• Energy Research
• 2021-2025close
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• Yıldız Technical University close

Çalışmada, mevcut durumda elektrik anahtarlarında kullanılan bakır ve pirinç hammaddelere göre daha uygun maliyetli bir alternatif olacağı düşünülen Al-Cu bimetalik hammaddesinin elektrik anahtarlarında kullanımının IEC standartları açısından uygunluğu araştırılmıştır. IEC 60669-1 elektrik anahtarları standardının en belirleyici testi olan aşırı akım testinde, iletkenlerin artan ısınma miktarları incelenmektedir. Anahtarın iletkenlerinden ürünün beyan akımının (In:10A) 1,35 katı aşırı akım geçirilerek iletkenlerdeki maksimum sıcaklık artış miktarının (ΔT) 45°C altında olması istenmektedir. Araştırmada, üç farklı hammadde (Al-Cu, pirinç ve bakır) ile oluşturulmuş ürün dataları, standartta belirtilen sınır şartları dahilinde multi-fizik simülasyonlara tabi tutulmuş ve laboratuvar testleri yapılmadan önce sıcaklık artışı ile alakalı teorik sonuçlara ulaşılmıştır. Simülasyona göre en yüksek sıcaklık artışı 20,5°C ile pirinç, en düşük sıcaklık artışı 17,25°C ile bakır numunede gözlemlenmiştir. Al-Cu numunede ise 19,9°C sıcaklık artışı gözlemlenmiştir. Simülasyonlardan sonra yapılan laboratuvar testlerinde simülasyon verilerine yakın sonuçlar alınmıştır. Test sonuçlarına göre en yüksek sıcaklık artışı meydana gelen pirinç numunede 22,63°C, en düşük sıcaklık artışı meydana gelen bakır numunede 19,14°C ve Al-Cu numunede ise 20,72°C sıcaklık artışı gözlemlenmiştir. Sırasıyla pirinç, Al-Cu ve bakır için analiz-deneysel veri sapma miktarları şu şekildedir; %10,37, %4,10 ve %10,95. Bu verilere göre hiçbir numune maksimum 45°C miktarını aşmamıştır ve numunelerin tamamı standart açısından uygundur. Direncin ısınma ile doğru, iletkenlik ile ters orantılı olduğu bilinmektedir. Bu bilgiler ve test sonuçlarından yola çıkılarak hammaddelerin iletkenlik miktarları için bakır>Al-Cu>pirinç sıralaması yapılabilir. Simülasyon ve deneysel doğrulama sonuç verileri incelendiğinde Al-Cu bimetal hammaddesinin, uluslararası elektrik anahtarları standardındaki aşırı akım testlerini geçerek elektrik anahtarlarında pirinç ve bakır iletkenlere alternatif olarak kullanılabileceği sonucuna ulaşılmıştır.

This study tests binary and ternary n-pentanol, ethanol, and petrol blends to increase spark-ignition (SI) engine performance and minimize CO and HC emissions. To improve brake thermal efficiency (BTE) and reduce emissions, adding ethanol into gasoline is one of the practices used in Automobiles. But the literature reported some performance limitations and problems with adding a high ethanol concentration to gasoline as phase separation problem occurs in fuel tank due to the hygroscopic nature of ethanol, a higher ethanol concentration may corrode some parts of the fuel supply system. Ethanol has a lower calorific value than gasoline, so a higher ethanol concentration in blends beyond a specific limit reduces BTE. N-pentanol as a fuel additive in gasoline can better solve these problems due to its high caloric value compared to ethanol. Also, when n-pentanol is mixed with gasoline and exposed to moisture, it does not separate in stages as in the ethanol case. Accordingly, this research aims to evaluate n-pentanol's viability as a fuel additive in petrol and ethanol-gasoline blends at different compression ratios. The experiments were carried out on a single-cylinder, four-stroke spark-ignition engine running at a constant speed. Different blends of n-pentanol with gasoline and ethanol were tested, and results were compared against gasoline and E10 (the optimal blend of ethanol-gasoline, 10/90 v/v %). Various parameters were examined, including BTE, brake-specific fuel consumption (BSFC), and different exhaust pollutants. The effects of compression ratio values on these parameters were also recorded. The 1.5 vol% pentanol with E10 (E10P1.5) mix has the best overall characteristics, including low BSFC, high BTE, and low CO and HC emissions compared to petrol and E10 fuels. E10P1.5 shows a maximum enhancement in BTE, low BSFC, CO reduction, and HC reduction by 23.79%, 19.80%, 37.79%, and 19.46%, respectively, over gasoline. Compared to E10, the improvement is 3.64% for BTE, 4.59% for BSFC, 8.88% for CO emission reduction, and 4.13% for HC emission reduction.

In this study, an Internet of Things (IoT) communication network is considered, where mobile users in a dense urban environment communicate via a stationary Unmanned Aerial Vehicle (UAV) that acts as a base station. It is thought that the users in the network are designed with a single antenna and the UAV with a double antenna. Users estimate the channel gain parameters according to the pilot symbols they receive from the UAV and send their symbols to the UAV by encoding them with the Space-Time Line Coding (STLC) technique according to these channel gain parameters. In the UAV, on the other hand, symbols are retrieved intensively without the need for channel gain information that may come from users. Monte Carlo simulations were created under various assumptions and the error performance of a fixed user on the network was examined. It is assumed that the envelopes of the communication channels in the system follow the Ricean fading channel in small-scale fading.

The efforts to reduce CO2 emissions from road transport have focused mainly on passenger cars, but the attention shifts to heavy-duty vehicles, which contribute significantly to the sector's greenhouse gas emissions despite their low fleet share. The current study focused on a bus and investigated the effect of environmental conditions and passenger occupancy on auxiliary usage and CO2 emissions. It utilised measurements conducted over the Zincirlikuyu – Avcilar route in Istanbul, Turkey, to develop vehicle simulation models. The vehicle was simulated under different environmental conditions and passenger occupancy, and it was found that the auxiliary use could differ between −1.05 and 2.67 kW compared to the European reference conditions. Simulations with variable passenger capacity showed no difference with runs that utilised a standard average passenger capacity value. In addition, a factorial analysis was performed to cover a broader range of environmental conditions. The findings were used to develop a methodology to calculate vehicle-specific CO2 emissions under different on-road conditions by utilising the vehicle's reference emissions. The study results are expected to contribute to the field as HVAC energy demands could increase on-road CO2 emissions and limit the range of electrified powertrains.

In this paper, we propose a sophisticated battery model for vanadium redox flow batteries (VRFBs), which are a promising energy storage technology due to their design flexibility, low manufacturing costs on a large scale, indefinite lifetime, and recyclable electrolytes. Primarily, fluid distribution is analysed using computational fluid dynamics (CFD) considering only half-cells. Based on the analysis results, a novel model is developed in the MATLAB Simulink environment which is capable of identifying both the steady-state and dynamic characteristics of VRFBs. Unlike the majority of published studies, the inherent characteristics of the flow battery, such as shunt current, ion diffusion, and pumping energy consumption, are considered. Furthermore, simplified charge transfer resistance (CTR) is taken into account based on electrochemical impedance spectroscopy (EIS) measurement results. The accuracy of the model was determined by comparing the simulation results generated by the equivalent circuit battery model developed in this study with real datasets. The obtained results indicate that the developed model has an accuracy of 3% under the sample operating conditions selected. This study can also be used to fill the gap left by the absence of the VRFB battery model in commonly used programs for renewable energy systems, such as TRNSYS.

This study analyzes comprehensively the role of green technology, environmental taxes, and green energy toward a sustainable environment in 5 sovereign Nordic countries by also considering income and population. For this purpose, annual data of Nordic countries from 1995 to 2020 is extracted and the cross-sectional augmented autoregressive distributed lag (CS-ARDL) technique is applied to test short-run and long-run compatibilities of the indicators on carbon dioxide (CO2) emissions. Moreover, Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) approaches are applied for robustness checks. The empirical results reveal that (i) green technology, environmental taxes, and green energy have a negative association with CO2 emissions in the both short-run and long-run; (ii) income and population have a positive association between CO2 emissions in the both short-run and long-run; (iii) AMG and CCEMG approaches report similar findings with the CS-ARDL and validate the robustness in turn. Thus, the empirical results confirm the contributing role of green technology, environmental taxes, and green energy toward a sustainable environment in 5 sovereign Nordic countries. Moreover, policy implications are discussed. © 2023 International Association for Gondwana Research

The current study highlights the potential of hybrid renewable energy systems in mitigating CO2 emissions for a near-zero energy building. A Python-based controller is used to manage the state of charge (SoC) of the lithium-ion battery. Two buildings are considered in the study. Once the SoC in the first building reaches 75 %, the system prevents overcharging and redirects the green electricity towards the hybrid system for hydrogen production. To compare the role of a hybrid system in which a fuel cell is used to supply the required energy for electric load and electrolyzer demand, a diesel generator is considered for the same energy demands. The hybrid system achieves a 56.14 % reduction in diesel fuel consumption, leading to an annual decrease of 33.860 tons of CO2 emissions. Economic analysis reveals that while the cost of the diesel mode is calculated to be 96 % higher than the hybrid mode, the CO2 emissions in the hybrid mode will be 56.14 % lower than the full diesel mode. Additionally, the system's total annual hydrogen production is 7582.74 kg, with a maximum production rate of 15.52 m³/hr at 1.3 bar pressure. Despite higher initial costs, hybrid systems effectively address the challenge of CO2 emissions compared to conventional systems. The results underscore the necessity of hybrid systems for achieving significant reductions in fossil fuel consumption, presenting a sustainable solution for future energy needs.

The transportation of oil and gas through pipelines is an integral aspect of the global energy infrastructure. It is crucial to ensure the safety and integrity of these pipelines, and one way to do so is by utilizing an inspection tool called a smart pig. This paper reviews various smart pigs used in steel oil and gas pipelines and classifies them according to pipeline structure, anomaly-detection capability, working principles, and application areas. The advantages and limitations of each sensor technology that can be used with the smart pig for in-line inspection (ILI) are discussed. In this context, ultrasonic testing (UT), electromagnetic acoustic transducer (EMAT), eddy current (EC), magnetic flux leakage (MFL), and mechanical contact (MC) sensors are investigated. This paper also provides a comprehensive analysis of the development chronology of these sensors in the literature. Additionally, combinations of relevant sensor technologies are compared for their accuracy in sizing anomaly depth, length, and width. In addition to their importance in maintaining the safety and reliability of pipelines, the use of ILI can also have environmental benefits. This study aims to further our understanding of the relationship between ILI and the environment.