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Öğe A comparison of the performance characteristics of large 2 MW and 3 MW wind turbines on existing onshore wind farms(Techno-Press, 2021) Bilgili, Mehmet; Ekinci, Firat; Demirdelen, TugceThe aim of the current study is to compare the performance of large 2 MW and 3 MW wind turbines operating on existing onshore wind farms using Blade Element Momentum (BEM) theory and Angular Momentum (AM) theory and illustrate the performance characteristic curves of the turbines as a function of wind speed (U-infinity). To achieve this, the measurement data obtained from two different Wind Energy Power Plants (WEPPs) located in the Hatay region of Turkey was used. Two different horizontal-axis wind turbines with capacities of 2 MW and 3 MW were selected for evaluation and comparison. The hub-height wind speed (U-D), turbine power output (P), atmospheric air temperature (T-atm) and turbine rotational speed (Omega) data were used in the evaluation of the turbine performance characteristics. Curves of turbine power output (P), axial flow induction factor (a), turbine rotational speed (omega), turbine power coefficient (C-P), blade tip speed ratio (lambda), thrust force coefficient (C-T) and thrust force (T) as a function of U-infinity were obtained for the 2 MW and 3 MW wind turbines and these characteristic curves were compared. Results revealed that, for the same wind speed conditions, the higher-capacity wind turbine (3 MW) was operating at higher turbine power coefficient rates, while rotating at lower rotational speed ratios than the lower capacity wind turbine (2 MW).Öğe A comprehensive study on dry type transformer design with swarm-based metaheuristic optimization methods for industrial applications(Taylor & Francis Inc, 2018) Aksu, Inayet Ozge; Demirdelen, TugceBy the development of technology, clean, reliable, and continuous energy has increased its importance. Transformers, one of the indispensable parts of this, have a role in the production, transmission, distribution, and consumption of electrical energy. Dry type transformers are more widely applied for industrial application because of its properties such as safety, incombustible structure, and eco-friendly. However, these transformers have some drawbacks related to dimension and cost depending on it. Therefore, the researchers have begun to study for reduction of dimension. Thus, the manufacturers will be supplied lower material cost. The idea of using new optimization methods is emerged to minimize the dimension of dry type transformer design This article presents the Invasive Weed Optimization (IWO) and the Firefly Algorithm (FA) which are newly introduced in the literature applied first time in the industry. First of all, the mathematical model of the three-phase dry-type transformer is described in detail. Secondly, the transformer is re-designed with the FA and the IWO by adjusting the current density (s) and the iron section compatibility factor (C). In addition, these optimization methods are compared with the performance with Particle Swarm Optimization (PSO), one of the most preferred optimization methods in the literature, in detail. The main contribution of this article is to optimize the weight and its related to cost of dry type transformer A 100 kVA three-phase dry-type transformer is used. The obtained results showed that the optimization of the weight and cost of the transformer are efficient. This article aims at providing a broad perspective on the status of optimum design for transformer fo the researchers and the application engineers dealing with these issues.Öğe A Fuzzy Neural Network Approach to Estimate PMSG based and DFIG based Wind Turbines' Power Generation(IEEE, 2017) Demirdelen, Tugce; Bakmaz, Emel; Tumay, MehmetNeural networks and fuzzy systems are amalgamate their advantages and to eliminate its individual disadvantages. Neural networks have its computational characteristics of learning in the fuzzy systems and receive from them the interpretation and clarity of systems representation. Thus, the disadvantages of the fuzzy systems are fulfilled by the capacities of the neural networks. These techniques are complementary, which prove its use together. This is called fuzzy neural networks In this paper, a fuzzy neural network is applied to estimate PMSG based and DFIG based wind turbines' power generation. The obtained results showed that this model can be used to predict wind turbine power generation and performance analysis both two type turbines in a simple, reliable and accurate way.Öğe A Life Cycle Analysis of a Polyester-Wool Blended Fabric and Associated Carbon Emissions in the Textile Industry(Mdpi, 2024) Tekin, Piril; Alici, Hakan; Demirdelen, TugceThe effect of industrialization and technological developments and the rate of population growth have begun to disrupt the ecological balance in the world. A large share of the deterioration of this balance is due to the rapidly increasing energy demands of people. Fossil fuels and renewable energy sources are used to obtain the energy that is needed by human beings. Most of the world ' s energy needs are met by fossil fuels such as coal, oil, and natural gas. These resources, which we call fossil fuels, cause many parallel environmental problems, such as global warming, climate change, and carbon emissions, for the world and nature. The most affected by all these experiences, of course, is the entire production sector, which is dependent on energy. However, textile and apparel, which is a pioneer in taking steps towards harmonization with the Green Agreement, is one of the sectors that started the transition to green energy within the scope of the European Union and brands ' net-zero targets. Within the scope of the Green Agreement, Turkey has participated and started to work for a 70% carbon reduction, which is the target for 2030, and carbon neutrality, which is the target for 2050. Therefore, within the scope of these targets, the textile sector of cukurova Region, which has the highest export rate in Turkey, was chosen. Within the scope of this study, carbon emission, which is one of the global problems, was examined within the framework of the ISO 14067-ISO Product Based Carbon Footprint (CF) standard by examining the production of a textile company, and the results were analyzed in detail. The main innovation of this article is to follow all stages of the fabric called Tricia, which is the most produced product in the textile industry, from its entry as fiber to its exit as fabric in the factory, and to calculate and analyze the amount of carbon that is released into nature. The dynamic and experimental results showed that it was determined that 6.00 tons of carbon dioxide carbon were released in the time it took for the fabric to go to the sewing room as a fabric.Öğe A new method for generating short-term power forecasting based on artificial neural networks and optimization methods for solar photovoltaic power plants(Springer Verlag, 2019) Demirdelen, Tugce; Ozge Aksu, Inayet; Esenboga, Burak; Aygul, Kemal; Ekinci, Firat; Bilgili, MehmetIn recent times, solar PV power plants have been used worldwide due to their high solar energy potential. Although the PV power plants are highly preferred, the main disadvantage of the system is that the output power characteristics of the system are unstable. As PV power plant system is connected to the grid side, unbalanced power flow effects all systems controls. In addition, the load capacitys is not exactly known. For this reason, it has become an important issue to be known correctly in PV output power and their time-dependent changes. The main aim of this work is to eliminate power plant instability due to the output power imbalance. For the short-term, power prediction is estimated by real-time data of 1 MW PV power plant in use. Estimation power data are compared with real-time data and precision of the proposed method is demonstrated. In the first phase, traditional artificial intelligence algorithms are used. Then, these algorithms are trained with swarm based optimization methods and the performance analyses are presented in detail. Among all the algorithms used, the algorithm with the lowest error is determined. Thus, this study provides useful information and techniques to help researchers who are interested in planning and modeling PV power plants. © Springer Nature Singapore Pte Ltd. 2019.Öğe A novel hybrid metaheuristic optimization method to estimate medium-term output power for horizontal axis wind turbine(Sage Publications Ltd, 2019) Ekinci, Firat; Demirdelen, Tugce; Aksu, Inayet Ozge; Aygul, Kemal; Esenboga, Burak; Bilgili, MehmetThe increasing damage caused by fossil fuels has made it a necessity for new and clean energy sources. In recent years, the use of wind energy from renewable energy sources has increased, which is a new and clean energy source. Wind energy is everywhere in nature. The wind speed changes depending on time. Thus, the wind power is unstable. In order to keep this disadvantage at a minimum level, future power estimation studies have been carried out. In these studies, different methods and algorithms are applied to estimate short and medium term in wind power. In this study, artificial neural network, particle swarm optimization and firefly algorithm (FA) as a new method are used for the first time in predicting wind power. As input data, temperature, wind speed and rotor speed the data recorded in the SCADA in wind turbines are used to predict medium-term wind speed and also wind power. Each method is compared in detail and their performances are revealed.Öğe A review of magnetically controlled shunt reactor for power quality improvement with renewable energy applications(Pergamon-Elsevier Science Ltd, 2017) Tumay, Mehmet; Demirdelen, Tugce; Bal, Selva; Kayaalp, Rahmi Ilker; Dogru, Burcu; Aksoy, MahmutRenewable energy sources are widely available on Earth; hence they have attracted much interest in both research and practical applications. In the large scale renewable energy system, power quality into the grid, especially harmonics and flicker, impacts on grid system significantly. In recent years, magnetically controlled shunt reactors (MCSRs) have been widely used to solve the problems of the power quality caused a failure or malfunction of the end-user equipment. MCSR can simplify the system reactive power and voltage control in the super / special high-voltage power grid, suppress power frequency and operation over voltage, eliminating generator self excitation, dynamically compensate charging the power in a transmission line, suppress the secondary arc current, damping system resonance and so on, which can meet the various needs of the system, it has a very broad application prospects. This paper presents a comprehensive review of MCSR configurations, the control strategies, the selection of components, other related economic and technical considerations, and their selection for specific applications. It is aimed at providing a broad perspective on the status of MCSR technology to the researchers and the application engineers dealing with power quality issues. A list of more than 130 research publications on the subject is also appended for a quick reference.Öğe Butterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition(Taylor & Francis Inc, 2023) Aygul, Kemal; Cikan, Murat; Demirdelen, Tugce; Tumay, MehmetBecause of dust, trees, high buildings in the surrounding area, partial shading conditions (PSC) occur in photovoltaic (PV) systems. This condition affects the power output of the PV system. Under PSC there is a global maximum power point (GMPP) besides there are a few local maximum power points (LMPP). This condition makes the maximum power point tracking (MPPT) procedure a challenging task. In order to solve this issue, soft computing techniques such as gray wolf optimization (GWO), particle swarm optimization (PSO) and Gravitational Search Algorithm (GSA) are implemented. However, the performance of MPP trackers still needs to be improved. The main contribution of this paper is improving the tracking speed by implementing BOA to the MPPT of the PV system under PSC. Thus, in real-time applications a promising alternative presented to the literature to improve the performance of the PV systems under variable PSC because of its fast tracking speed. PV system consists of PV array, boost converter and load are modeled and simulated in MATLAB/Simulink. BOA algorithm is implemented for three different insolation scenarios on the PV array. The results of the BOA algorithm verified by a comparative analysis with PSO-GSA and GWO algorithms. The results show that BOA can give high accuracy and better tracking speed than these algorithms in recent literature.Öğe Carbon Emission Analysis and Reporting in Urban Emissions: An Analysis of the Greenhouse Gas Inventories and Climate Action Plans in Sarıçam Municipality(Mdpi, 2024) Davutluoglu, Orkun; Yavuzdeger, Abdurrahman; Esenboga, Burak; Demirdelen, Ozge; Ates, Kuebra Tuemay; Demirdelen, TugceThe urban carbon footprint (UCF) is an important tool for assessing an organization's ecological impacts and in guiding sustainability efforts. This calculation is usually measured in tons of carbon dioxide equivalent (CO2-eq). Calculations provide important data to determine strategies to reduce the carbon footprint and establish sustainability targets. Various standards and protocols guide UCF calculation, and many organizations aim to make these data transparent to their stakeholders and the public. This study aims to calculate the UCF of Sar & imath;& ccedil;am Municipality (SM) in the Adana Province of T & uuml;rkiye. This study includes the greenhouse gas emission inventories resulting from all activities of the SM main service building, guest house, construction site service building, Cultural Center service building, and additional service buildings between 1 January 2022 and 31 December 2022. The calculations include generator fuel consumption, electricity consumption, the refrigerant gas leaks and refills resulting from these activities, the fuel consumed in vehicles owned by the company or whose fuel consumption is under company control, emissions originating from personal travel, emissions originating from customers and visitors, emissions originating from business travel, purchases, etc. Emissions from products purchased and emissions from waste transportation are included. The findings show that, in 2022, the total UCF of SM was equal to 10,862.46 tons of CO2-eq. The Paris Agreement aims to reduce the per capita emissions to approximately two tons of CO2-eq by 2030. The carbon footprint per employee within the municipality was calculated at 12.43 tons of CO2-eq, as derived from the analyzed data. The results reveal the importance of implementing sustainable practices and strategies within SM, such as energy efficiency measures, waste reduction, and the adoption of renewable energy sources, to mitigate its carbon footprint. This study plans to provide a basis for SM's reduction efforts by keeping greenhouse gas emissions under control.Öğe Chenille Yarn Production Parameters Improvement Studies and Evaluation of Their Effects(2022) Şener, Arif; Koç, Duygu Durdu; Yılmaz, Kübra; Tosunoğlu, Ece; Çam, Pınar; Gündübay, Anıl; Demirdelen, TugceChenille yarn has an increasing share of use in the upholstery fabric sector recently. To have an important place in chenille yarn production in the world, it has become necessary for manufacturers to improve the quality, durability, and performance of their products and to carry out innovative studies in this field. Increasing the abrasion resistance of the yarns that form the basis of upholstery fabrics will significantly affect the service life performance. In this study, two raw materials selected with different production parameters were examined. These raw materials are determined as viscose and polyester, which are mostly used for chenille yarn in the production facility. The parameters covered in this study are determined and evaluated as the fixed/unfixed state of the yarn, the state of having different twist values, and the presence or absence of melted yarn added to ensure better adhesion of the pile and binder yarn with each other. In this direction, to test the abrasion resistance of the yarns produced from 6 polyester raw materials and 6 viscose raw materials with different properties, they are woven into fabrics by weaving on a 65-density jacquard loom. Each fabricated sample is realized by Martindale test. This test is realized to see the result of friction force and impact effect on the fabric surface. Also, it is aimed to determine the resistance of the samples against pilling and surface change. Based on the results, different parameters affecting the abrasion resistance of upholstery fabrics obtained from chenille yarn were interpreted and it was aimed to be a pioneering study in this field.Öğe Design and Finite Element Analysis of Permanent Magnet Synchronous Generator for Wind Turbine Application(Springer Science and Business Media Deutschland GmbH, 2021) Yavuzdeger, Abdurrahman; Esenboga, Burak; Ekinci, Firat; Demirdelen, TugceToday, the demand for renewable energy sources is increasing day by day in order to reduce fossil fuels and meet the increasing energy demand. The fact that wind energy is suitable for energy production at continuous or low wind speed depending on geographical conditions increases its importance among eco-friendly energy sources. However, energy efficiency is one of the most important issues in the renewable energy field because energy production from these energy sources is constantly changing due to climate changes. Therefore, it is very important to use renewable energy sources efficiently and to enable innovative developments that will increase energy efficiency. In this chapter, a more efficient wind turbine alternator is modeled and analyzed in detail by using the ANSYS/Maxwell software program. The main objective of this chapter is to create an efficient alternator model used in both vertical and horizontal wind turbines. This alternator model is selected as a permanent magnet synchronous generator (PMSG) since there is no need for external excitation, smaller in size and easy to control. Firstly, the parameters are determined by using the mathematical model of the alternator. Secondly, the alternator is modeled and designed with the help of the design parameters such as pole pair, magnetizing inductance, the stator leakage, winding properties, number of turns and slots, etc. During the design process, all materials of the alternator are designed by taking into consideration of characteristic features of them. Finally, the designed alternator is electromagnetically analyzed thanks to ANSYS/Maxwell Electromagnetic Suit program which uses the Finite Element Method (FEM). Therefore, the electrical efficiency of the wind turbine alternator at different wind speeds is performed and the optimum design of the alternator is obtained. It is hoped that this study will guide for wind power plant operators and researchers interested in wind turbine design parameters. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Designing and performance analysis of solar tracker system: A case study of Çukurova region(Elsevier, 2021) Alici, Hakan; Esenboga, Burak; Oktem, Irfan; Demirdelen, Tugce; Tumay, MehmetToday, solar energy has an important place among the renewable energy sources in the world due to its high energy potential. Therefore the share of solar energy is gradually increasing in electricity generation. It is difficult to get maximum efficiency from the solar photovoltaic (PV) panels installed permanently because they can’t benefit from solar energy continuously. Therefore one of the most effective ways to prevent loss of energy efficiency is the solar tracking systems that provide up to 40% efficiency. In this study, it is aimed to increase the efficiency of solar PV plants by following the sun throughout the day and to maximize the power produced by solar PV panels by exposing it to more light. Therefore a single-axis passive-controlled solar tracker system design is recommended for 42, 000 kWp solar PV power plants in the Çukurova region. The efficiency effect of the proposed tracker system for high-power solar PV plants is examined. By comparing the performance analysis of the proposed solar PV system having a solar tracker system with a fixed angle solar PV system, the effectiveness of the proposed system is revealed for high-power solar PV plants. © 2021 Elsevier Inc. All rights reserved.Öğe Effect of partial shading conditions on off-grid solar PV/Hydrogen production in high solar energy index regions(Pergamon-Elsevier Science Ltd, 2019) Mert, Basak Dogru; Ekinci, Firat; Demirdelen, TugceIn present work, the effect of partial shading on off-grid solar PV/hydrogen production in solar energy has been studied. The study was designed to stimulate future work in this area and to help demonstrate PV/hydrogen production. Four different electrodes in the study were coated and used in PV/Hydrogen Production. Pt anode and four different cathode materials which were Cu, Cu/Ni, Cu/NiBi and Cu/NiMo were used in the study. Data obtained from 105 W PV panel via automation system installed at ATU University, Adana, in Turkey were used for data of days representing different seasons by electrolysis experiment. The experiments were carried out between 08:00 and 16:00. The main contribution of this study is to produce hydrogen by using a part of the electrical energy gained from the solar panels, and at the same time to reveal the effect of the electrical energy produced by the partial shading of the panels on the hydrogen production. Furthermore, the effect of cathode material type was investigated for the impact of partial shading on hydrogen production. Results showed that Cu/NiMo has better hydrogen production efficiency than Cu/Ni, Cu/NiBi. The lowest efficiency was observed in the bare Cu electrode. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.Öğe Efficiency and Cost Based Multi-optimization and Thermal/Electromagnetic Analyses of 3-Phase Dry-Type Transformer(Taylor & Francis Ltd, 2022) Esenboga, Burak; Demirdelen, TugceDry-type transformers are one of the most significant devices used in the conversion, transmission and management process of the electricity. In practice, the electrical energy conversion entails energy losses such as heat, electromechanical and electromagnetic losses during the transformation. Hence, primary importance is the efficiency of energy conversion for a device that converts AC voltage from one value to another with the same frequency. Therefore, this study offers the best 3-phase dry-type transformer modelling interested in cost and efficiency related to transformer losses and useful energy conversion. Transformer manufacturing industries will produce a low cost and more efficient dry-type transformer by using electromagnetic/thermal analyzing and multi-optimization methods. Firstly, a 250 VA 380/110 V 3-phase cast resin core type transformer is modelled by an electromagnetic field simulator software programme called as ANSYS/Maxwell so the transformer is analyzed in detail in terms of the thermal and electromagnetic. In addition, the cost and efficiency values are optimized based on the current density (s) and C coefficient parameters by the multi-optimization method. Secondly, the transformer model is analyzed as thermal and electromagnetic at the end of the simulation results. Finally, the transformer is tested experimentally so the test results are confirmed by the simulation results considering the measurements. It is hoped that this study will contribute to transformer designers and operators interested in the conversion, transmission and management of the electrical energy.Öğe Experimental and theoretical study: Design and implementation of a floating photovoltaic system for hydrogen production(Wiley, 2022) Gullu, Emre; Mert, Basak Dogru; Nazligul, Huseyin; Demirdelen, Tugce; Gurdal, YelizIn this study, lab-made modified graphite cathodes were used to design and implement floating PV assisted alkaline electrolysis cell. The influence of temperature on PV performance was studied both experimentally and theoretically, and the PV module performance was investigated in floating as well as non-floating modes. Power generation of floating PV panel and non-floating PV panel at four different air temperatures was examined. Although there was no substantial improvement in power generation at 6 degrees C or 16 degrees C, values improved by 6.25% and 10.75% at 24 degrees C and 37 degrees C, respectively. For alkaline electrolysis cell part of this system, the graphite (G) cathode was galvanostatically coated with nickel (G/Ni) and decorated with cobalt nano-particles (G/Ni/Co). The characterization of the electrode was achieved using X-Ray diffraction (XRD) and field emission scanning electron microscopy (FESEM). The Co(111)-decorated Ni was determined by XRD, the electrode surface was very rough in FE-SEM micrographs, the detected features provided a larger contact area that supported the formation of simultaneous electrochemical reactions. The electrochemical behavior of electrodes were determined in 1 M KOH by cyclic voltammetry (CV). The modified cathode (G/Ni/Co) enhanced the hydrogen production performance owing to lower hydrogen onset potential. Electronic structure calculations were carried out in order to investigate water as well as proton adsorption on a Co-decorated Ni(111) surface. Density Functional Theory (DFT) calculations identified the role of Co cluster and Ni surface on water and proton adsorptions. According to our knowledge of the literature to date, the practical and theoretical analysis of a floating PV assisted-an alkaline electrolysis system that worked with the laboratory-made electrodes has not been performed before. Results showed that floating PV panels were beneficial than land mounted panels and the G/Ni/Co enhanced the hydrogen generation performance of the system.Öğe Experimental investigation on solar PV panel dust cleaning with solution method(Pergamon-Elsevier Science Ltd, 2022) Ekinci, Firat; Yavuzdeger, Abdurrahman; Nazligul, Hueseyin; Esenboga, Burak; Mert, Basak Dogru; Demirdelen, TugceThe efficiency of solar PV panels varies depending on various factors; the type of material used to generate electrical energy, the quality of workmanship in the solar PV panel installation, environmental factors, dirt on the PV panel and design. Dust and dirt formed according to environmental conditions adhere to the solar PV panels and prevent the solar radiation from penetrating the surface. Thus, the solar PV panels need to be cleaned. In this study, three different chemical solutions prepared in laboratory conditions are applied to solar PV panels with a solar PV panel cleaning robot, which is manufactured using 3D printer technology to remove dust and dirt accumulated on solar PV panels for the first time in the literature. Thus, the effectiveness of chemical solutions to increase solar PV panel efficiency is demonstrated. The penetration of chemical solutions on the PV panel surface is ensured by the solar PV panel cleaning robot. The experimental set is realized under natural dust and dirt conditions. The effectiveness of the chemical solutions and electrical performance analysis results of solar PV panels are demonstrated by measurements and tests. The amount of power harvested from the PV panel cleaned using proposed Solution 1 (2-propanol) has been increased by 15%.Öğe Exploiting Digitalization of Solar PV Plants Using Machine Learning: Digital Twin Concept for Operation(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Yalçin, Tolga; Paradell Solà, Pol; Stefanidou-Voziki, Paschalia; Domínguez-García, Jose Luis; Demirdelen, TugceThe rapid development of digital technologies and solutions is disrupting the energy sector. In this regard, digitalization is a facilitator and enabler for integrating renewable energies, management and operation. Among these, advanced monitoring techniques and artificial intelligence may be applied in solar PV plants to improve their operation and efficiency and detect potential malfunctions at an early stage. This paper proposes a Digital Twin DT concept, mainly focused on O&M, to obtain more information about the system by using several artificial intelligence boxes. Furthermore, it includes the development of several machine learning (ML) algorithms capable of reproducing the expected behavior of the solar PV plant and detecting the malfunctioning of different components. In this regard, this allows for reducing downtime and optimizing asset management. In this paper, different ML techniques are used and compared to optimize the selected methods for enhanced response. The paper presents all stages of the developed Digital Twin, including ML model development with an accuracy of 98.3% of the whole DT, and finally, a communication and visualization platform. The different responses and comparisons have been made using a model based on MATLAB/Simulink using different cases and system conditions. © 2023 by the authors.Öğe Green touch for hydrogen production via alkaline electrolysis: The semi-flexible PV panels mounted wind turbine design, production and performance analysis(Pergamon-Elsevier Science Ltd, 2020) Demirdelen, Tugce; Ekinci, Firat; Mert, Basak Dogru; Karasu, Ilyas; Tumay, MehmetThe novel solar-wind integrated system has been firstly used for hydrogen production in literature with validating theoretical, simulated and experimental studies. This integrated system consists of two main parts; solar-assisted wind turbine and alkaline electrolysis cell. In the first part of this system, the semi-flexible PV panels are smoothly integrated on the vertical axis wind turbine blade. This is a unique design in literature, unlike the hybrid systems that include wind turbines and solar PV panels in published literature. The production and testing of the hybrid integrated system in a single structure were performed both in laboratory conditions and also the system was set up the roof of ATU (Adana Alparslan Turkes Science and Technology University) in Adana. The second part includes hydrogen production via alkaline electrolysis system. The cathodes consist of nickel-coated copper (Cu/Ni) and nickel-vanadium binary coated copper (Cu/NiV), that was produced via electrodeposition technique by self-supporting. The performance of electrodes was compared in 1 M KOH solution via I-V behavior, electrochemical impedance spectroscopy, and long term cathodic polarization analysis. Results showed that polarization resistance was decreased almost 4 times by NiV when comparing the Ni. The surface inhomogeneity values were 0.91 and 0.81 for Cu/Ni and Cu/NiV respectively. The hydrogen gas evolved at the cathodes was also measured and higher volumes were detected for NiV binary coating. (C) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.Öğe Investigation of the Carbon Footprint of the Textile Industry: PES- and PP-Based Products with Monte Carlo Uncertainty Analysis(Mdpi, 2023) Demirdelen, Tugce; Aksu, Inayet Oezge; Yilmaz, Kubra; Koc, Duygu Durdu; Arikan, Miray; Sener, ArifThe Carbon Border Adjustment Mechanism was developed to ensure that industrial sectors operating outside the EU follow the same environmental standards and targets while competing with the EU's carbon market. This mechanism aims to calculate the carbon footprint of goods and services imported into the EU and make carbon adjustments accordingly. The transition phase, starting in 2023, represents the period when the Carbon Border Adjustment Mechanism will be implemented. The completion of the transition phase is targeted for 2025. By this date, the effective implementation of this mechanism is aimed at demonstrating that countries outside of the EU comply with emissions regulations using Carbon at Border certificates. The textile industry's products have a significant environmental impact throughout their life cycle, from the production of raw materials to the disposal of the finished product. Textile production, especially synthetic yarns, requires large amounts of energy, contributing to greenhouse gas emissions and climate change. In this study, a cradle-to-customer plus waste life cycle assessment (LCA) is conducted to evaluate the environmental impacts of two products in the textile sector. The Monte Carlo analysis method can be used to handle uncertainties in LCA calculations. It is a method for modeling uncertainties and statistically evaluating results. In this study, this method is preferred at the stage of determining uncertainties. The processes from chips to yarns are investigated for two synthetic yarns: polyester (PES) and polypropylene (PP). The carbon emissions of PP and PES used in textiles are calculated for the first time in this study using detailed modeling with LCAs and a real application. The main production operations are considered: (i) transport of raw materials and packaging material, (ii) energy consumption during the production process, (iii) transport of products, and (iv) end-of-life steps. When the actual data obtained from a company are analyzed, the carbon footprints (CFs) of the PES and PP are calculated to be 13.40 t CO2-eq (t PES)-1 and 6.42 t CO2-eq (t PP)-1, respectively. These data can be used as reference points for future studies and comparisons. According to the results obtained, when the energy consumption and raw material stages in the production of the PES and PP products are compared, it is seen that the CF of PP yarn is lower, and it is more environmentally friendly. These findings can be utilized to enhance government policies aimed at reducing greenhouse gas emissions and managing synthetic yarn production in Turkiye. Since PP and PES raw materials are predominantly used in synthetic yarns, this study's objective is to quantify the carbon emissions associated with the utilization of these raw materials and provide guidance to companies engaged in their production.Öğe Lightning Electric Field Analysis of a Transformer Using ANSYS Maxwell(Institute of Electrical and Electronics Engineers Inc., 2019) Bal, Selva; Demirdelen, Tugce; Tumay, MehmetLightning strike is a very important phenomenon for all electrical power systems because of over voltage impulse. Thus, lightning analysis is equally important for power issue. In this paper, lightning electric field analysis of an oil type distribution transformer with a 25-kVA power capacity using ANSYS Maxwell simulation program are proposed. Lightning impulse voltage applied to transformer, electric field and voltage distribution of the transformer during lightning are presented with simulation results. Critical regions that can cause breakdown on insulation materials between primary and secondary windings are shown as three dimensionally. Electric field distribution on critical regions on insulation material of two-dimensional model is also shown. The comparison of three and two-dimensional analyses are compared for insulation breakdown during lightning analyses. This paper provides advantage researchers and engineers whom design/produce/choose the transformer bushings/isolators and other insulation materials on a simulation program such as ANSYS. In future, optimization study for insulation materials and partial discharge localization will be done. © 2019 IEEE.
