-scale, i.e. the component's dimensions below which the size effect is observed, was found to depend on densities of polar and statistical dislocations and interaction between them.
Citation - WoS: 1
Citation - Scopus: 2
Experimental and numerical investigation of comparability of whiplash sled test results
(Springer Heidelberg, 2016) Ozdemir, Mustafa; İder, Sıtkı Kemal; Ider, Sitki Kemal; Gokler, Mustafa Ilhan; 108608; 182869; Makine Mühendisliği
Whiplash-associated neck injuries represent an important health and socioeconomic problem attracting more and more attention of the vehicle safety community. Sled tests are conducted for the dynamic whiplash assessment of seats. However, reproducibility of the initial backset distances and of the sled pulses in every test plays an important role on the comparability of these results. In this study, in order to investigate these aspects, three different driver seat types are considered with three identical and unused samples for each of them, and by strictly following the European New Car Assessment Program (Euro NCAP) whiplash protocol and using the BioRID II dummy, totally nine sled tests are performed. The sled pulses are in general reproduced quite well for different vehicle seats in these tests. However, it is seen that there are differences of up to 5 mm in the initial backset distances recorded for the identical seats of the same type, while this difference increases up to 7 mm among the different seat types considered. Moreover, taking into account the associated tolerances allowed in this protocol, this uncertainty in the backset can even increase up to 10 mm. Based on the previous simulation results obtained by using the finite element model of the BioRID II dummy, linear regression models are constructed, and it is shown that a 10-mm increase in the backset will yield an increase of 2.25, 2.89 and 3.11 m(2)/s(2) in the NICmax values for the low, medium and high severity Euro NCAP pulses, respectively. Being 38, 22 and 31 % of the differences between the associated Euro NCAP higher and lower performance limits, and 68, 96 and 124 % of the differences between the associated Euro NCAP lower performance and capping limits, such increases in the NICmax values are found to bring an unacceptably high uncertainty in the test results, and they can even easily lead to the application of capping, which means giving a zero score for the entire test. In light of these findings, several suggestions are recommended for a more solid whiplash dynamic assessment procedure.
Citation - WoS: 0
Citation - Scopus: 0
Experimental and numerical investigation of transition to turbulent flow and heat transfer inside a horizontal smooth rectangular duct under uniform bottom surface temperature
(Springer, 2013) Arslan, Kamil; Onur, Nevzat; Onur, Nevzat; 47465; 53858; Makine Mühendisliği
In this study, steady-state turbulent forced flow and heat transfer in a horizontal smooth rectangular duct both experimentally and numerically investigated. The study was carried out in the transition to turbulence region where Reynolds numbers range from 2,323 to 9,899. Flow is hydrodynamically and thermally developing (simultaneously developing flow) under uniform bottom surface temperature condition. A commercial CFD program Ansys Fluent 12.1 with different turbulent models was used to carry out the numerical study. Based on the present experimental data and three-dimensional numerical solutions, new engineering correlations were presented for the heat transfer and friction coefficients in the form of and , respectively. The results have shown that as the Reynolds number increases heat transfer coefficient increases but Darcy friction factor decreases. It is seen that there is a good agreement between the present experimental and numerical results. Examination of heat and mass transfer in rectangular cross-sectioned duct for different duct aspect ratio (alpha) was also carried out in this study. Average Nusselt number and average Darcy friction factor were expressed with graphics and correlations for different duct aspect ratios.
Citation - WoS: 15
Citation - Scopus: 18
Experimental investigation of flow and heat transfer in rectangular cross-sectioned duct with baffles mounted on the bottom surface with different inclination angles
(Springer, 2014) Arslan, Kamil; Onur, Nevzat; Onur, Nevzat; 47465; 53858; Makine Mühendisliği
In this study, steady-state forced convection heat transfer and pressure drop characteristics in a horizontal rectangular cross-sectioned duct, baffles mounted on the bottom surface with different inclination angles were investigated experimentally in the Reynolds number range from 1 x 10(3) to 1 x 10(4). The study was performed under turbulent flow conditions. Effects of different baffle inclination angles on flow and heat transfer were studied. Results are also presented in terms of thermal enhancement factor. It is observed that increasing in baffle inclination angle enhances the heat transfer and causes an increase in pressure drop in the duct.
Citation - WoS: 2
Citation - Scopus: 1
Exploring 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, 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 - WoS: 11
Citation - Scopus: 15
Fast fluorometric enumeration of E. coli using passive chip
(Elsevier, 2019) Çoğun, Ferah; Kasap, Esin Nagihan; Dogan, Uzeyir; Yıldırım, Ender; Cogun, Ferah; Yildirim, Ender; Boyaci, Ismail Haklu; Cetin, Demet; Ertas, Nusret; Makine Mühendisliği
In this report, a passive microfluidic chip design was developed for fast and sensitive fluorometric determination of Escherichia coli (E. coli) based on sandwich immunoassay. Initially, magnetic nanoparticles (MNPs) and chitosan modified mercaptopropionic acid capped cadmium telluride (CdTe) quantum dots (QDs) were functionalized with E.coli specific antibody to form a sandwich immunoassay with the E. coli. The magnetic separation and preconcentration of the E.coli from the sample solution was performed in the vial. Conjugation of QDs to the magnetically captured E. coli and washing were performed using a passive type of microchip. The microfluidic chip consists of four microchambers connected to each other by microchannels which act as capillary valves. Signal measurement was performed at the last chamber by using a hand-held spectrofluorometer equipped with a fiber optic reflection probe. The selectivity of the method was tested with Enterobacter aerogenes (E. aerogenes) and Salmonella enteritidis (S. enteritidis), it was observed that these bacteria have no interference effect on E.coli determination. The calibration curve was found to be linear in the range of 10(1)-10(5) cfu/mL with a correlation coefficient higher than 0.99. The limit of detection was calculated as 5 cfu/mL. The method was successfully applied to spiked tap and lake water samples. The results suggest that the developed method is applicable for on-site E. coli detection and offers several advantages such as large dynamic range, high sensitivity, high selectivity and short analysis time.
Citation - WoS: 34
Citation - Scopus: 40
Improvement of electric discharge machining (EDM) performance of Ti-6Al-4V alloy with added graphite powder to dielectric
(Assoc Mechanical Engineers Technicians Slovenia, 2015) Unses, Emre; Çoğun, Can; Cogun, Can; 3837; Mekatronik Mühendisliği
Ti-6Al-4V is a well-known Ti alloy widely used in the aerospace industry and belongs to the group of difficult-to-machine materials. It is less suitable for both conventional chip removal (machining) techniques and electric discharge machining (EDM). The very low material removal rate (MRR) of the Ti alloys during the EDM process causes prohibitively long machining durations. The goal of this study was to improve the EDM performance of the Ti-6Al-4V alloy by the addition of graphite powder into the kerosene dielectric liquid. The EDM performance was quantified by MRR, tool electrode wear rate (EWR), relative wear (RW), surface roughness and texture properties. The experiments conducted have shown that the use of graphite powder mixed with the kerosene dielectric (GPMKD) during machining considerably increases the MRR, improves the R-a and R-z(DIN) surface roughness and decreases the RW. 3D topographic views of the machined workpiece surfaces attained with GPMKD revealed uniformly distributed surface valleys and peaks over the surface and peaks with short arid round tops since the discharge energy of a spark is distributed over a large area at the machining gap. The experimental results strongly indicate the adaptability of the proposed technique to EDM die sinking and EDM drilling applications of the Ti-6Al-4V alloy in the aerospace industry. The ED machining performance of Ti-6Al-4V alloy using GPMKD is also compared to that of AISI 1040 steel, which is commonly used in EDM applications.
Citation - WoS: 1
Citation - Scopus: 1
Investigation of aerodynamic and aeroacoustic behavior of bio-inspired airfoils with numerical and experimental methods
(Sage Publications Ltd, 2024) Aylı, Ülkü Ece; Guzey, Kaan; Ayli, Ulku Ece; Koçak, Eyup; Kocak, Eyup; Aradag, Selin; 265836; 283455; Makine Mühendisliği
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 (& 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.
Citation - WoS: 1
Citation - Scopus: 1
Kinematic analysis of overconstrained manipulators with partial subspaces using decomposition method
(Cambridge Univ Press, 2022) Selvi, Ozgun; Selvi, Özgün; 46949; Makine Mühendisliği
Overconstrained manipulators in lower subspaces with unique motions can be created and analyzed. However, far too little attention has been paid to creating a generic method for overconstrained manipulators kinematic analysis. This study aimed to evaluate a generic methodology for kinematic analysis of overconstrained parallel manipulators with partial subspaces (OPM-PS) using decomposition to parallel manipulators (PMs) in lower subspaces. The theoretical dimensions of the method are depicted, and the use of partial subspace for overconstrained manipulators is portrayed. The methodology for the decomposition method is described and exemplified by designing and evaluating the method to two overconstrained manipulators with 5 degrees of freedom (DoF) and 3 DoF. The inverse kinematic analysis is detailed with position analysis and Jacobian along with the inverse velocity analysis. The workspace analysis for the manipulators using the methodology is elaborated with numerical results. The results of the study show that OPM-PS can be decomposed into PMs with lower subspace numbers. As imaginary joints are being utilized in the proposed methodology, it will create additional data to consider in the design process of the manipulators. Thus, it becomes more beneficial in design scenarios that include workspace as an objective.
Citation - WoS: 5
Citation - Scopus: 6
Machine Learning Based Developing Flow Control Technique Over Circular Cylinders
(Asme, 2023) Koçak, Eyup; Ayli, Ece; Kocak, Eyup; Türkoğlu, Haşmet; Turkoglu, Hasmet; 265836; 283455; 12941; Makine Mühendisliği
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 R-2(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 - WoS: 5
Citation - Scopus: 8
Modeling of Computer Virus Propagation with Fuzzy Parameters
(Tech Science Press, 2023) Alhebshi, Reemah M.; Baleanu, Dumitru; Ahmed, Nauman; Baleanu, Dumitru; Fatima, Umbreen; Dayan, Fazal; Rafiq, Muhammad; Mahmoud, Emad E.; 56389; Matematik
Typically, a computer has infectivity as soon as it is infected. It is a reality that no antivirus programming can identify and eliminate all kinds of viruses, suggesting that infections would persevere on the Internet. To understand the dynamics of the virus propagation in a better way, a computer virus spread model with fuzzy parameters is presented in this work. It is assumed that all infected computers do not have the same contribution to the virus transmission process and each computer has a different degree of infectivity, which depends on the quantity of virus. Considering this, the parameters beta and gamma being functions of the computer virus load, are considered fuzzy numbers. Using fuzzy theory helps us understand the spread of computer viruses more realistically as these parameters have fixed values in classical models. The essential features of the model, like reproduction number and equilibrium analysis, are discussed in fuzzy senses. Moreover, with fuzziness, two numerical methods, the forward Euler technique, and a nonstandard finite difference (NSFD) scheme, respectively, are developed and analyzed. In the evidence of the numerical simulations, the proposed NSFD method preserves the main features of the dynamic system. It can be considered a reliable tool to predict such types of solutions.

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