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Öğe The Estimation of Monthly Mean Soil Temperature at Different Depths in Sivas Province, Turkey by Artificial Neural Networks(2023)In this study, soil temperature of Sivas province was estimated by the artificial neural networks (ANNs) method using data obtained from five different meteorological measurement stations situated in provincial borders. Nineteen years of (2000–2018) monthly mean air temperature data obtained from five different soil depths (5, 10, 20, 50 and 100 cm) was used for ANN analysis. Predicted and measured soil temperatures were strongly correlated with determination coefficient (R2) values ranging between 0.9767 and 0.9941. Mean Absolute Error (MAE) ranged from 0.532°C to 1.381°C, while Mean Absolute Percentage Error (MAPE) ranged from 5.692% to 16.263% and Root Mean Squared Error (RMSE) ranged between 0.694°C and 1.666°C. It was found that the predicted values are in good agreement with the measured data. However, there was a tendency to underestimate the soil temperature.Öğe Machine Learning Approaches for One-Day Ahead Soil Temperature Forecasting(2023)Present study investigates the capabilities of six distinct machine learning techniques such as ANFIS network with fuzzy c-means (ANFIS-FCM), grid partition (ANFIS-GP), subtractive clustering (ANFIS-SC), feed-forward neural network (FNN), Elman neural network (ENN), and long short-term memory (LSTM) neural network in one-day ahead soil temperature (ST) forecasting. For this aim, daily ST data gathered at three different depths of 5 cm, 50 cm, and 100 cm from the Sivas meteorological observation station in the Central Anatolia Region of Turkey was used as training and testing datasets. Forecasting values of the machine learning models were compared with actual data by assessing with respect to four statistic metrics such as the mean absolute error, root mean square error (RMSE), Nash−Sutcliffe efficiency coefficient, and correlation coefficient (R). The results showed that the ANFIS-FCM, ANFIS-GP, ANFIS-SC, ENN, FNN and LSTM models presented satisfactory performance in modeling daily ST at all depths, with RMSE values ranging 0.0637-1.3276, 0.0634-1.3809, 0.0643-1.3280, 0.0635-1.3186, 0.0635-1.3281, and 0.0983-1.3256 °C, and R values ranging 0.9910-0.9999, 0.9903-0.9999, 0.9910-0.9999, 0.9911-0.9999, 0.9910-0.9999 and 0.9910-0.9998 °C, respectively.Öğe Artificial neural networks approach for forecasting of monthly relative humidity in Sivas, Turkey(2023) Gürlek, CahitRelative humidity is a crucial parameter for various agricultural and engineering applications and atmospheric dynamics; hence its accurate and reliable estimation is essential. This study aims to predict monthly relative humidity by means of the artificial neural networks (ANNs) method using neighbouring data in Sivas Province, Turkey. Nineteen years (2000- 2018) monthly mean relative humidity data of five measurement stations was used for ANN analysis. The prediction accuracy of the ANN models was evaluated with the coefficient of determination (R2), mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean squared error (RMSE). Contour plot maps were also generated for visual comparison. R2, MAE, MAPE and RMSE values ranged between 0.952-0.965, 1.916-2.586, 3.422-4.974 and 2.472-3.391, respectively. The results showed that the ANN method provided satisfactory predictions for relative humidity.Öğe Numerical thermo-mechanical analysis of a railway train wheel(2023) Mehmet Bulut; Nail Karagöz; Halil İbrahim Acar; Netice DumanIn this paper, the variation of thermal stresses, strains and deformations created by combined thermal and mechanical loads is investigated in block braked railway wheels. Thermo-mechanical analyses of the railway wheel were performed by using finite element (FE) for the numerical analysis. Before performing FE analyses, input parameters, e.g. heat flow, heat conduction, heat convection, applied loads and boundary conditions were transferred from railway wheel conditions in reality. The thermal analysis of wheel structure in the analysis calculation was evaluated experimentally, and validated with numerical result used in current model. In this purpose, ANSYS Workbench module package was used to simulate the distribution of stress and temperature field over the wheel. Combined thermal and mechanically induced damage surfaces of the railway wheel in reality were compared with numerical results in ANSYS. It was concluded from the results that 3D simulations in this wheel model showed a significant effect of thermal loading rather than mechanical loading on wheel braking tread, and combination of thermal and mechanical loading caused the detrimental effect on railway wheel structures those used in this model.Öğe Experimental exergy analysis of low-GWP R290 refrigerant and derivation of exergetic performance equations with regression algorithms(2023) Pektezel, Oğuzhan; Daş, Mehmet; Acar, Halil İbrahimThis study analyses the derivation of performance equations for a refrigeration system operating with R290 and R404A refrigerants using different regression models. Results of pace regression for coefficient of performance (COP), second law efficiency, and total exergy destruction showed mean absolute error (MAE) are 0.0993, 0.0159, and 0.0066, respectively. In all cases, the pace regression model made better predictions than elastic net regression. It was concluded that predictions made with regression models showed a good agreement with the actual experimental results. The derived equations can be utilised for refrigerants working in similar operational ranges.Öğe Experimental comparison of R290 and R600a and prediction of performance with machine learning algorithms(2023) Pektezel, Oğuzhan; Acar, Halil İbrahimThe use of alternative refrigerants is among the popular topics of the refrigeration industry. In the first part of this study, thermodynamic performances of R290 and R600a gases were compared in a vapor compression refrigeration experiment setup. Although R600a caused an average of 33.44% less compressor power consumption compared to R290 refrigerant, R290 provided an average of 23.77% increase in COP (coefficient of performance), 82.55% in cooling capacity, and 20.99% increase in second law efficiency compared to R600a. In the second part of the study, the performance parameters of the refrigeration system were predicted with MLP (multi-layer perceptron), SVM (support vector machine), and DT (decision tree) machine learning algorithms. It was detected that the SVM method predicted all parameters with the least error. MAE (mean absolute error) values detected in the COP prediction with test set were 0.0317, 0.0324, and 0.0989 for SVM, MLP, and DT, respectively. Results revealed that performance of the refrigeration system increased when utilizing R290, and SVM was superior in prediction of performance indicators compared to other machine learning methods.Öğe Experimental Analysis of Different Refrigerants’ Thermal Behavior and Predicting Their Performance Parameters(2023) Pektezel, Oğuzhan; Daş, Mehmet; Acar, Halil İbrahimThis study experimentally compares thermodynamic performance of R290 and R404A refrigerants in a refrigeration system. In the first part of the paper, energy analysis of the refrigeration system was performed at various evaporator and condenser temperatures. Results revealed that R404A refrigerant caused an 18.6% increase in compressor power consumption. The highest coefficient of performance values in the system for R290 and R404A were 3.99 and 3.21, respectively. The second part of the paper includes artificial intelligence prediction studies. The pace and elastic net regression models were used to predict performance parameters. A single equation that can predict the cooling capacity and compressor power consumption of R290 and R404A simultaneously was derived. For the cooling capacity, pace regression showed mean absolute error of 0.0252 and root-mean-squared error of 0.0334, while elastic net regression indicated mean absolute error of 0.1103 and root-mean-squared error of 0.1262. It was concluded that R290 had better thermodynamic performance than R404A and the equations obtained with artificial intelligence were applicable to predict the experimental findings, regardless of which refrigerant gas was used.Öğe Experimental Investigation of PV Panel Performance by Using PCM with Different Fin Geometries(2023) Bayat, Muhammed Musab; Buyruk, Ertan; Can, AhmetDuring the photovoltaic (PV) conversion process, a significant amount of solar radiation is converted into heat, which increases the cell's temperature and reduces its efficiency. A system consisting of PCM and aluminium fins was developed to minimise power loss due to temperature increments. Using PCM as heat absorbers in this study, heat from photovoltaic panels was transferred more efficiently with aluminium fins. The PV panel temperature is regulated by this method in hot climates as a passive cooling method. To regulate the surface temperature of PV panels, RT28HC was used as PCM. The reference PV panel was compared with a container-integrated PV panel with PCM and flat aluminium fins and a container-integrated PV panel with PCM and perforated aluminium fins to regulate the temperature of the PV cells and improve the efficiency of the panels. In the laboratory, with an initial ambient temperature of 20 °C, an experiment was conducted for 60 minutes. The results of the experiment show that the average surface temperature of the PV panel decreased by 8.32 °C from 49.24 °C to 40.92 °C with flat fins and by 8.55 °C from 49.24 °C to 40.69 °C with perforated fins. The maximum electric power generation by the PV panels increased by 7.43 % compared to the usual PV panels from 1.48 W to 1.59 W with flat fins and by 9.46 % from 1.48 W to 1.62 W with perforated fins as the surface temperature of the PV panels decreased. The surface temperature and generated current, voltage, and power of the uncooled and cooled PV panels are plotted over time in this study.Öğe Experimental Heat Transfer Analysis from Helical Coiled Tubes with the Same Surface Area(2023) Caner, Mustafa; Buyruk, Ertan; Can, AhmetHelical coiled tubes are commonly used inserted in water storage tank. In this study, an experimental investigation was carried out to obtain heat transfer characteristics of different geometric dimensions in helical tubes under steady state conditions. Helical coiled tubes of different geometric dimensions with the same overall length and total surface area were fabricated from the same copper tubes. The helical coiled tubes were placed in a hot water tank which could be adjusted to different water temperatures. Cold water was pumped into the helical coiled tubes at different flow rates with 20 °C. The experiments were carried out for laminar flow in the range of Re numbers between 3394 and 8332. Helical coiled tube Nu number was determined and compared with the literature. Then, the effectiveness’s of helical coiled tubes were calculated using the ε-NTU method.Öğe Experimental investigation of variable fin length on melting performance in a rectangular enclosure containing phase change material(ELSEVIER, MAR 2023) Temel Ümit Nazlı; Kılınç FerhatThe present study proposes a new technique to determine liquid fractions of phase change material during the melting process in a left-side heated rectangular enclosure. The effects of variable fin length arrangements on the melting performance of phase change material (PCM) were also investigated experimentally. Detailed information about solid, mushy, and liquid ratios was obtained by analysing the temperature histograms of real thermal images of the melting zone. In accordance with the nature of the melting, the use of variable-length fins shortens the melting time by 14.9% compared to the equal-length fin arrangement. Similarly, variable-length fins reduce the average temperature of the latent heat thermal energy storage (LHTES) by around 10 ◦C compared to the equal-length fin arrangement. The use of variable length fin arrangements ensures a more homogeneous melting process within the LHTES. The fin arrangement evenly distributed to the entire heating source is more effective at low heating rates. In contrast, fin arrangements evenly distributed over the lower half of the heating source are more efficient at high heating rates.Öğe Exergy Analysis of Graphene-Based Nanofluids in a Compact Heat Exchanger(TURKISH SOCIETY OF THERMAL SCIENCES AND TECHNOLOGY, 2022) KILINÇ, FERHAT; UYGUN, CİHAN ZEKİIn this study, the exergy analysis of graphene-based nanofluids in a compact heat exchanger is examined. In experiments using distilled water as the base fluid, graphene nano-ribbon and graphene oxide nanofluids were used at 0.01% and 0.02% of the volume concentrations. The experiments were carried out at 36, 40, and 44 oC fluid inlet temperatures and 0.6, 0.7, 0.8, and 0.9 m3/h mass flow rates. As a result of the calculations made for all temperature and flow rates, it was found that the exergy efficiency values of 0.01% by volume GO nanofluid were higher than the exergy efficiency of the other nanofluids used. Also, the exergy destruction values calculated for %0.01 GO were lower than the value of exergy destruction calculated for other nanofluids. It was concluded that the exergy efficiencies of nanofluids increased with the increase of the fluid flow rates and the inlet temperature of the heat exchanger. When the exergy efficiencies were compared according to the nanofluid concentrations, it was found that the exergy efficiencies decreased with the increase of the fluid concentration. It was examined that the exergy destruction values also increases with the increase of nanofluid flow rates, as well as exergy efficiency. When the exergy destructions were compared to the nanofluid concentrations, it was concluded that the exergy destructions increased with the increase of the nanofluid concentration. It was determined that the amount of increase in exergy destruction of GO nanofluid was higher than that of GNR.Öğe The experimental and numerical investigation on thermal responses of passive thermal protected batteries in different packs from low to high discharge rates(Springer, 06.07.2022) Temel Ümit Nazlı; Kılınç FerhatThis study contains experimental and numerical investigation of the shape effect of the pack on the performances of PCM (or GNP/PCM) based passive thermally protected battery packs. Also, the performances of the PCM and thermally enhanced GNP/PCM composite for battery thermal protection are compared from low to high discharge rates. The thermal response results show that the cylindrical pack performs worse than the rectangular pack in terms of the maximum temperature and maximum temperature difference performance criteria. For the maximum temperature restriction criteria, 7% GNP/RT44 composite, that has enhanced thermal conductivity, performs better at first, but then its performance deteriorates compared to RT44 depending on the increase of its viscosity. It was determined that 7% GNP/RT-44 extend the effective protection times by 95.8%, 73.3% and 28.0% at the discharge rates of 4.4 W, 6.6 W and 8.8 W, respectively.Öğe Thermal Protection Performances of the Macro and/or Nano Enhanced PCM in a Representative Battery Pack(NANOSCALE AND MICROSCALE THERMOPHYSICAL ENGINEERING, Nisan 2022) Temel, Ümit Nazlı; Kılınç, Ferhat; Coşkun, SerkanThis experimental study focused on the comparison of thermal protection performances of macro and/or nano enhanced organic PCM in a representative battery pack from low to high discharge rates. The macro/nano enhanced RT-44 provides the desired battery thermal protection requirements in terms of criteria such as maximum temperature and maximum temperature difference restriction and uniform temperature distribution throughout the battery pack. It increases the effective battery thermal protection time by 117%-32% depending on the discharge rates. While PCM thermal protection provides a more homogeneous temperature distribution throughout the battery pack, nano and/or macro enhanced one provides it throughout the cell. The macro enhancement essentially makes a major contribution to shortening the cooling time for the next use.Öğe Particle image velocimetry studies around a rectangular body close to a plane wall(2010) Gurlek C.; Sahin B.Flow structures around a rectangular body located close to a ground board in a free-surface water channel were investigated using the particle image velocimetry (PIV) technique. The rectangular body is set with ?=0° and ?=10° yaw angles referenced to the flow direction, and measurements were performed on the vertical and horizontal planes. The PIV technique provided instantaneous and time-averaged flow fields for Reynolds number ReH=1.2×104 based on the model height. For ?=0°, the results indicate that the flow structure in the wake region vary significantly with the elevation level from the ground surface. An asymmetric large circulating flow region is identified in the wake region for ?=10°. The instantaneous flow fields reveal the presence of small-scale vortices in the main flow over the separation line. These small-scale vortices coalesce to form larger-scale vortices. © 2010 Elsevier Ltd.Öğe Numerical investigation of fouling on cross-flow heat exchanger tubes with conjugated heat transfer approach(PERGAMON-ELSEVIER SCIENCE LTD, 2008) Kaptan, Y.; Buyruk, E.; Ecder, A.Although fouling on heat exchanger tubes is extensively investigated, due to the lack of energy resources, the effects of fouling on heat exchangers is still an important area of study and gaining more and more attention every day. In this study we investigated the effects of fouling on heat transfer and flow structures numerically for cross-flow heat exchanger tube geometry. The distributions of temperature, heat transfer coefficient and heat flux at the surface of fouling were obtained for single and double layer fouling cases. In the analysis, Reynolds number and the blockage ratio were fixed to 100 and 0.1 respectively. We used ANSYS software in our analyses and compared some of our results with the literature. (C) 2008 Elsevier Ltd. All rights reserved.
