Makine Mühendisliği Bölümü

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Citation - WoS: 14
Citation - Scopus: 16
A Comparative Study of Multiple Regression and Machine Learning Techniques for Prediction of Nanofluid Heat Transfer
(Asme, 2022) Ayli, Ece; Turkoglu, Hasmet; Kocak, Eyup
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: 6
Citation - Scopus: 6
Machine Learning Based Developing Flow Control Technique Over Circular Cylinders
(Asme, 2023) Turkoglu, Hasmet; Ayli, Ece; Kocak, Eyup
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: 3
Citation - Scopus: 5
Optimization of Vortex Promoter Parameters To Enhance Heat Transfer Rate in Electronic Equipment
(Asme, 2020) Ayli, Ece; Bayer, Ozgur
In this paper, optimization of the location and the geometry of a vortex promoter located above in a finned surface in a channel with eight heat sources is investigated for a Reynolds number of 12,500 < Re < 27,700. Heat transfer rates and the corresponding Nusselt number distributions are studied both experimentally and numerically using different vortex promoter geometries (square, circular, and triangular) in different locations to illustrate the effect of vortex promoter on the fluid flow. Optimization study considered a range of following parameters: blockage ratio of 0.30<(y/C) < 0.45 and interpromoter distance ratio of 0.2277 <(x/L) < 0.3416. Results show that fins over which rectangular and circular promoters are integrated perform better in enhancing the heat transfer. According to the numerical and experimental results, higher blockage ratios cause significantly higher heat transfer coefficients. According to the observations, as the interpromoter distances increase, shedding gains strength, and more turbulence is created. All vortex promoters enhance heat transfer resulting in lower temperature values on the finned surface for different (y/C) and (x/L) values and Reynolds numbers. The use of promoters enhances the heat transfer, and the decrease in the maximum temperature values is recorded on the finned surface changing between 15% and 27%. The biggest decrease in maximum surface temperature value is 500 K-364 K and observed in circular promoter case with (y/C) = 0.43, (x/L) = 0.3416, and Reynolds numbers of 22,200.
Citation - WoS: 1
Citation - Scopus: 1
Performance Determination of Axial Wind Tunnel Fan With Reverse Engineering, Numerical and Experimental Methods
(Asme, 2022) Ayli, Ece; Kocak, Eyup
In 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.
Citation - WoS: 2
Citation - Scopus: 3
Performance Optimization of Finned Surfaces Based on the Experimental and Numerical Study
(Asme, 2023) Ayli, Ece; Kocak, Eyup; Turkoglu, Hasmet
This 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.
Citation - WoS: 8
Citation - Scopus: 10
Solar Chimney Power Plant Performance for Different Seasons Under Varying Solar Irradiance and Temperature Distribution
(Asme, 2021) Tareq, Maisarh; Ozgirgin, Ekin; Ayli, Ulku Ece
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). 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.

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