Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
Browse
31 results
Search Results
Article Citation - WoS: 1Citation - Scopus: 1Exergy-Based Evaluation of High-CO2 Biogas/Diesel RCCI Combustion Heat Flow for Enhanced Mixture Distribution, Power Output, and Fuel-Energy Performance(Pergamon-Elsevier Science Ltd, 2026) Dalha, Ibrahim B.; El-Adawy, Mohammed; Wong, Nur Leena W. S.; Man, Hafsalina C.; Said, Mior A.; Koca, Kemal; Abdulsalam, MuhammedUtilising high-CO2 biogas in compression-ignition engines poses significant challenges due to poor mixture reactivity, inefficient combustion, and increased energy degradation. This work addresses these difficulties by conducting experimental research on a port-injection at the valve reactivity-controlled compression ignition (PIVE-RCCI) strategy. This study addresses these concerns by conducting experiments on a PIVE-RCCI technique to improve mixture distribution and combustion efficiency in biogas-diesel engines. The engine was modified to provide biogas through the inlet valve, allowing for controlled variations of biogas injection pressure (BIP: 1-4 bar) and port swirl ratio (PSR: 0-80%) at 1600 rpm and 4.9-5.7 bar IMEP. Energy and exergy analyses were used to determine the effect of intake flow dynamics on temperature uniformity, heat transfer, and power generation during combustion. The results reveal that normal airflow conditions minimise accounted heat loss, indicating higher thermal efficiency (ITE) and increased output power across all BIPs. In contrast, introducing a strong intake swirl dramatically improves combustion performance. The 80% PSR configuration resulted in the lowest exergy destruction and the maximum energy recovery potential, with an ITE of 26.54% at 4 bar BIP. Increasing BIP increased power output, whereas the optimal combustion work was found at 1 bar BIP and 40% PSR. The optimal working conditions were 1 bar BIP, 80% PSR, and 5.45 bar IMEP, which resulted in 26.00% exergy destruction, 39.38% destruction-to-released exergy ratio, 86.00% exergy-energy ratio of heat transfer, and 63.78% exhaust exergy-energy ratio. This work's novelty lies in integrating biogas injection, intake swirl control, and exergy-based evaluation to measure mixture distribution and energy recovery in high-COQ biogas RCCI combustion. The findings offer useful operational guidance for increasing energy efficiency and advancing the commercialization of renewable gaseous fuels in RCCI engines. As a result, operating the engine at half load, 80% PSR, and atmospheric air pressure (1 bar) conditions significantly enhanced the combustion efficiency and energy utilisation.Article Citation - WoS: 225Citation - Scopus: 243The Role of Interaction Effect Between Renewable Energy Consumption and Real Income in Carbon Emissions: Evidence From Low-Income Countries(Pergamon-Elsevier Science Ltd, 2022-02) Ehigiamusoe, Kizito Uyi; Dogan, EyupEven though the existing studies have extensively investigated the impacts of renewable energy and real income on carbon emissions, the literature overlooks the role of their interaction effect in the level of emissions. In addition, the studies have usually chosen high-income and middle-income countries as focused group. To fill these gaps in the existing body of energy-environment literature, this study investigates the impacts of real income, renewable energy consumption and their interaction effect on carbon emissions in low-income countries by employing empirical estimations that control different econometric and economic issues such as heterogeneity and cross-sectional dependence. The results reveal that renewable energy mitigates emissions; however, the interaction effect stays positive. The marginal effect of renewable energy on emissions varies with the levels of real income. Policymakers in these economies should implement policies and regulations to promote the adoption and use of renewable energy to mitigate carbon emissions. Besides, this study emphasizes that the levels of renewable energy and real income are not the only panacea to abating pollution, but the interaction effect should be considered in ensuring environmental sustainability.Article Citation - WoS: 8Citation - Scopus: 9The Effect of Spoilers on Flow Around Tandem Circular Cylinders(Pergamon-Elsevier Science Ltd, 2023-03) Ilkentapar, Mucella; Aksit, Serhat; Acikel, Halil Hakan; Oner, Ahmet AlperExamining the flow characteristics around the cylindrical elements, such as offshore (submarine) pipelines which can be used in single or multiple arrangements, has a prominent place in fluid mechanics. The use of spoilers for self-embedding of these structures has been a subject that researchers have studied for many years. In this study, (a) the flow around a cylinder without and with a spoiler and (b) the effect of adding spoiler(s) to the tandem cylinders on the flow was experimentally investigated. In these experiments, where the ratio of the distance between the cylinders to the cylinder diameter is 2, the Reynolds number is 14000, which remains in the subcritical region. Four experiments were performed: the smoke-wire method was used for flow visualization, aerodynamic force measurement, velocity measurement by hot-wire anemometer, and pressure measurement to determine the pressure distribution on the cylinders. Pressure, velocity, and force results were recorded with the time histories in this study for the first time. Experimental studies show that when a spoiler is added to a single cylinder, an opposing lift force acts on that and the drag force increases due to the enlargement of the lowpressure region at the wake of the cylinder. In a tandem situation, when the upstream cylinder has a spoiler, no drag force acts on the downstream cylinder. The forces exerted on the upstream cylinder are not affected by whether the downstream cylinder has a spoiler. In the case of the downstream cylinder with the spoiler, the fluctuations in the aerodynamic forces of the upstream cylinder decrease owing to the downstream cylinder with the spoiler. The force fluctuations are more in the downstream cylinder, and unlike other tandem and singlecylinder cases, the vortex shedding becomes complex.Article Citation - WoS: 77Citation - Scopus: 89Revisiting the Nexus of Ecological Footprint, Unemployment, and Renewable and Non-Renewable Energy for South Asian Economies: Evidence From Novel Research Methods(Pergamon-Elsevier Science Ltd, 2022-07) Dogan, Eyup; Majeed, Muhammad Tariq; Luni, TaniaGiven the need to employ novel research methods in the energy-environment nexus, the objective of the present research is to investigate the impacts of real output, unemployment, and renewable and nonrenewable energy on ecological footprint under a STIRPAT theoretical framework by applying the second-generation unit root, cointegration, Granger-causality, and long-run estimation methods on the annual data from 1990 to 2017 for South Asian economies. Empirical results show that increases in unemployment and renewable energy decrease ecological footprint while increases in real income and non-renewable energy hurt the environment. This study confirms the adverse effect of renewable energy on environmental degradation as well as the trade-off between unemployment and pollution through multiple robustness and sensitivity checks. In addition, the causality test supports unidirectional causality from income, renewable energy, and non-renewable energy to ecological footprint. Regarding policy perspectives, the governments of the South Asian region should support the deployment of renewable energy through various channels and regulations. The development of technologies that promote sustainable production and consumption play critical roles for reducing the trade-off unemployment and ecological footprint. Further policy suggestions are discussed in the study.(c) 2022 Elsevier Ltd. All rights reserved.Article Citation - WoS: 47Citation - Scopus: 61Real-Time Energy Management in an Off-Grid Smart Home: Flexible Demand Side Control With Electric Vehicle and Green Hydrogen Production(Pergamon-Elsevier Science Ltd, 2023-07) Boynuegri, Ali Rifat; Tekgun, Burak; Rifat Boynuegri, AliA real-time energy management system for an off-grid smart home is presented in this paper. The primary energy sources for the system are wind turbine and photovoltaics, with a fuel cell serving as a supporting energy source. Surplus power is used to generate hydrogen through an electrolyzer. Data on renewable energy and load demand is gathered from a real smart home located in the Yildiz Technical University Smart Home Laboratory. The aim of the study is to reduce hydrogen consumption and effectively utilize surplus renewable energy by managing controllable loads with fuzzy logic controller, all while maintaining the user's comfort level. Load shifting and tuning are used to increase the demand supplied by renewable energy sources by 10.8% and 13.65% from wind turbines and photovoltaics, respectively. As a result, annual hydrogen consumption is reduced by 7.03%, and the average annual efficiency of the fuel cell increases by 4.6% & COPY; 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.Article Citation - WoS: 3Citation - Scopus: 3NeRNA: A Negative Data Generation Framework for Machine Learning Applications of Noncoding RNAs(Pergamon-Elsevier Science Ltd, 2023-06) Orhan, Mehmet Emin; Demirci, Yilmaz Mehmet; Demirci, Mueserref Duygu Sacar; Saçar Demirci, Müşerref DuyguMany supervised machine learning based noncoding RNA (ncRNA) analysis methods have been developed to classify and identify novel sequences. During such analysis, the positive learning datasets usually consist of known examples of ncRNAs and some of them might even have weak or strong experimental validation. On the contrary, there are neither databases listing the confirmed negative sequences for a specific ncRNA class nor standardized methodologies developed to generate high quality negative examples. To overcome this challenge, a novel negative data generation method, NeRNA (negative RNA), is developed in this work. NeRNA uses known examples of given ncRNA sequences and their calculated structures for octal representation to create negative sequences in a manner similar to frameshift mutations but without deletion or insertion. NeRNA is tested individually with four different ncRNA datasets including MicroRNA (miRNA), transfer RNA (tRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA). Furthermore, a species-specific case analysis is per-formed to demonstrate and compare the performance of NeRNA for miRNA prediction. The results of 1000 fold cross-validation on Decision Tree, Naive Bayes and Random Forest classifiers, and deep learning algorithms such as Multilayer Perceptron, Convolutional Neural Network, and Simple feedforward Neural Networks indicate that models obtained by using NeRNA generated datasets, achieves substantially high prediction performance. NeRNA is released as an easy-to-use, updatable and modifiable KNIME workflow that can be downloaded with example datasets and required extensions. In particular, NeRNA is designed to be a powerful tool for RNA sequence data analysis.Article Citation - WoS: 17Citation - Scopus: 19Investigation of the Performance and Properties of ZnO/GO Double-Layer Supercapacitor(Pergamon-Elsevier Science Ltd, 2024-08) Buyukkurkcu, Handan; Durmus, Ali; Colak, Hakan; Kurban, Rifat; Sahmetlioglu, Ertugrul; Karakose, ErcanComposite electrode material was formed by mixing reduced graphene oxide (rGO) and zinc oxide (ZnO) compound, using the Hummers and green synthesis methods, respectively. Of rGO powder, 10 g was mixed with 10%, 20% and 30% ZnO, and composite electrodes were obtained by using 10% binder. The energy storage performance and structural characteristics of the supercapacitor were evaluated by analyzing the capacitance values of the synthesized electrodes. The structural characterization of ZnO/rGO composites was performed using X-ray diffraction and field-emission scanning electron microscopy. The electrochemical properties of the ZnO/GO electrodes were analyzed by cyclic voltammetry, electrochemical impedance and galvanostatic charge -discharge tests. The specific capacitance value of electrodes increased as zinc content increased in the ZnO/ rGO composite material used to produce electrodes. The maximum specific capacitance values were measured at 5 mV/s scanning rate as 194.23 (rGO), 366.81 (10% ZnO), 383.18 (20% ZnO) and 410.48 F/g (30% ZnO). In conclusion, the use of composite material formed by the combination of ZnO nanoparticles obtained by green synthesis method from orange peel and graphene oxide increased the electrochemical efficiency of the supercapacitor.Article Citation - WoS: 20Citation - Scopus: 22Investigation of the Effect of Hidden Vortex Generator-Flap Integrated Mechanism Revealed in Low Velocities on Wind Turbine Blade Flow(Pergamon-Elsevier Science Ltd, 2023-07) Ozden, Mustafa; Genc, Mustafa Serdar; Koca, KemalIn this study, the flap and vortex generator (VG) mechanisms which were employed separately in aircraft were used as integrated first in literature. In this mechanism, the flap motion triggered and activated the VGs when it was needed at low speeds. Thus, this flap mechanism eliminated the unnecessary drag force generation when VGs were not needed. Numerical simulations which were validated with experimental data were employed in the study. In the first step, the flow characteristics formed on the S809 airfoil with 4 different flap angles ( beta = 30 degrees, 20 degrees, 10 degrees, 0 degrees) were investigated without the VG. Then, those flow structures formed on the S809 airfoil with both flap and VG were examined under the same conditions. According to the results, utilizing flap and VGs together had a positive impact at low wind speeds. Moreover, due to the flap and vortex generator integrated mechanism closed up to be not unnecessary drag formation at high wind speeds, thus those structures increased further to the positive effect with the increasing wind velocity. In terms of energy output, it was shown that this novel idea provided more energy output in this study.Article Citation - WoS: 150Citation - Scopus: 163Investigating the Spillovers and Connectedness Between Green Finance and Renewable Energy Sources(Pergamon-Elsevier Science Ltd, 2022-09) Dogan, Eyup; Madaleno, Mara; Taskin, Dilvin; Tzeremes, PanayiotisAlthough a few studies have analyzed the nexus of renewable energy and green finance, the literature lacks the use of renewable energy by sources. The other major failure is that it uses only annual and small data. Therefore, this study investigates the connectedness and spillovers relationship between green finance and five types of renewable energy (biofuels, fuel cell, geothermal, solar, and wind) by applying the novel TVP-VAR method of Balcilar et al. [1] to the daily indexes from July 31, 2014, to Feb 4, 2022. The results show that dynamic connectedness, both total and pairwise, is heterogeneous over time and influenced by economic events. Furthermore, wind is found to be the largest transmitter of shocks to green finance, followed by biofuels, while both fuel cell and geothermal receive the least shocks. The findings suggest that green finance is mostly a net receiver of shocks from renewable energy sources and that wind has been a net receiver of shocks during the COVID-19 pandemic. A high interconnectedness between the indexes highlights the safe-haven property for diversification purposes of green finance. Our results are important for energy policymakers, those responsible for the implementation of environmental policies, individual investors, and portfolio managers, while also shedding light on the achievement of COP26 goals.Article Citation - WoS: 11Citation - Scopus: 13Investigating the Best Automatic Programming Method in Predicting the Aerodynamic Characteristics of Wind Turbine Blade(Pergamon-Elsevier Science Ltd, 2023-08) Arslan, Sibel; Koca, KemalAutomatic programming (AP) is a subfield of artificial intelligence (AI) that can automatically generate computer programs and solve complex engineering problems. This paper presents the accuracy of four different AP methods in predicting the aerodynamic coefficients and power efficiency of the AH 93-W-145 wind turbine blade at different Reynolds numbers and angles of attack. For the first time in the literature, Genetic Programming (GP) and Artificial Bee Colony Programming (ABCP) methods are used for such predictions. In addition, Airfoil Tools and JavaFoil are utilized for airfoil selection and dataset generation. The Reynolds number and angle of attack of the wind turbine airfoil are input parameters, while the coefficients CL, CD and power efficiency are output parameters. The results show that while all four methods tested in the study accurately predict the aerodynamic coefficients, Multi Gene GP (MGGP) method achieves the highest accuracy for R2Train and R2Test (R2 values in CD Train: 0.997-Test: 0.994, in CL Train: 0.991-Test: 0.990, in PE Train: 0.990-Test: 0.970). By providing the most precise model for properly predicting the aerodynamic performance of higher cambered wind turbine airfoils, this innovative and comprehensive study will close a research gap. This will make a significant contribution to the field of AI and aerodynamics research without experimental cost, labor, and additional time.