WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653
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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: 16Citation - Scopus: 17A Comparative Study of Multiple Regression and Machine Learning Techniques for Prediction of Nanofluid Heat Transfer(Asme, 2022) Ayli, Ece; Turkoglu, Hasmet; Kocak, EyupThe 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.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.Article Citation - WoS: 17Citation - Scopus: 17Developing and Implementation of an Optimization Technique for Solar Chimney Power Plant With Machine Learning(Asme, 2021) Kocak, Eyup; Bayer, Ozgur; Beldek, Ulas; Yapic, Ekin Ozgirgin; Ayli, Ece; Ulucak, Oguzhan; Yapici, Ekin ÖzgirginGreen energy has seen a huge surge of interest recently due to various environmental and financial reasons. To extract the most out of a renewable system and to go greener, new approaches are evolving. In this paper, the capability of Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System in geometrical optimization of a solar chimney power plant (SCPP) to enhance generated power is investigated to reduce the time cost and errors when optimization is performed with numerical or experimental methods. It is seen that both properly constructed artificial neural networks (ANN) and adaptive-network-based fuzzy inference system (ANFIS) optimized geometries give higher performance than the numerical results. Also, to validate the accuracy of the ANN and ANFIS predictions, the obtained results are compared with the numerical results. Both soft computing methods over predict the power output values with MRE values of 12.36% and 7.25% for ANN and ANFIS, respectively. It is seen that by utilizing ANN and ANFIS algorithms, more power can be extracted from the SCPP system compared to conventional computational fluid dynamics (CFD) optimized geometry with trying a lot more geometries in a notably less time when it is compared with the numerical technique. It is worth mentioning that the optimization method that is developed can be implemented to all engineering problems that need geometric optimization to maximize or minimize the objective function.Article Citation - WoS: 3Citation - Scopus: 5Optimization of Vortex Promoter Parameters To Enhance Heat Transfer Rate in Electronic Equipment(Asme, 2020) Ayli, Ece; Bayer, OzgurIn 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.Article Citation - WoS: 4Citation - Scopus: 3Some Kinds of the Controllable Problems for Fuzzy Control Dynamic Systems(Asme, 2018) Tri, P. V.; Ahmadian, A.; Salahshour, S.; Baleanu, D.; Phu, N. D.In this work, we have discussed the fuzzy solutions for fuzzy controllable problem, fuzzy feedback problem, and fuzzy global controllable (GC) problems. We use the method of successive approximations under the generalized Lipschitz condition for the local existence and furthermore, we have described the contraction principle under suitable conditions for global existence and uniqueness of fuzzy solutions. We have too the GC results for fuzzy systems. Some examples and computer simulation illustrating our approach are also given for these controllable problems.Article Citation - WoS: 4Citation - Scopus: 3Nonlinear Adaptive Magneto-Thermal Analysis at Bushing Regions of a Transformers Cover Using Finite Difference Method(Asme, 2019) Iskender, I.; Zahedi, Mohammad ZiaIn this study, losses analysis at bushing regions of a transformer covers is done using finite difference method (FDM), considering that FDM being more flexible to deal with the nonlinear constitutive law and easier to be implemented than finite element (FE) and analytical methods. The analysis is performed based on a 2-level adaptive mesh solution of Maxwell equations and Ohm law at the cross section area in the axial symmetry page of a steel disk, taking account the nonlinear magnetic permeability of the steel. The losses density obtained, as a heat source, is imported into an alternating direction implicit (ADI) approach of heat conduction equation. Therefore, a finite difference (FD) solution algorithm for magneto-thermal analysis on cover plate is obtained by combination of adaptive mesh refinement and ADI-FDM, which improves the accuracy and decreases the computational time without losing accuracy. The reliability of the proposed technique is confirmed by experimental and FE method (FEM) results, considering the temperature distribution of the cover. The comparison of the results with those obtained from FEM and experiments shows the efficiency and capability of the method.