Dogan Simsek

In this study, AISI 304 austenitic stainless steel was reinforced with five different Vanadium (V) contents through mechanical alloying, and the wear behavior of the produced alloys was evaluated. Response Surface Methodology (RSM) was used to optimize the V addition. Vanadium was incorporated at 0.1, 0.2, 0.4, 0.7, and 1 wt%. Wear tests were performed using a pin-on-disc setup under three loads (15, 30, 45 N) and sliding distances (400, 1200, 2000 m). The central composite design considered load, sliding distance, and V content (0, 0.4, 1 wt%) as input factors, while alloys containing 0.2 and 0.7 wt% V were used for validation. RSM analysis produced high correlation coefficients, with R² values of 92.46% for weight loss and 85.60% for the friction coefficient, indicating strong model reliability. Predictions showed good agreement with experimental data. The highest error in weight loss (12.44%) occurred in the alloy with 0.7 wt% V at 15 N and 400 m. Overall, the proposed model enables the prediction of weight loss and friction coefficient with an accuracy of approximately 88%.

In this study, an artificial neural network (ANN) was used to estimated the performance and exhaust emission parameters of a diesel engine running on diesel, biodiesel, and propanol fuel mixtures. In addition, the parameters estimated by ANN were tried determining the optimum operating parameter by using Response Surface Methodology (RSM). In the experimental study, propanol was added in 3 different ratios (5%, 10% and 20%) into 100% diesel, 80% diesel and 20% biodiesel fuel blends. In addition, engine tests, were made at 5 different engine speeds with 400 min-1 intervals between 1000 min-1 and 2600 min-1 revolutions at full load. In addition, HC (Hydrocarbon), CO (Carbon Monoxide), NOX (Nitrogen oxides) and Smoke emissions were measured during in the working. ANN model was developed for estimation of engine output parameters depending on fuel mixture ratios and engine speed. In the ANN results, the regression coefficients (R2) of the proposed model were found to be between 0.924 and 0.99. When the obtained ANN results were compared with the experimental results, it was seen that the maximum mean relative error (MRE) was 6.895%. It has been shown that the applied model can predict with a low error rate. The RSM results showed that the optimum operating parameters were 2034-min-1 engine speed, 74.667% diesel, 11.36% biodiesel and 15% propanol fuel mixture. In addition, in the validation tests of the model where the desirability was 0.7833%, the highest error rate was obtained as 7.37% as a result of NOX. As a result of the study, it was seen that RSM supported ANN is a good method for estimating diesel engine parameters working with diesel/biodiesel/propanol mixtures and determining optimum operating parameters.

The objective of this study designed in three steps is to evaluate the optimization of tribological performance in the elevated temperature of TiC reinforced A356 matrix composites, produced by mechanical alloying (MA), using the dragonfly algorithm (DA). In the first step, an experimental design is created to formulate the problem as an optimization problem with the help of regression modeling, and wear tests by adding a temperature module according to ASTM G99-05 standards are performed at various reinforced rates, operating temperatures, and loads. In the second step, regression models are fitted to the experimental results. In the third step, the dragonfly algorithm (DA) – one of the recent nature inspired metaheuristic optimization algorithms – has been adapted to optimize the formulated problem. The results of DA indicate that the optimum factor levels for the reinforced rate, operating temperature, and load are determined as 7%, 10°C, and 20 N respectively to optimize the responses, namely weight loss, wear rate, and friction coefficient.

This study investigated the wear performances of ZrO₂ reinforced 316L stainless steel matrix composite materials. The 316 L matrix was mechanically alloyed by adding three different amounts (wt. 1%, 2%, and 3%) of ZrO₂ for 60 minutes. Mechanically alloyed powders were shaped through a uniaxial hydraulic press under 800 MPa pressure, and thus, green compacts in Øx6 mm dimensions were produced. The green compacts produced were sintered at 1300 °C in a vacuum environment of 10⁻⁶ mbar for 2 hours. Sintered composites were characterized by hardness and density measurements and microstructure studies. The wear tests were carried out under ASTM G99-05 standards, through a pin-on-disc wear test device, exerting three different loads (10N, 20N, and 30N), and using four different sliding distances (500m, 1000m, 1500m, and 2000m). As a result of the studies, it was observed that the reinforcement material (ZrO₂), added to the matrix, was positioned at the grain boundaries. As the amount of reinforcement within the matrix increased, the hardness of the composites increased while their densities decreased. In the wear test results, on the other hand, the increase in the amount of reinforcement decreased the weight loss. As for the wear surfaces, the abrasive wear mechanism was dominant.

Bu çalışmada, Mekanik Alaşımlama (MA) yöntemiyle üretilen alüminyum matrisli hibrit (in-situ Al4C3 ve ex-situ Al2O3) kompozit malzemenin farklı çözeltilerdeki korozyon davranışları incelenmiştir. Alüminyum matrise %2 grafit ve %12 Al2O3 ilave edilerek hazırlanan tozlar mekanik alaşımlanmıştır. Mekanik alaşımlanan hibrit kompozit tozlar 750 MPa altında soğuk preslenmiş ve 600 °C sıcaklıkta 120 dk sinterlenmiştir. Üretilen AMK malzemelerin korozyon testleri %3,5 NaCl ve 0,1 M H2SO4 çözeltilerinde elektrokimyasal empedans spektroskopi (EIS) ve potansiyodinamik polarizasyon teknikleri kullanılarak yapılmıştır. Polarizasyon ölçümleri üç elektrot kurulumlu bir korozyon hücresinde (Ag/AgCl referans elektrotu, bir platin plaka ve karşıt elektrot) yapılmıştır. Mikroyapı çalışmalarında matrise ilave edilen Al2O3 takviyesinin tane sınırlarında kümelenme eğiliminde olduğu görülmüştür. Ayrıca matrise ilave edilen grafit’in yapıda tamamen çözünmediği iri grafit parçacıkları şekilde kaldığı görülmüştür. XRD sonuçlarında yapıda oluşması beklenen Al4C3 fazının oluştuğu belirlenmiştir. Korozyon sonuçlarda hibrit kompozit malzemenin NaCl çözeltisi içerisinde daha düşük potansiyel ve daha düşük akım yoğunluğu elde edilmiştir. Empedans ölçümleri sonucunda H2SO4 çözeltisinde daha küçük bir yarım daire çapına sahip Nyquist eğrisi elde edilmiştir. Sonuçlarda NaCl çözeltisi içerisinde korozyon direncinin H2SO4 çözeltisinden daha iyi olduğu belirlenmiştir. Korozyon yüzeyi incelemelerinde baskın korozyon mekanizmasının çukurcuk korozyonu olduğu görülmüştür.

Bu çalışmada, mekanik alaşımlama yöntemiyle üretilen alüminyum matrisli kompozitlerin aşınma performansı incelenmiştir. Tepki Yüzey Metodolojisi (TYM) Merkezi Birleşik Tasarım (MBT) kullanılarak belirli sürtünme katsayına bağlı olarak aşınma parametreleri optimize edilmeye çalışılmıştır. Farklı takviye miktarlarıyla (%6 ve %12) üretilen kompozit malzemelerin aşınma testleri farklı yük (5 N, 10 N ve 20 N) ve farklı kayma hızlarında (0,2 ms-1, 0,4 ms-1 ve 0,6 ms-1) yapılmıştır. Aşınma test sonuçlarında, optimum aşınma parametrelerini belirlemek için ağırlık kaybı (düşük en iyi) ve sürtünme katsayısı 0,54 (en iyi) yaklaşımı kullanılmıştır. Elde edilen sonuçlarda, ağırlık kaybı için en etkili parametrenin takviye miktarı ve kayma hızına kıyasla yük olduğu görülmüştür. Sürtünme katsayısı için ise yük ve kayma hızına kıyasla takviye miktarı en etkili parametre olduğu belirlenmiştir. Elde edilen optimum parametreler ise 9,24 N yük, 0,6 ms-1 kayma hızı ve %12 takviye miktarı olduğu belirlenmiştir. Çalışma sonucunda elde edilen parametreler kullanılarak yapılan aşınma testlerinde, ağırlık kaybı 8,536 mg, sürtünme katsayısı 0,522 olarak elde edilmiştir.

In this study, the microstructure and wear behaviours of aluminium composites, reinforced with different amounts of (3-12%) Al ₂ O ₃ and 2% (% vol.) graphite were investigated. The Al ₂ O ₃ and graphite were added to Al matrix and mechanically alloyed for 60 minutes. Subsequently, the mechanically alloyed powders were pressed under 700MPa pressure and sintered at 600 ^∘ C for 120 minutes. The produced aluminium composites were characterized by microstructure, scanning electron microscope (SEM), X-ray diffraction (XRD), density and hardness measurements. Afterwards, wear tests were carried out on a block on-ring type wear testing device, under three different loads and four different sliding distances. As a result, the hardness and density of composites were observed to increase due to the increase in the amount of reinforcement in aluminium composites. The highest hardness and density values were obtained in composite material containing 12% Al ₂ O ₃ . The wear tests, the lowest weight loss was also obtained in composite containing 12% Al ₂ O ₃ .