This study examines mass reduction methods and optimization techniques used in primary satellite structures and develops a new design method compatible with additive manufacturing technology. The proposed method aims to reduce mass in the mechanical infrastructure of satellites. To evaluate the efficiency of the developed approach, a satellite was initially designed using aluminum sandwich panels, and optimization studies were conducted while keeping the internal volume constant. Ribs were added to the panel design to enhance its modal stiffness. The shape of the ribs was determined through shape optimization, and their distribution was defined using size optimization based on strain energy distribution.
The results demonstrated a 20% reduction in the total weight of satellite panels. Additionally, the use of simple geometries preserved isotropic structural properties, allowing for analyses without the need for complex analytical methods. Panels compatible with additive manufacturing significantly reduced production time and eliminated unforeseen manufacturing defects commonly encountered in sandwich panels. The clean and simple geometry of the design also eliminated the need for special post-production cleaning processes. This study provides a lightweight and easily manufacturable alternative solution for primary satellite structures.

Modeling the behavior of materials under the combined effects of stress, deformation rate and temperature on the flow stress and damage that may occur is extremely important, especially because of the requirements in simulations such as metal forming, blast, chip removal, etc. In order to use the desired material in the analysis, the model parameters that will be needed must exist in advance. Not every material does not have parameters, and obtaining them requires costly and long-term efforts. Among these models, one of the most preferred ones in simulation programs are the parameters of Johnson Cook (JC) flow stress and damage models. The aim of this study is to economically obtain the JC parameters describing the mechanical behavior of low carbon EREGLI 1312 steel in simple tensile tests and low stress ratio reference with the help of simulations of the tests.

The damage model proposed by JC was used to predict the flow stress and damage behavior of our material. In order to determine the model parameters, tensile tests were applied to six different types of notched and unnotched specimens cut from plates at room temperature and under different speeds. Curve fitting and regression procedures were performed automatically with the program written for this purpose, and the data required for the calculation of the parameters were easily obtained by matching the simulated tests with the tensile tests. It was calculated that the parameters obtained can predict the material behavior at room temperature very closely for all strain rates. Compared to the test results, it can simulate the process of stress-strain variation until rupture with a small error of 3.63% on average.. In this research, the JC flow stress and damage model parameters estimated for EREGLI 1312 steel were found to be safely used in simulations such as metal bending and deep drawing.

Precision-casting is a casting process that minimizes porosity and has the power to produce exact shapes and sizes of parts. In the metal part production sector, precision-casting is the closest casting form to the final version of the part. Using single-use aluminosilicate molds in casting operations causes a storage problem after precision-casting, which adds to the expanding waste problem. Moreover, the disposal of this waste without recycling poses environmental concerns. Interestingly, the waste contains zircon minerals, which are well-known for improving refractories' mechanical, thermal, and corrosion-resistant qualities. The aim of this study is to produce fireclay refractory bricks that have decreased manufacturing costs, increased mechanical and thermal properties, and are improved by the addition of precision-casting sand.
Density and open porosity were determined using the Archimedes principle. Cold crushing strength was tested according to ASTM-C133, and three-point bending tests were performed according to ASTM-C1161-90 standards. For thermal shock resistance, samples were heated to 1000°C for 30 minutes and then quenched in water. Finally, microstructure analyses were conducted using a scanning electron microscope (SEM).
Compared to the additive-free fireclay refractory, samples containing X2, Y2, and Z1 precision-casting waste sand (PCWS) showed increases in 3-point bending strength by 27%, 10%, and 5%, respectively, after undergoing thermal shock testing. Similarly, with the addition of PCWS, X2 and Y2 samples exhibited increases of 17% and 33% in cold crushing strength (CCS) values.

In this study, transverse vibration of a beam under a moving singular load and a moving moment is investigated. A simply supported beam with intermediate vertical supports modeled according to Euler-Bernoulli beam theory. The supports are modeled as consisting of a linear spring and a linear damper. The moving force and the moment, the spring force and the damper force are expressed using Dirac delta functions in the equations of motion. Obtaining the exact solution for this problem with other methods are quite lengthy and complicated. Beam must be divided into spans between each support. Each span must be solved separately with different set of coordinates having same boundary conditions on support points. As the number of support increases, solution becomes more complicated. However, the present method can be used to solve the problem for the whole beam length without having to separate into various spans regardless of number of supports. Dirac delta functions are converted to series expansions which allows us to get exact solution in form of series expansion. This solution than can be easily calculated by a computer. Dynamic responses of several cases such as various number of supports; different support points; various moving load, moving moment and axial load combinations are examined.

In this study, modelling of the Pyrolytic oil production system using Artificial Neural Networks (ANNs) was conducted with oak acorn, which can be considered as forest waste. The parameters used in the pyrolytic oil production system were determined as reactor temperature, nitrogen gas flow rate, biomass particle size, and heating rate. In experimental studies, the highest pyrolytic oil production was achieved at 500 °C temperature, 1.5 L/min nitrogen gas flow rate, 5 °C/min heating rate, and 0-2 mm biomass particle size, with a product yield of 17.83%. 164 different Multi-Layer Feed Forward (MLFF) ANN-based network architectures were trained for 20,000 iterations using the data obtained from the pyrolytic oil production system. In the training process, various network architectures incorporating activation functions such as TanSig, LogSig, and RadBas with one and two hidden layers were utilized. According to the results obtained from the studies, the Multi-Layer Feed Forward ANN-based Pyrolytic Oil Production System structure, which has a single hidden layer and contains 16 LogSig non-linear activation function neurons, was the network structure with the best performance with a value of 1.08E-15.

The effects of Tungsten Cobalt (WCo) nanoparticle contribution on the shear and bending strengths are examined in adhesively bonded single-lap joints made with glass fiber-reinforced polymer (GFRP) substrates in this study. WCo particles were synthesized via mechanical alloying and added to epoxy adhesives at varying concentrations (1.0, 3.0, and 5.0 wt.%). The adhesive mixtures were used to bond GFRP plates in single-lap joints(SLJ), and their mechanical performance was evaluated under shear and bending loading conditions. The shear strength results indicate that the incorporation of 1.0 wt.% WCo increased shear strength by 68.5%, while 3.0 wt.% WCo yielded the highest improvement at 136%. However, the addition of 5.0% WCo led to a reduced enhancement (60%) due to nanoparticle agglomeration and local stress concentrations. Notably, the maximum bending stress was observed in the 3% WCo-containing specimens. Specifically, the bending load increased by 51.5%, from 61.96 MPa in the pure epoxy specimen to 93.85 MPa in the 3% WCo-reinforced specimen. Failure surface analysis revealed that WCo-reinforced samples exhibited ligt-fiber tear, thin-layer cohesive failures, and enhanced bonding properties due to increased viscosity and the filling of micro-voids. These findings suggest that WCo nanoparticles effectively improve the shear and bending performance of epoxy adhesives by enhancing interfacial bonding, ductility, and stress distribution mechanisms. The study provides insights into the potential of WCo-reinforced adhesives as a cost-effective and high-performance solution for engineering applications.

In this study, the design guideline for the power stage of true-bridgeless AC-DC power factor corrector(PFC) converter is provided, and working principle is explained. The dynamic responses, total harmonic distortion and power factor of true-bridgeless PFC converter are analyzed using predictive current control with pulse train strategy techniques and average current mode control for different load conditions. The main mathematical framework of the control algorithm is introduced, simulation and control charts are presented. The simulations are performed to illustrate the advantages of the method and compare it with average current mode control approach. According to the simulation results, input current complies with the IEC61000-3-2 standards. In the control of the converter using the predictive current control with the pulse train strategy, it is observed that dynamic response of the converter is improved compared to average current control method.

Titanium implants are mechanical systems where tribocorrosion is frequently observed at the interface between the implant and the abutment alloy. In this paper, important parameters in terms of tribocorrosion such as abrasion coefficient, abrasion volume loss and corrosion rate were determined experimentally in a laboratory environment by preparing a sufficient number of samples obtained from the field for this material (Titanium-Ti6Al4V), which is actively used in surgeries. Comprehensive analysis of these mechanical systems in body-like environments contributes to a better understanding of the material loss caused by abrasion and corrosion interactions occurring at the interface between the implant and the abutment alloy. The samples were subjected to dry sliding wear with the pin-on-disc system in accordance with the relevant standards for a certain number of cycles, during which abrasion volume loss and friction coefficient were measured simultaneously. To create an experimental environment closer to real conditions, a small part of the material surfaces interacted with artificial body fluid in accordance with body pH levels and changes in corrosion kinetics were observed. The results of these experiments were examined to evaluate the degree to which titanium is resistant to material loss due to abrasion and corrosion in body implants. Additionally, the morphological features of the abraided and corroded surfaces of Ti6Al4V alloy were analyzed and interpreted using scanning electron microscopy (SEM) and digital image processing techniques.

As the importance of energy resources increases, the issue of efficiency in the equipment becomes important. Especially in these days when efforts to reduce carbon emissions It is inevitable to use more efficient equipment are intensified. HVDC systems, in electricity transmission which provide transmission over long distances, are included in this scope with their low line losses. With direct current transmission is not yet carried out in the Turkish electricity transmission system. In this study, in order to compare AC and DC transmission options, an HVDC system was modeled by converting the existing AC lines in the into DC lines. 600 km long who lines, were combined and converted into a DC line and compared with AC lines transmitting at the same distance and features. In addition, a detailed fault analysis study was carried out, which should be carried out in detail for the protection of the system and equipment selection. A fault simulation circuit was created with the PSCAD program for fault analysis in the HVDC transmission system. For DC line Pole-to-pole, pole-to-ground faults and AC three-phase short circuit fault situations are simulated. The effects of fault resistance and limiting reactor values on the fault current were also examined.

In this study, 9 different substances (egg, rotten egg, mint, naphthalene, lemon, angelica root, acetone, nail polish and rose water) were distinguished by using an electronic nose using 8 metal oxide gas sensors. In the study, fuzzy logic method and artificial neural networks were used for data classification. In the data classification process performed using artificial neural networks, the classification performances were examined using different network architectures. In the classification process carried out with the fuzzy logic method, an attempt was made to increase the classification accuracy with the different membership functions used. In the classification process performed with artificial neural networks, 96.41% classification accuracy was achieved by using logarithmic sigmoid and hyperbolic tangent functions in the hidden layer and output layer, respectively. 8 artificial nerve cells were used in the hidden layer of this artificial neural network, where the highest accuracy value was achieved. In the classification process carried out with the fuzzy logic method, the classification accuracy was achieved as 95.55% by using the bell membership function.

Heart diseases are one of the leading causes of death worldwide, and early diagnosis and proper treatment planning are critical for patients' quality of life and survival rates. This study aims to comprehensively investigate the performance of machine learning algorithms in heart disease diagnosis on the Weka platform. Regression, classification and clustering algorithms were applied on the data set obtained using data mining methods, and then evaluated with performance measures such as precision, accuracy and F-score. The findings reveal that the various algorithms examined provide success in the diagnosis of heart disease. The obtained results provide guidance for both healthcare professionals and researchers on the application of machine learning techniques to heart disease diagnosis and contribute to the improvement of patient diagnosis processes.

In this research, a novel approach for classifying colon cancer was developed by employing two convolutional neural network (CNN) models, namely GoogLeNet and AlexNet. This approach involves training CNNs with histopathological images segmented into color clusters using an augmented k-means clustering algorithm, rather than utilizing original-raw images. This method was applied to 20 datasets with distinct structural and characteristic features, derived from larger datasets comprising both original and segmented images. The datasets were used to train and test CNN models. The results indicate that AlexNet, trained with segmented images, showed a 2% to 23% increase in accuracy performance, while GoogLeNet's accuracy performance improved by 2% to 27%. Notably, the proposed approach yielded higher accuracy with datasets containing non-homogeneous data.

In this paper, a quality of service supported (QoS) medium access control (MAC) protocol designed to transmit two different data traffic types, namely real-time and non-real-time, with different bandwidth requirements for Internet of Things (IoT) applications is proposed. A new fair channel allocation-based algorithm used in the proposed MAC protocol efficiently performs bandwidth allocation for two different data traffic types. In this study, TDMA is chosen as the MAC technique due to its tendency to flexible bandwidth allocation. With the TDMA MAC technique, QoS support is provided to the related IoT nodes by allocating one or more time slots according to the bandwidth requirements of the nodes. The analytical model of the proposed MAC protocol has been developed by using a two-dimensional continuous-time Markov chain and its performance has been analyzed in an example network scenario. Performance analysis is carried out based on call blocking probability, throughput, utilization and call completion rate. In addition, a Monte Carlo simulation of the proposed MAC protocol has been performed, and the results obtained from the analytical model have been confirmed with the results obtained from the simulation model. According to the results obtained from the sample networking scenario in which the proposed MAC protocol is utilized, when the total load of the network is 10, the call blocking probability of real-time users is 10%, and the call blocking probability of non-real-time users is 26.6%. Under the same load conditions, the call completion ratio for non-real-time users is 80.23%, while for real-time users this ratio is 46.80%.

Compacted bentonite as a buffer and/or backfill material in deep geological repositories is recommended to safely dispose of high-level nuclear waste. The high swelling potential and low permeability properties of bentonite are the main bases for this recommendation. Bentonite used in the repositories will hydrate with groundwater to form a self-sealing barrier while exposed to the high temperature emitted from the canister. In this process, the outer zones tend to swell, while the zones close to the canister may become unsaturated due to the high temperature. These conditions can affect the hydraulic and mechanical properties of bentonite and limit its long-term performance. Therefore, determining soil-water characteristic curves and swelling pressure at different thermal conditions is of great importance for evaluating groundwater movement and sealing properties of bentonite. Temperature cycles can adversely affect critical properties of bentonite, such as water retention capacity and swelling pressure. In this study, Etibor-48 (E-48) boron mineral, known for its low thermal expansion properties, was used as an additive to improve the engineering properties of bentonite under high temperature conditions. E-48 mineral was added to the compacted bentonite at 10% and 20% ratios, and the swelling pressure and soil-water characteristic curves of the mixtures were investigated at room temperature and high temperature (80 °C) conditions. The swelling pressure tests were performed using constant volume method in an oedometer system and the soil-water characteristic curves were determined using the vapor equilibrium technique. The results showed that high temperature and E-48 addition decreased the water retention capacity and swelling pressure of bentonite. It was also found that the drying path did not overlap with the wetting path, and the additive-free bentonite had a higher water retention capacity than the E-48-added mixtures. These results provide important insights into understanding the effect of additives to evaluate and optimize the performance of bentonite-based buffer materials under high-temperature conditions.

Promoting bicycle use fosters health, orderliness, and improved transportation conditions. As a key component of active mobility, the global rise in bicycle usage reflects its growing importance. In developed cities, the use of conventional and e-bikes has increased, with cycling rates surpassing 7%. Despite the limited use in different cities, efforts to enhance bicycle usage are ongoing, although hindered by traffic safety issues and infrastructure deficiencies. This article conducts a detailed literature review to identify the necessary steps for increasing the share of bicycles in urban transportation. The review explores the impact of traffic infrastructure, environmental factors, and user behavior on urban bicycle use. Since the 1970s, these topics have been examined through various methods worldwide. This study reviews 89 articles published between 2010 and 2023, presenting a multifaceted analysis encompassing bicycle infrastructure, user behavior, and environmental factors affecting cycling. Key findings highlight the importance of well-planned bicycle infrastructure in enhancing safety and reducing traffic stress. Segregated bicycle lanes, effective intersection designs, and comprehensive cycling networks are crucial for promoting urban bicycle use. Environmental factors such as noise and air pollution, weather conditions, and urban design significantly influence cycling behavior. The review reveals that cities with robust cycling infrastructures and supportive policies, such as Copenhagen and Amsterdam, exhibit higher bicycle usage rates and improved urban mobility. Conversely, cities with inadequate infrastructure face challenges integrating bicycles as a viable transportation mode. The study suggests that adopting best practices from leading cycling cities and addressing local challenges can significantly enhance urban cycling. By providing a comprehensive overview of global research on urban bicycle use, this study aims to guide urban planners, policymakers, and researchers in developing effective strategies for promoting cycling as a sustainable and healthy transportation alternative. The insights gained can contribute to creating safer, more efficient, and environmentally friendly urban transport systems. This approach is vital for increasing bicycle usage and ensuring safe cycling practices, ultimately contributing to sustainable urban development.

University campus transportation plans should focus on reducing private transportation trips, similar to strategies used in urban areas. This not only promotes an environment-friendly, sustainable campus transportation system but also ensures safer transportation for non-motorized modes. In this context, it becomes crucial to identify the factors that influence mode choice. In this paper, by establishing a binary logit model, we estimate the factors influencing the choice of using car mode for commute trips among the academic staff of Ege University, Türkiye. The most significant variables found in this study are age, academic title, and trip durations for both car and public transportation. These findings are informative and provide a basis for implementing measures to reduce car trips, thereby promoting a green university campus.

This study evaluates the efficiency of xylem-based filters derived from five tree species—Pinus pinea, Populus nigra, Pinus brutia, Tilia tomentosa, and Quercus petraea—in removing turbidity and color from Bartýn River water samples. Filtration experiments were conducted under varying pressure conditions (5 psi, 10 psi, and 15 psi) to assess the performance of each xylem filter based on flow rate, turbidity removal, and color reduction. The results highlighted that gymnosperm species, particularly Pinus pinea, exhibited high turbidity (up to 99.36%) and color removal efficiency (up to 95.58%) at lower pressures. Conversely, angiosperm species demonstrated higher flow rates but lower filtration efficiencies. Durability analysis of pit membranes revealed that high pressure could compromise their integrity, slightly reducing efficiency. These findings indicate that xylem-based filtration is a promising, cost-effective, and eco-friendly water purification method suitable for areas lacking advanced water treatment systems. Further optimization of pressure conditions and enhanced pit membrane durability are recommended to maximize efficiency and longevity.

The aim of this study is to decide on the municipal solid waste (MSW) management alternatives for the minimum criterion of Zero Waste Regulation (ZWR) which is binary separation at source. To achieve this aim, analytical hierarchy process (AHP) was used as a multi-criteria decision-making tool. Five different waste management alternatives were selected as decision points. The main criterion affecting the decision points was binary separation of solid waste at source, and five environmental, four economic, three social and three technical criteria were selected as sub-criteria. Expert opinions were consulted to obtain binary comparison data both within the sub-criteria themselves and for each criterion of MSW management alternatives. The survey prepared using Google Forms. Using the geometric means of the numerical data obtained from expert opinions, binary comparison matrices were created for each sub-criteria group within the scope of the ZWR minimum criterion and the necessary AHP analysis processes were applied. According to the results obtained; MSW management alternative preferences were calculated as material recovery(0.381)> thermal process(0.193)> biomethanization(0.187)> composting(0.125)> sanitary landfill(0.112) for environmental; sanitary landfill(0.357)> material recovery(0.247)> composting(0.193)> biomethanization(0.097)> thermal process (0.054) for economic; material recovery(0.393)> composting(0.233)= biomethanization(0.233)> thermal process(0.086)> sanitary landfill(0.055) for social; material recovery (0.381)> sanitary landfill(0.315)> composting(0.143)> biomethanization (0.114)> thermal process (0.047) for technical criteria. As a result; in case of applying binary separation at source, it has been determined that the priority of municipal solid waste management alternative is material recovery in terms of environmental, social and technical criteria, and sanitary landfill in terms of economic criteria.

In this study, PVDF fibers were produced using centrifugal spinning (CS) and solution blowing (SB) methods, and their comparative characterization has been carried out. While defect-free mats composed of smoother, thicker and more uniform fibers were obtained with the CS method, mats containing fine and crimped fibers and highly entangled fiber bundles were produced with the SB method. The average fiber diameters were measured as 0.827 ± 0.365 μm for fibers produced by CS and 0.356 ± 0.168 μm for those obtained by SB. It was determined that the PVDF fibers produced by both methods predominantly exhibited the β-phase with a small amount of the α-phase. In the production where the same amount of solution was used, fiber mats of similar thickness were obtained, while the basis weight of the mats produced by the CS method was approximately half that of the SB samples. The SB samples, containing both thin fibers and thick fiber bundles, exhibited a more compact structure. Therefore, the filtration efficiency of the samples with the same thickness was higher for SB. However, mats with the same basis weight showed similar filtration efficiency. These results indicate that both methods are suitable to produce PVDF fibers. The CS method enables the production of thicker but defect-free fibers, and the production methods do not significantly affect the fiber's crystalline structure. Additionally, fiber diameter, morphology, and basis weight of the mats significantly influence filtration performance. The compact structure of the fibrous mat from SB resulted in a higher filtration efficiency.