WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Exergy-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: 221Citation - Scopus: 240The 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: 40Citation - Scopus: 43The Role of Hydrogen in the Edge Dislocation Mobility and Grain Boundary-Dislocation Interaction in Α-Fe(Pergamon-Elsevier Science Ltd, 2021-09) Kapci, Mehmet Fazil; Schoen, J. Christian; Bal, Burak; Schön, J. ChristianThe atomistic mechanisms of dislocation mobility depending on the presence of hydrogen were investigated for two edge dislocation systems that are active in the plasticity of alpha-Fe, specifically 1/2<111>{110} and 1/2<111>{112}. In particular, the glide of the dislocation pile-ups through a single crystal, as well as transmission of the pile-ups across the grain boundary were evaluated in bcc iron crystals that contain hydrogen concentrations in different amounts. Additionally, the uniaxial tensile response under a constant strain rate was analyzed for the aforementioned structures. The results reveal that the presence of hydrogen decreases the velocity of the dislocations -in contrast to the commonly invoked HELP (Hydrogen-enhanced localized plasticity) mechanism-, although some localization was observed near the grain boundary where dislocations were pinned by elastic stress fields. In the presence of pre-exisiting dislocations, hydrogen-induced hardening was observed as a consequence of the restriction of the dislocation mobility under uniaxial tension. Furthermore, it was observed that hydrogen accumulation in the grain boundary suppresses the formation of new grains that leads to a hardening response in the stress-strain behaviour which can initiate brittle fracture points. (C) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.Article Citation - WoS: 7Citation - 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: 30Citation - Scopus: 37Testing of 17-Different Leaching Agents for the Recovery of Zinc From a Carbonate-Type Pb-Zn Ore Flotation Tailing(Pergamon-Elsevier Science Ltd, 2021-07) Hussaini, Shokrullah; Kursunoglu, Sait; Top, Soner; Ichlas, Zela Tanlega; Kaya, MuammerThe recovery of zinc from a flotation tailing using 17-different leaching agents, including inorganic and organic acids, alkaline solutions and chelating agents, was investigated. The effects of the lixiviant type, acid concentration, leaching temperature, leaching time, and solid-to-liquid ratio on the metals dissolution were studied. The use of sulfuric acid resulted in 91% of zinc extraction with a high selectivity against lead. The major impurities of lead, iron, calcium and arsenic precipitated during the leaching process as a segnisite, beudantite, gypsum, and goethite in this lixiviant. It was seen that the addition of oxidants in sulfuric acid solution slightly increased zinc dissolution. The citric acid dissolved 90.1% of zinc along with 9.1% lead. 90% of zinc dissolution was achieved by using malic acid, and high selectivity between zinc and lead dissolutions was also observed. The citric and malic acid leach residues contained a substantial amount of segnitite, beudantite, and quartz as the major phases. In term of zinc and lead dissolution selectivity, the best inorganic agents were determined in the following order: sulfuric acid > hydrochloric acid > perchloric acid > nitric acid. With organic agents, the best zinc and lead selectivity was achieved in the following order: sulfosalicylic acid > citric acid > malic acid > formic acid > tartaric acid > ascorbic acid. The best simultaneous zinc and lead dissolutions were achieved using sodium hydroxide agent. Using 5 M sodium hydroxide at 80 degrees C and 1/10 solid-to-liquid ratio for 180 min. leaching time, 81.4% of zinc and 47.4% of lead were dissolved while leaving a considerable amount of iron in the residue. When the ammonium chloride was used as a lixiviant, the silver and zinc were taken into the leach solution. 61.3% of zinc dissolution was obtained by using 50% ammonia as lixiviant, whereas no iron and lead dissolutions were observed. Using 0.37 M EDTA at 80 degrees C, 1/10 solid-to-liquid ratio for 180 min. leaching time, more than 90% of zinc dissolved along with a substantial amount of iron, arsenic and lead co-dissolutions. 47.4% of zinc dissolution was obtained at 80 degrees C and 1/10 solid-to-liquid ratio for 180 min. leaching time when sodium citrate was used as lixiviant, whereas less than 20% of zinc dissolved using ammonium oxalate at similar leaching condition. 39% zinc was dissolved using 3 M ammonium acetate at 80 degrees C, 1/10 solid-to-liquid ratio for 180 min., while 23.1% of zinc dissolution was achieved when the ammonium acetate was tested under similar experimental conditions. As a result, sulfuric, citric, malic, sulfosalicylic and formic acids were deemed to be the most promising leaching agents for the selective recovery of zinc from the lead-zinc flotation tailing.Article Citation - WoS: 27Citation - Scopus: 30Super Resolution Convolutional Neural Network Based Pre-Processing for Automatic Polyp Detection in Colonoscopy Images(Pergamon-Elsevier Science Ltd, 2021-03) Tas, Merve; Yilmaz, BulentColonoscopy is the most common methodology used to detect polyps on the colon surface. Increasing the image resolution has the potential to improve the automatic colonoscopy based diagnosis and polyp detection and localization. In this study, we proposed a pre-processing approach that uses convolutional neural network based super resolution method (SRCNN) to increase the resolution of the training colonoscopy images before the localization of polyps. We also investigated the use of CNN based models such as the Single Shot MultiBox Detector (SSD) and Faster Regional CNN (RCNN) for real-time polyp detection and localization. Our results showed that using SRCNN method before the training process provides better results in terms of accuracy in both models compared to the low-resolution cases. Furthermore, we reached an F2 score of 0.945 for the correct localization of colon polyps using Faster RCNN with ResNet-101 feature extractor.Article Citation - WoS: 23Citation - Scopus: 24Strain Rate and Hydrogen Effects on Crack Growth From a Notch in a Fe-High Steel Containing 1.1 Wt% Solute Carbon(Pergamon-Elsevier Science Ltd, 2020-01) Najam, Hina; Koyama, Motomichi; Bal, Burak; Akiyama, Eiji; Tsuzaki, KaneakiEffects of strain rate and hydrogen on crack propagation from a notch were investigated using a Fe-33Mn-1.1C steel by tension tests conducted at a cross head displacement speeds of 10(-2) and 10(-4) mm/s. Decreasing cross head displacement speed reduced the elongation by promoting intergranular crack initiation at the notch tip, whereas the crack propagation path was unaffected by the strain rate. Intergranular cracking in the studied steel was mainly caused by plasticity-driven mechanism of dynamic strain aging (DSA) and plasticity-driven damage along grain boundaries. With the introduction of hydrogen, decrease in yield strength due to cracking at the notch tip before yielding as well as reduction in elongation were observed. Coexistence of several hydrogen embrittlement mechanisms, such as hydrogen enhanced decohesion (HEDE) and hydrogen enhanced localized plasticity (HELP) were observed at and further away from the notch tip resulting in hydrogen assisted intergranular fracture and cracking which was the key reason behind the ductility reduction. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.Article Citation - WoS: 75Citation - 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: 44Citation - Scopus: 58Real-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.