Ahmet Calik
@mehmetakif.edu.tr
Burdur Mehmet Akif Ersoy University
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Ahmet Çalık, Salih Akpınar, and Murat Demiral
Elsevier BV
Ahmet Çalık
Frontiers Media SA
In this research, we experimentally examined how incorporating HHO into blends of 20% canola biodiesel with 80% diesel and 40% canola biodiesel with 60% diesel impacts the engine’s performance and its emission traits. Canola oil, widely used in Europe, served as the biodiesel base. The addition of HHO, recognized for its potential to improve combustion efficiency and reduce emissions which were deteriorated by biodiesel addition. The findings revealed decrement on fuel consumption as 5.74% and 4.43% and rise in thermal efficiencies as 3.92% and 3.97% with HHO addition compared to B20 and B40, respectively. Besides that, CO emissions were reduced significantly up to 35.43%, while CO2 emissions decreased moderately up to 14.93% compared to diesel fuel. On the other hand, biodiesel and HHO addition increased NOx emissions as 49.80%. Utilization of biodiesel and HHO in diesel engines offers a straightforward way to reduce emissions and enhance fuel efficiency, addressing environmental issues and promoting sustainable transportation.
Salih Akpinar, İlyas Hacısalihoglu, and Ahmet Çalık
Informa UK Limited
Abstract Studies to increase the joint strength of adhesively bonded joints used in the aerospace and automotive sectors are met with interest in the field of engineering. Many different methods are used to increase the strength of the bonded joint, and one of these methods is to change the joint geometry. This study aims to increase the joint strength by changing the geometry of the joint with the same adhesive area condition. In the study, the DP460 structural adhesive was used as the adhesive, the AA2024-T3 aluminum alloy was used as the adherend, and the One Step-Lap Joint (OSLJ), Double-Strap Joint (DSJ), and Stepped Double-Strap Joint (SDSJ) was used as the joint types. The joint strengths of the joints obtained by using different step lengths and different patch lengths for these three types of joints with the same adhesive area were investigated experimentally and numerically. Firstly, the strengths of the SLJ type obtained by using four different step lengths and the DSJ type obtained by using patches of four different lengths were investigated. In the light of these investigations, the mechanical properties of the joints obtained by changing the step length and patch length in the SDSJ type, a new joint type with the same adhesive area, were obtained. As a result, compared to the OSLJ type with the same adhesive area, the joint strength of the DSJ type increases by approximately 45% to 67%. In addition, while the strength of the new type of joint (SDSJ) obtained in the presented study increases between 7% and 35% according to the DSJ type, it increases between 56% and 126% according to the OSLJ type. These increases in the joint strength vary according to the bonding area. Additionally, in the presented study, experimental data were compared with numerical analysis, and it was observed that the data were quite consistent with each other.
Ahmet Çalık and Salih Akpinar
Elsevier BV
Ahmet Çalık, Erdi Tosun, Mustafa Atakan Akar, and Mustafa Özcanlı
EDP Sciences
Efforts to reduce the dependency on fossil-based fuels have intensely been researched by scientists recently. Therefore, in internal combustion engines, the usability of various alternative fuels is still being evaluated. The present study experimentally focused on the illumination of the combined impacts of nanoparticle additives and hydrogen fuel on the performance and emission characteristics of a compression ignition engine. For this purpose, diesel fuel and combinations of diesel fuel, terebinth oil biodiesel, titanium dioxides nanoparticle, and hydrogen were utilized. Reduced engine performance caused by biodiesel was compensated with the use of nanoparticles. Further improvement was also observed with hydrogen addition. Emission results showed that carbon monoxide (CO) emission values can be reduced with biodiesel, nanoparticle additive, and hydrogen since they all have positive effects to enhance combustion quality and avoid incomplete combustion. On the other hand, oxides of nitrogen (NOx) emission was increased due to a rise in cylinder temperature with the use of biodiesel, nanoparticle, and hydrogen.
Mustafa Özcanlı, Erdi Tosun, and Ahmet Çalık
Wiley
AbstractIn this study, effects of iron oxide (Fe3O4) and hydrogen (H2) additions into 20% sunflower biodiesel + 80% diesel (B20) operated compression ignition engine performance and emissions are evaluated. Diesel fuel (D) is selected as a reference fuel for comparison purpose. Reduced performance level with B20 can be recovered with use of nanoparticle and hydrogen due to their superior combustion characteristics. In comparison to diesel, B20 mixture has caused to reduction on power by 6.44% while addition of nanoparticle and hydrogen (H_B20_Fe) have increased power by 5.76%. B20 mixture led to decrease carbon monoxide (CO) emission by 7.92% whereas nanoparticle and hydrogen addition have caused further decrement by 12.35% compared to diesel. Diesel shows best nitrogen oxides (NOx) emission characteristics of all. Increment levels are 7.24% and 12.94 for B20 and H_B20_Fe, respectively.
Simay Bayramoglu, Salih Akpinar, and Ahmet Çalık
Springer Science and Business Media LLC
M. Kerem Ün and Ahmet Çalık
Elsevier BV
Sefa Yıldırım, Erdi Tosun, Ahmet Çalık, İhsan Uluocak, and Ercan Avşar
Informa UK Limited
ABSTRACT The present paper investigates the prediction of vibration, noise level, and emission characteristics of a four-stroke, four-cylinder diesel engine fueled with sunflower, canola, and corn biodiesel blends while H2 injected through inlet manifold using two different artificial intelligence methods: artificial neural network (ANN) and support vector machines (SVM). The aim of using these methods is to predict vibration, noise, carbon monoxide (CO), CO2, and NOx based on the initial experimental study by varying engine speed, blends of biodiesel, and H2 energy substitution ratio. Experimental data were gathered from the literature. For the ANN method, LevenbergMarquardt backpropagation training algorithm with logarithmic sigmoid and linear transfer function for hidden and output layers, respectively, gives the best results for prediction of vibration, noise, and emission characteristics. For SVM, a regression model is implemented with Gaussian kernel function. Results show that the ANN performs better than SVM, and the best mean average percent error and R2 for the models developed are 2.03 and 0.988 for vibration acceleration, 0.39 and 0.9615 for noise, 7.27 and 0.8549 for CO, 5.09 and 0.9398 for NOx, and 2.21 and 0.993 for CO2 values, respectively. Eventually, it is found that the ANN method is a good choice for simulation and prediction of dual fueled hydrogen sunflower, canola, and corn biodiesel blends.
Mustafa Özcanlı, Hasan Serin, and Ahmet Çalık
Elsevier BV
D. Yarımpabuç, K. Celebi, A. Çalık, and M.S. Horpan
Elsevier BV
Ahmet Çalık, Sefa Yıldırım, and Erdi Tosun
Elsevier BV
Erinç Uludamar, Erdi Tosun, Gökhan Tüccar, Şafak Yıldızhan, Ahmet Çalık, Sefa Yıldırım, Hasan Serin, and Mustafa Özcanlı
Elsevier BV
Mustafa Ozcanli, Mustafa Atakan Akar, Ahmet Calik, and Hasan Serin
Elsevier BV
Ahmet Çalik and Sefa Yildirim
Springer Science and Business Media LLC
Erdi Tosun and Ahmet Çalık
Elsevier BV
Kerem Ün and Ahmet Çalık
Informa UK Limited
ABSTRACT Cortical bone is an inhomogeneous and anisotropic tissue subjected to large loads during typical daily activities. While studies assuming isotropic material properties are frequent, anisotropy and inhomogeneity of cortical bone have been rarely taken into account. Moreover, the question, whether an assumption of anisotropy and inhomogeneity has an impact in the mechanical analysis of cortical bone, has not been explored in the literature. This study explores the relevance of anisotropy in human cortical bone. The cortical bone model has been divided into six radial regions and a different set of orthotropic material properties has been assigned to each region. This inhomogeneous and anisotropic elastic tibia model has been compared with a corresponding isotropic model under various loading modes using the finite element method. In particular, the variation in the maximum von Mises stress and strain values has been observed along the bone axis. We have observed that the isotropic model may overestimate the maximum von Mises strain up to 15% under pure compression and underestimate up to 50% under pure torsion relative to the inhomogeneous–anisotropic model. Our results suggest that consideration of anisotropy and inhomogeneity of the bone may make a significant difference in the predicted maximum von Mises strain values, which can be important for strain-based damage accumulation studies and fracture risk evaluation.
Ahmet Çalık and Sefa Yıldırım
Elsevier BV