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    A case study on the effect of meteorological events on the efficiency of flight training organization
    (Emerald Group Holdings, 2022) Tatli, Ali; Bocu, Erdogan; Filik, Tansu; Karakoc, Tahir Hikmet
    Purpose – The purpose of this study is to determine the meteorological events that affect flight training to make the training flight more efficient in a flight training organization (FTO) and to examine the effects of these events on FTO. Design/methodology/approach – Within the scope of this study, the flight training given at Eskisehir Technical University Pilotage Department (ESTU-P) is discussed, and the effect of meteorological events on flight training in this FTO is evaluated. Findings – When the two-year (2019–2020) flight training process of ESTU-P is examined, 45% of the flights planned for 2019, 25% of the flights planned for 2020 and 33% of the total flights in the two-year period could not be realized due to meteorological events. It is determined that this result naturally affects the efficiency of the FTO negatively. Meteorological events such as high temperature, fog and snow are among the main meteorological events that cause flight training to be interrupted. Originality/value – This study will create a framework for FTOs that have been or will be established.
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    Image processing methods decision mechanism for surveillance applications with UAVs
    (Emerald Group Holdings, 2022) Ayar, Murat; Dalkiran, Alper; Kale, Utku; Nagy, András; Karakoc, Tahir Hikmet
    Purpose – The use of unmanned aerial vehicles (UAVs) has significantly increased in the past decade and nowadays is being used for various purposes such as image processing, cargo transport, archaeology, agriculture, manufacturing, health care, surveillance and inspections. For this reason, using the appropriate image processing method for the intended use of UAVs increases the study’s success. This study aims to determine the most suitable one among the innovative methods that constitute the image processing system for a UAV to be used for surveillance purposes. Design/methodology/approach – Analytical hierarchy process has been used in the solution of the decision problem to be handled in three stages, namely, platform, architecture and method. The most suitable alternative and the effect weights of these criteria results were determined at each stage. Findings – As a result of this study, Jetson TX2 was determined as the most suitable embedded platform, ResNet is the optimum architecture and Faster R-convolutional neural networks was the best method in the image processing layer for a system that will provide surveillance with image processing method using UAV. Practical implications – In UAV designs, where multiple hardware and software choices and system combinations exist, multi-criteria decisionmaking (MCDM) approaches can be used as a system decision mechanism. Originality/value – The novelty of this work comes from the application of MCDM methods that are used as a multi-layered decision mechanism in UAV design.
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    Nanofluid-based cooling of prismatic lithium-ion battery packs: an integrated numerical and statistical approach
    (Springer, 2023) Morali, Ugur; Yetik, Ozge; Karakoc, Tahir Hikmet
    Recently, the need for thermal management of lithium-ion batteries in electrical transportation engineering has received increased attention. To get maximum performance from lithium-ion batteries, battery thermal management systems are required. This paper quantitatively presents the efects of several factors on both maximum battery temperature and tem perature gradient. These factors include ambient temperature (288 K, 293 K, 298 K, 303 K, 308 K), C-rate (1C, 2C, 3C, 4C, 5C), mixing ratio (1%, 2%, 3%, 4%, 5%), and inlet velocity (0.01 m s ?1, 0.02 m s ?1, 0.03 m s ?1, 0.04 m s ?1, 0.05 m s ?1). Five levels for each parameter were considered to develop the orthogonal array. The signifcance of the variables was orderly shown through the L25 experiment. Results indicated that for maximal battery temperature, C-rate and ambient temperature are the most signifcant factors while for temperature gradient, C-rate and inlet velocity play an important role. For maxi mum battery temperature ambient temperature, C-rate, mixing ratio, and inlet velocity of 288 K, 1C, 4%, and 0.05 m s ?1, respectively, were obtained at the optimal setting. An ambient temperature of 308 K, a C-rate of 1, a mixing ratio of 5%, and an inlet velocity of 0.05 m s ?1 was the optimal setting for the temperature gradient. The results showed that the confrmatory test validates the optimization process for maximum battery temperature and temperature gradient. This study may provide a pathway for manufacturers and researchers interested in minimizing battery temperature and improving temperature gradient in electric vehicle applications.
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    A numerical study of thermal management of lithium-ion battery with nanofluid
    (Elsevier, 2023) Yetik, Ozge; Morali, Ugur; Karakoc, Tahir Hikmet
    In this study, the NTGK model was used to evaluate the thermal and electrical analyzes of the battery model and Taguchi design was implemented to investigate the main effects of four control factors in the battery thermal management process, those are inlet velocity, mixing ratio, ambient temperature, and C-rate. The Taguchi’s L16 array was fabricated using varying control factors to obtain detailed battery temperature behaviors. As the discharge rate increased, the temperature value of the model increased, while the temperature value of the model decreased as the mixing ratio of the nanoparticle increased. As the inlet velocity of the refrigerant increases, the temperature value taken by the model decreases, while the higher the ambient temperature, the less the increase in the maximum temperature reached by the model. Also results showed that the most influential factor on both maximum battery temperature and temperature uniformity responses was the C-rate, while the least effective factor was the mixing ratio. It was found that an inlet velocity of 0.04 m/s, a mixing ratio of 5, a C-rate of 2, and an ambient temperature of 283 K will yield the lowest maximum battery temperature. The maximum battery temperature was 294 K under these conditions. On the other hand, to maximize the temperature uniformity, 0.04 m/s inlet velocity, 3 mixing ratio, 2 C-rate, and 313 K ambient temperature need to be set as processing parameters. The results showed that the C-rate has to be closely controlled during the discharge process and the influence of the mixing ratio is negligible. This study can be used as a robust guideline in the design of battery thermal management systems using nanofluids.
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    A study on lithium-ion battery thermal management system with Al2O3 nanofluids
    (John Wiley and Sons Ltd, 2022) Yetik, Ozge; Karakoc, Tahir Hikmet
    In this study, a comparison is made with regard to cooling of 15 prismatic batteries connected in series with air, alumina nanofluid. The concentration of the nanofluid was taken as 3% and 5%, the ambient temperature was taken 295 and 300 K, the inlet velocity of the refrigerant was taken 0.01, 0.02, 0.04 m/s, and the discharge rate was taken 1 to 5 C. When the discharge rate is less than or equal to 3, the battery module remained at a safe operating temperature. As the discharge rate increased, problems began to be encountered.
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    Thermal and electrical analysis of batteries in electric aircraft using nanofluids
    (Elsevier Ltd, 2022) Yetik, Ozge; Karakoc, Tahir Hikmet
    Batteries are the primary power supply for hybrid electric aircraft. The most important parameter affecting the performance, life, safety and cost of the batteries is the operating temperature. Therefore, thermal management of batteries is extremely important. The battery module (10 S, 3 P) consists of thirty prismatic lithium-ion batteries. The cooling of the battery is provided by nanofluid, which is a combination of nanoparticles and refrigerants in different mixing ratios (H2O + 3% Fe2O3, H2O + 4% Fe2O3, H2O + 6% Fe2O3), engine oil (EO + 3% Fe2O3, EO + 4% Fe2O3, EO + 6% Fe2O3). The temperatures of each of the batteries in the module are examined separately. The thermal and electrical studies of the battery model are also investigated with the volumetric ratio of the nanofluid, different input speeds and different discharge rates of the battery model. The busbar, which should not be ignored in the thermal management of the batteries, that is, the materials connecting the batteries to each other are included in the model. Air cooling, which is the traditional cooling method of the battery model, cannot bring the battery to the desired temperature range. For this reason, nanofluid cooling should be preferred. Considering the sensitivity to the volume fraction ratio, EO reacted more quickly than water. When the volume fraction ratio was increased from 3% to 6%, when the refrigerant was water, the temperature of the battery model changed by 0.05 K, and when the refrigerant was EO, there was a change of 1.15 K. Looking at all the results, they gave better results than the nanofluid EO added to the water. Considering the effect of the inlet velocity of the refrigerant on the maximum and minimum temperatures, there was a 1 K change at the maximum temperature, and a 0.2 K change at the minimum temperature (H20 + 6% Fe2O3).