Makine Mühendisliği Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/263
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Article Citation - WoS: 3Citation - Scopus: 3Empirical and Statistical Modeling of Heat Loss From Surface of a Cement Rotary Kiln System(Gazi Univ, Fac Engineering Architecture, 2013) Simsek, Baris; Altunok, Taner; Simsek, Emir H.; Altunok, Taner; Makine MühendisliğiIn branches of industry too much energy consuming such as cement sector, controlled use of energy, only it is possible to know how energy is distributed in the system. In cement production process, a large portion of the heat losses which is due to energy consumption consist of convection and radiation heat losses from the surface of rotary kiln. In this study, empirical equation was derived for heat loss from surface of rotary kiln in a cement factory using empirical equations and statistical modeling techniques by the help of temperatures measured surface of rotary kiln. Measured with thermal cameras and the data necessary for experimental modeling was obtained the factory central control room. Total heat loss of system was calculated using Matlab. Statistical analysis related to results was carried out by Minitab 15.1.1 program. It was concluded that heat losses throughout rotary kiln increased toward the center of the kiln.Article Citation - WoS: 5Citation - Scopus: 6Prediction of the Heat Transfer Performance of Twisted Tape Inserts by Using Artificial Neural Networks(Korean Soc Mechanical Engineers, 2022) Kocak, Eyup; Ayli, EceA numerical study is undertaken to investigate the effect of twisted tape inserts on heat transfer. Twisted tapes with various aspect ratios and single, double, and triple inserts are placed inside a tube for Reynolds numbers ranging from 8000 to 12000. Numerical results show that the tube with a twisted tape and different numbers of tape is more effective than the smooth tube in terms of thermo-hydraulic performance. The highest heat transfer is achieved with the triple insert, with the highest turning number and an increment of 15 %. Then, an artificial neural network (ANN) model with a three-layer feedforward neural network is adopted to obtain the Nusselt number on the basis of four inputs for a heated tube with a twisted insert. Several configurations of the neural network are examined to optimize the number of neurons and to identify the most appropriate training algorithm. Finally, the best model is determined with one hidden layer and thirteen neurons in the layer. Bayesian regulation is chosen as the training algorithm. With the optimized algorithm, excellent precision for measuring the output is provided, with R2 = 0.97043. In addition, the optimized ANN architecture is applied to similar studies in the literature to predict the heat transfer performance of twisted tapes. The developed ANN architecture can predict the heat transfer enhancement performance of similar problems with R2 values higher than 0.93.Article Citation - WoS: 20Citation - Scopus: 20Modeling of Mixed Convection in an Enclosure Using Multiple Regression, Artificial Neural Network, and Adaptive Neuro-Fuzzy Interface System Models(Sage Publications Ltd, 2020) Ayli, EceIn this study, the heat transfer characteristics of laminar combined forced convection through a horizontal duct are obtained with the help of the numerical methods. The effect of the geometrical parameters of the cavity and Reynolds number on the heat transfer is investigated. New heat transfer correlation for hydrodynamically fully developed, laminar combined forced convection through a horizontal duct is proposed with an average error of 6.98% and R-2 of 0.8625. The obtained correlation results are compared with the artificial neural network and adaptive neuro-fuzzy interface system models. Due to the obtained results, good agreement is identified between the numerical results and predicted adaptive neuro-fuzzy interface system results. In conclusion, it is seen that adaptive neuro-fuzzy interface system can predict the Nusselt number distribution with a higher accuracy than the developed correlation and the artificial neural network model. The developed adaptive neuro-fuzzy interface system model predicts the Nusselt number with 1.07% mean average percentage error and 0.9983 R-2 value. The effect of the different training algorithms and their ability to predict Nusselt number distribution are examined. According to the results, the Bayesian regulation algorithm gives the best approach with a 2.235% error. According to the examination that is performed in this study, the adaptive neuro-fuzzy interface system is a powerful, robust tool that can be used with confidence for predicting the thermal performance.Book Part Comparison of Different Turbulent Models in Turbulent-Forced Convective Flow and Heat Transfer Inside Rectangular Cross-Sectioned Duct Heating at the Bottom Wall(Springer International Publishing, 2014) Onur, N.; Arslan, K.In this study, steady-state turbulent-forced flow and heat transfer in a horizontal smooth rectangular cross-sectioned duct was numerically investigated. The study was carried out in the turbulent flow region where Reynolds number ranges from 1 × 104 to 5 × 104. The flow was developing both hydrodynamically and thermally. The bottom surface of the duct was assumed to be under constant surface temperature. A commercial CFD program Ansys Fluent 12.1 with different turbulent models was used to carry out the numerical study. Different turbulence models (k–ε Standard, k–ε Realizable, k–ε RNG, k–ω Standard and k–ω SST) were used. Based on the present numerical solutions, new engineering correlations were presented for the heat transfer and friction coefficients. The numerical results for different turbulence models were compared with each other and the experimental data available in the literature. It was observed that k–ε turbulence models represented the turbulent flow condition very well for the present study. © Springer International Publishing Switzerland 2014.