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Yayın Comparison of classical and heuristic methods for solving engineering design problems(2024) Tanrıver, Kürşat; Ay, MustafaThis paper presents an innovative application of the Ant Colony Optimization (ACO) algorithm to optimize engineering problems, specifically on welded beams and pressure vessels. A simulation study was conducted to evaluate the performance of the new ACO algorithm, comparing it with classical optimization techniques and other heuristic algorithms previously discussed in the literature. The algorithm was executed 20 times to obtain the most efficient results. The best performance outcome in the welded beam simulation was 1.7288, achieved after 540 iterations using 1000 ants, with a computation time of 6.27 seconds. Similarly, the best performance result in the pressure vessel simulation was 5947.1735, obtained after 735 iterations using 1000 ants and completed in 6.97 seconds. Compared to similar results reported in the literature, the new ACO algorithm demonstrated superior performance, offering an outstanding solution. Additionally, users can utilize this new ACO algorithm to quickly acquire information about welded beam design and prefabrication through simulation.Yayın Comparison of different machining strategies and their effects on CNC vertical machining center(2024) Öztürk, Ömer Faruk; Tanrıver, Kürşat; Ay, MustafaIn today's world, interest in the aviation sector and developments within it continue to grow at an accelerated pace. With this increase, the demand for the production of components for unmanned aerial vehicles, passenger airplanes, or jet aircraft has risen correspondingly. However, due to the complex structure of aviation parts, the strategy employed during their processing is of significant importance. The distortion issue encountered in the machining of aviation parts, particularly in thin-walled components, leads to unwanted dimensional changes and significantly complicates the production of these parts. This study aims to investigate the effects of different machining techniques on the widely used Al 7075 T7351 aluminum alloy in the aviation sector and to contribute the experimental results to both readers and the literature. In the experiments, samples of Al 7075 T7351 aluminum alloy with thicknesses of 1.00 mm, 1.20 mm, and 1.50 mm were processed using various machining strategies. According to the experimental results, the effect of tool strategy on thickness was observed to vary between a minimum of 0.67% and a maximum of 7.78%. Taking the average of the minimum and maximum values of the three samples, the average effect of the tool path strategy on surface roughness was found to be 55.46%, and its effect on parallelism varied between 37.50% and 112.50%. Furthermore, it is believed that the methods presented in this study will contribute to solving similar problems in other industries, in addition to the aviation sector, in areas such as material selection, determination of processing parameters, and compliance of three-dimensional coordinate measurements (CMM) with standards.Yayın Efficient path planning for drilling processes: The hybrid approach of a genetic algorithm and ant colony optimisation(University of Zagreb, 2024) Tanrıver, Kürşat; Ay, MustafaEfficiency in machining time during drilling is affected by various factors, with one key element being the machining path. Solving the machining path closely resembles the Travelling Salesman Problem (TSP). In this article, drilling on a sample model is simulated using a hybrid algorithm that is developed based on TSP. This hybrid algorithm (GACO) is created by combining the strengths of the Genetic Algorithm (GA) and Ant Colony Optimisation (ACO). Codes written to verify the stability of the algorithms were executed 10 times, and results were recorded indicating the shortest path and machining sequence. Accordingly, the performance of the hybrid GACO algorithm was observed to be 3.16% better than the ACO algorithm in terms of both total path length and total machining time. In terms of computation time, the ACO algorithm lagged behind the GACO algorithm by 6.46%. Furthermore, the hybrid GACO algorithm demonstrated enhanced performance in both total path length and total machining time when compared with the literature. This study aims to contribute to the industry, professionals, and practitioners in this field by providing cost and time savings.Yayın Modifying the refuse chute design to prevent infection spread: Engineering analysis and optimization(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Tanrıver, Kürşat; Ay, MustafaConsidering the presence of airborne viruses, there is a need for renovation in refuse chutes, regarded as the first step in recycling household waste in buildings. This study aimed to revise the design of existing refuse chutes in light of the challenging experiences in waste management and public health during the coronavirus pandemic. This research primarily focused on the risks posed by various types of coronaviruses, such as the novel coronavirus (COVID-19) and acute respiratory syndrome (SARS and SARS-CoV), on stainless steel surfaces, with evidence of their survival under certain conditions. Refuse chutes are manufactured from stainless steel to resist the corrosive effects of waste. In examining the existing studies, it was observed that Casanova et al. and Chowdhury et al. found that the survival time of coronaviruses on stainless steel surfaces decreases as the temperature increases. Based on these studies, mechanical revisions have been made to the sanitation system of the refuse chute, thus increasing the washing water temperature. Additionally, through mechanical improvements, an automatic solution spray entry is provided before the intake doors are opened. Furthermore, to understand airflow and clarify flow parameters related to airborne infection transmission on residential floors in buildings equipped with refuse chutes, a computational fluid dynamics (CFD) analysis was conducted using a sample three-story refuse chute system. Based on the simulation results, a fan motor was integrated into the system to prevent pathogens from affecting users on other floors through airflow. Thus, airborne pathogens were periodically expelled into the atmosphere via a fan shortly before the intake doors were opened, supported by a PLC unit. Additionally, the intake doors were electronically interlocked, ensuring that all other intake doors remained locked while any single door was in use, thereby ensuring user safety. In a sample refuse chute, numerical calculations were performed to evaluate parameters such as the static suitability of the chute body thickness, static compliance of the chute support dimensions, chute diameter, chute thickness, fan airflow rate, ventilation duct diameter, minimum rock wool thickness for human contact safety, and the required number of spare containers. Additionally, a MATLAB code was developed to facilitate these numerical calculations, with values optimized using the Fmincon function. This allowed for the easy calculation of outputs for the new refuse chute systems and enabled the conversion of existing systems, evaluating compatibility with the new design for cost-effective upgrades. This refuse chute design aims to serve as a resource for readers in case of infection risks and contribute to the literature. The new refuse chute design supports the global circular economy (CE) model by enabling waste disinfection under pandemic conditions and ensuring cleaner source separation and collection for recycling. Due to its adaptability to different pandemic conditions including pathogens beyond coronavirus and potential new virus strains, the designed system is intended to contribute to the global health framework. In addition to the health measures described, this study calls for future research on how evolving global health conditions might impact refuse chute design.
