The aim of this study is to experimentally investigate the effects of applying a magnetic field generated by ten neodymium magnets sources on the thermal performance and flow behavior of a magnetic nanofluid (Fe₃O₄–H₂O) flowing through a copper pipe to a constant heat flux. This research stands out for its innovative approach in comprehensively evaluating the effects of a magnetic field on the heat transfer characteristics of ferrofluids with three different volumetric concentrations flowing under the influence of the magnetic field. This multifaceted approach enables an in-depth investigation of how each parameter influences the heat transfer performance of the nanofluid. While previous studies have predominantly concentrated on limited set of parameters, the present study offers a comprehensive analysis encompassing multiple variables. The findings revealed that magnetic field intensity and volumetric concentrations significantly influence convective heat transfer. In the experiments, it was observed that in the absence of a magnetic field, both the Nusselt number and friction factor increased with the volumetric concentration of the nanofluid, whereas under the influence of a magnetic field, the Nusselt number increased and pressure drops were observed with increasing Reynolds number. This experimental study investigating the effect of magnetic nanofluids on heat transfer emphasizes the interaction between flow conditions and magnetic effects, providing a significant contribution to the field. In these experiments, the greatest increase in the Nusselt number occurred at Re = 7050 in the nanofluid with 1.5% concentration and was calculated as 48.14%. In this study, it was observed that heat transfer increased when the concentration of the nanofluid increased, magnetic field was applied, and the Reynolds number increased. The comprehensive nature of this research presents novel opportunities for optimizing thermal systems through the application of magnetic nanofluids.

Purpose: Engine bearings are among the most critical components in rotating machinery, and their failure can often lead to the entire system stopping. Therefore, accurate and reliable monitoring of bearings is crucial for predictive maintenance and fault prevention. However, noisy signals, variable operating conditions, and the simultaneous occurrence of multiple fault types make it difficult to achieve high accuracy in fault diagnosis. This study proposes a new hybrid approach to overcome these challenges. Methods: The proposed method consists of five main stages. In the first stage, Empirical Mode Decomposition (EMD) based preprocessing is applied to remove noise and unwanted components from the vibration signals. In the second stage, feature extraction is performed from the processed signals using two different methods: Detrended Fluctuation Analysis (DFA) captures the fractal dynamics and statistical structure of the signals, while a Long Short-Term Memory (LSTM) network learns the complex time-dependent relationships of the signals. In the third stage, these obtained features are combined to obtain a more meaningful representation. In the fourth stage, the K-Means clustering method is used to group the features to increase the accuracy of the classifiers. In the final stage, three powerful classification algorithms, namely XGBoost, Random Forest, and Support Vector Machines (SVM), are used to classify bearing faults. The HUST engine bearing dataset used in this study enabled us to evaluate the performance of our method under realistic conditions because it contained data collected under different loads, speeds, and fault types. Results: Experimental analyses showed that the proposed hybrid structure exhibited superior performance compared to single feature sets. In particular, the combined use of DFA and LSTM-based features increased the generalizability and diagnostic power of the system. Furthermore, classification accuracy was further improved thanks to the feature vectors supported by EMD preprocessing and K-Means clustering. The obtained results show that the best performance was achieved when DFA + LSTM features were used together with EMD and K-Means and with the XGBoost classifier. In this case, 98.46% accuracy, 97.20% sensitivity, 97.24% precision, and 97.27% F1-score values were achieved. Conclusion: This study demonstrates that the proposed hybrid approach yields reliable results under different operating conditions and in data sets containing multiple fault types. The proposed method provides a robust and generalizable solution for predictive maintenance applications in industrial systems, making significant contributions to the safety and availability of rotating machinery.

Parallel to the developing technology and the increasing population, the energy requirement is increasing day by day. Turkey's dependence on foreign sources of energy constitutes a significant budget in terms of energy costs. In this context, in Turkey, renewable energy sources with high potential are gaining importance. Fossil energy sources cause environmental pollution and threaten human health more and more every day. For this reason, the use of renewable energy sources should be encouraged and widespread. With a good energy needs analysis, producer costs will be reduced and efficiency will be increased.Solar energy is an efficient resource in electricity generation. Increase the efficiency of the solar panels used, increases the amount of electricity produced. However, the change in the angle of the sun's rays has an adverse effect on energy production. In this study, it was aimed to increase the efficiency of the solar panels by moving according to angle of sunlight. For this purpose, solar panel was driven by the servo motor and it was directed to the sunlight. Servo motor's PID control was implemented using the MATLAB program. The energy analysis made is given in the results.Solar energy is an efficient resource in electricity generation. Increase the efficiency of the solar panels used, increases the amount of electricity produced. However, the change in the angle of the sun's rays has an adverse effect on energy production.In this study, it was aimed to increase the efficiency of the solar panels by moving according to angle of sunlight. For this purpose, solar panel was driven by the servo motor and it was directed to the sunlight. Servo motor's PID control was implemented using the MATLAB program. The energy analysis made is given in the results.

Tr en Bu çalışmada kanatçık sayısı farklı olan kanatçıklı iç borulu ısı değiştiricisinin dik konumlandırılmasıyla ısı transferinin artırılması deneysel olarak ele alınmıştır. Çalışmanın diğer çalışmalardan en önemli farkı ısı değiştiricinin dik konumlandırılmasıdır. Dik konumlandırılan ısı değiştiricisindeki ısı transferini analiz etmek için deney seti kurulmuştur. Isı transferleri ve basınç düşümleri farklı iç borularda incelenmiştir. Her boru için akış türbülanslıdır. Hem kanatçıklı iç boru için hem de iç boru ile dış boru arasındaki aralıklar için hesaplamalar yapılmıştır. Elde edilen sonuçlara göre Reynolds sayısı ve Nusselt sayısı hesaplanmış, grafikleri çizilmiştir. Deney sonuçlarından elde edilen değerler Petukhov’un eşitliğinden çıkan değerlere oldukça yakındır. Yapılan deneylerde en iyi ısı transferinin kanatçık sayısı en fazla olan iç boruda olduğu saptanmıştır. Kanatlı kısım uzunluğu 300 mm olan boruda düz boruya göre ısı transferi %147.38 artarken basınç kaybı da %131.25 artmıştır. Kanatçıklı iç borulu ısı değiştiricilerinde ısı transferi miktarı düz boruya göre daha iyi olmaktadır. Fakat kanatçıkların etkisiyle basınç düşümlerinde artışlar olmaktadır. In this study, increasing the heat transfer by the vertical positioning of the finned inner pipe heat exchanger which has different fin number has been discussed experimentally. The most important difference of the study from other studies is the vertical positioning of the heat exchanger. A testing set was installed to analyze the heat transfer in the vertically positioned heat exchanger. Heat transfers and pressure drop were analyzed at different inner pipes. The flow is turbulent for each tube with different fin number. Calculations were made both for finned inner pipe and annular spacing between inner pipe and outer pipe. All results were compared with each other to obtain the best results. According to the results, Reynolds number and Nusselt number were found and graphed. The values obtained from the experimental results are very close to the values derived from Petukhov's equation. In experiments, it was found that the best heat transfer was in pipe which has most fin number. In pipe which has 300 mm finned length, the heat transfer increased by 147.38% and also the pressure drop increased by 131.25% in comparison with straight tube. In finned inner tube heat exchangers, the amount of heat transfer is better than in straight tube. But with the effect of fins, pressure drops increase.

Hydrostatic measurement, a method traditionally used to measure the density of solid bodies, is not suitable for all solid bodies. This method is undesirable for solid materials that interact with water and lose their properties. In addition, this method is not suitable for porous objects because measurements in water are erroneous and can damage material samples due to the ability of some solid materials to absorb water. In this study, a new density measurement technique has been developed and evaluated to measure the density of rigid objects by means of nonstandard geometry. The density of objects with distorted geometry was measured pneumatically using communicating vessels logic and using the ideal gas equation. An experiment set has been developed, improved and evaluated. Through this technique, the measurement accuracy of the density of the sample tested was determined with an accuracy of 0.08 %.

In this research, the effect of Al₂O₃/water-based nanofluids on the heat transfer enhancement in heat exchangers with rotating straight inner tube was examined. Nanofluids including Al₂O₃ nanoparticles with 0.25 and 0.5% volume concentrations and pure water as a base fluid were obtained. The aim of the study is to experimentally investigate and compare the influence of straight inner tube on the performance of a double-tube heat exchanger at different flow rates, different capacity ratios (0.25, 0.5, 0.75, 1), different speeds of rotation (0 rpm, 100 rpm, 150 rpm, 200 rpm, 300 rpm, and 500 rpm) and by using the Al₂O₃/water-based nanofluid at volume concentrations of nanoparticles 0.25 and 0.5%. In the experiments for straight tubes, the flow is turbulent. In order to determine the heat transfer enhancement, the experimental data were compared for pure water and nanofluids. According to the results, the Nusselt number, pressure loss, and efficiency of heat exchanger were measured. The validation of the experimental results was proved by plotting the graphs of Nusselt numbers versus Reynolds numbers for nanofluids having various volume concentrations. From the experiments, the correlations for Nusselt number were obtained and experimental results were compared with the literature data by drawing graphs. In the experiments using nanofluids, their thermal performance increased considerably compared to pure water. The experiment that provides the best increase in heat transfer is that using the Al₂O₃/water-based nanofluid with 0.5% volume concentration at the speed of rotation 300 rpm.