5,404 research outputs found

    Precision Surface Processing and Software Modelling Using Shear-Thickening Polishing Slurries

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    Mid-spatial frequency surface error is a known manufacturing defect for aspherical and freeform precision surfaces. These surface ripples decrease imaging contrast and system signal-to-noise ratio. Existing sub-aperture polishing techniques are limited in their abilities to smooth mid-spatial frequency errors. Shear-thickening slurries have been hypothesised to reduce mid-spatial frequency errors on precision optical surfaces by increasing the viscosity at the tool-part interface. Currently, controlling the generation and mitigating existing mid-spatial frequency surface errors for aspherical and freeform surfaces requires extensive setup and the experience of seasoned workers. This thesis reports on the experimental trials of shear-thickening polishing slurries on glass surfaces. By incorporating shear-thickening slurries with the precessed bonnet technology, the aim is to enhance the ability of the precessions technology in mitigating mid-spatial frequency errors. The findings could facilitate a more streamlined manufacturing chain for precision optics for the versatile precessions technology from form correction and texture improvement, to MSF mitigation, without needing to rely on other polishing technologies. Such improvement on the existing bonnet polishing would provide a vital steppingstone towards building a fully autonomous manufacturing cell in a market of continual economic growth. The experiments in this thesis analysed the capabilities of two shear-thickening slurry systems: (1) polyethylene glycol with silica nanoparticle suspension, and (2) water and cornstarch suspension. Both slurry systems demonstrated the ability at mitigating existing surface ripples. Looking at power spectral density graphs, polyethylene glycol slurries reduced the power of the mid-spatial frequencies by ~50% and cornstarch suspension slurries by 60-90%. Experiments of a novel polishing approach are also reported in this thesis to rotate a precessed bonnet at a predetermined working distance above the workpiece surface. The rapidly rotating tool draws in the shear-thickening slurry through the gap to stiffen the fluid for polishing. This technique demonstrated material removal capabilities using cornstarch suspension slurries at a working distance of 1.0-1.5mm. The volumetric removal rate from this process is ~5% of that of contact bonnet polishing, so this aligns more as a finishing process. This polishing technique was given the term rheological bonnet finishing. The rheological properties of cornstarch suspension slurries were tested using a rheometer and modelled through CFD simulation. Using the empirical rheological data, polishing simulations of the rheological bonnet finishing process were modelled in Ansys to analyse the effects of various input parameters such as working distance, tool headspeed, precess angle, and slurry viscosity

    Dynamic analysis and energy management strategies of micro gas turbine systems integrated with mechanical, electrochemical and thermal energy storage devices

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    The growing concern related to the rise of greenhouse gases in the atmosphere has led to an increase of share of renewable energy sources. Due to their unpredictability and intermittency, new flexible and efficient power systems need to be developed to compensate for this fluctuating power production. In this context, micro gas turbines have high potential for small-scale combined heat and power (CHP) applications considering their fuel flexibility, quick load changes, low maintenance, low vibrations, and high overall efficiency. Furthermore, the combination of micro gas turbines with energy storage systems can further increase the overall system flexibility and the response to rapid load changes. This thesis aims to analyse the integration of micro gas turbines with the following energy storage systems: compressed air energy storage (CAES), chemical energy storage (using hydrogen and ammonia), battery storage, and thermal energy storage. In particular, micro gas turbines integrated with CAES systems and alternative fuels operate in different working conditions compared to their standard conditions. Applications requiring increased mass flow rate at the expander, such as CAES and the use of fuels with low LHV, such as ammonia, can potentially reduce the compressor surge margin. Conversely, sudden composition changes of high LHV fuels, such as hydrogen, can cause temperature peaks, detrimental for the turbine and recuperator life. A validated model of a T100 micro gas turbine is used to analyse transitions between different conditions, identify operational limits and test the control system. Starting from the dynamic constraints defined in the related chapters, in the final part, an optimisation tool for energy management is developed to couple the micro gas turbine with energy storage systems, maximizing the plant profitability and satisfying the local electrical and thermal demands. For the modelling of the CAES system and alternative fuels, the operating constraints obtained from the initial analyses are implemented in the optimisation tool. In addition, a battery and thermal energy storage system are also considered. In the first part, a comprehensive analysis of the T100 combined with a second-generation CAES system showed enhanced efficiency, reduced fuel consumption, reduced thermal power output and increased maximum electrical power output due to the reduction of the rotational speed. The study identified optimal air injection constraints, demonstrating a +3.23% efficiency increase at 80 kW net power with a maximum mass flow rate of 50 g/s. The dynamic analysis exposed potential instabilities issues during air step injections, mitigated by using ramps at a rate of +0.5 (g/s)/s for safe and rapid dynamic mode operation. The second part explored the effects of varying H2-NG and NH3-NG blends on the T100 mGT. Steady-state results showed increased power output with hydrogen or ammonia, notably +6.1 kW for 100% H2 and up to +11.3 kW for 100% NH3. Transient power steps simulations showed surge margin reductions, especially at lower power levels with high concentrations of ammonia, highlighting the need for controlled transitions. Controlled ramps were effective in preventing extreme temperature peaks during fuel composition changes. The final chapter focused on developing an energy scheduler for different plant setups, evaluating four configurations. For a typical day of the month of April of the Savona Campus, the integration of the CAES lead to relative savings of +8.1% and power-to-H2 of +5.3% when surplus electricity was not sold to the grid. Conversely, with the ability to sell excess electricity, CAES and battery energy storage (BES) systems exhibit modest savings of +1.2% and +2.4%, respectively, while the power-to-H2 system failed to provide economic advantages

    Exploiting the potential of chemical looping processes for industrial decarbonization and waste to energy conversion. Process design and experimental evaluations

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    The impact of anthropogenic activities on the environment is leading to climate changes and exceptional meteorological phenomena all over the world. To address this negative trend, the scientific community agrees that the environmental impact from fossil fuels-based power production must be mitigated by the integration with alternative and sustainable technologies, such as renewable energy. However, the time required for the complete development and diffusion of such technology poses the urgency of finding a midterm solution to significantly reduce CO2 emissions. Carbon capture, utilization, and storage (CCUS) technologies represent an interesting option to mitigate CO2 emissions. CCUS involves (among other possible applications) the separation of the CO2 content from industrial off-gases, its transport and storage or its reconversion to a chemical/fuel. Chemical looping can be considered as an oxyfuel combustion where the oxygen supply comes from the lattice oxygen atoms of a solid. It is based on gas-solid reactions where a solid also known as oxygen carrier, generally a metal oxide, undergoes successive reduction and oxidation steps. In the reduction step, normally occurring at high temperatures (700-1000 °C), the oxygen carrier interacts with a reducing agent, such as coal, natural gas, syngas etc. and loses part of its oxygen atoms. By controlling the degree of reduction of the oxygen carrier is thus possible to achieve a complete oxidation of the reducing agent (the fuel) to CO2 and H2O (chemical looping combustion) or a partial oxidation to a syngas (chemical looping reforming and gasification). In these latter case, the introduction of external CO2 and H2O can be of help to support the reforming or gasification processes. The oxygen carrier in the reduced phase is then sent to an air reactor, where it reacquires the oxygen atoms by an exothermic reaction with air. This process presents several advantages according to the specific application. In chemical looping combustion, intrinsic separation of N2 and CO2 is achieved, because the two streams are involved in two different reaction steps. This largely simplifies the CO2 separation effort for storage or utilization purposes. On the other hand, in chemical looping reforming it is possible to achieve autothermal operation thanks to the exothermicity of the oxidation step in the air reactor, as well as high reforming efficiencies. Similarly, in chemical looping gasification the resulting syngas is characterized by no N2 dilution, lower tar release and possibility of autothermal operation. These benefits enhance the energy efficiency of the process, leading to a better energy utilisation. In this work, strategies for the decarbonisation and circularity of the industrial and power sector are proposed based on the synthesis of hydrogen and hydrogen-derived fuels. In particular, the potential of chemical looping technology is deeply studied aiming at exploiting its ability to reconvert or valorise CO2 or waste streams to a syngas and then to a liquid fuel/chemical, such as methanol or ammonia. This task is carried out through modelling and experimental evaluations. The modelling activities mainly concern design of process schemes involving the chemical looping section for waste or CO2 reconversion and the liquid fuel synthesis section. The experimental evaluations are focused on two crucial that have been limitedly discussed in the literature: the thermochemical syngas production step by oxidation with CO2 and H2O streams, the effect of high-pressure operation on the redox abilities of a typical iron and nickel-based oxygen carrier. In Chapter 1, a general overview on the main research developments on chemical looping technology is provided. A section is reserved for each chemical looping variant, i.e. combustion, reforming and gasification, and a general description of each process is provided along with the summary of the main research achievements. Subsequently, the technology is divided by application in power production and chemicals production. Main findings from techno-economic assessment and process designs are discussed in comparison with benchmark technologies and other clean pathways. In Chapter 2 steel mills are taken as an example of the hard-to-abate industry. A H2-based decarbonization strategy is proposed and assessed by Aspen Plus simulation. The strategy starts from an initial configuration that is characterized by a typical blast furnace-basic oxygen furnace steel mill and consider the introduction of direct reduction – electric arc furnace lines, that are more efficient and involve natural gas as reducing agent rather than coke. Sensitivity analyses are carried out to assess the effect of the introduction of H2/CH4 blendings in the direct reduction plant and of the utilization of scrap material in the electric arc furnace. The impact of each configuration on the CO2 emissions and the energy flows of the plant is assessed by mass and energy balances. The results indicate a promising decarbonization potential of the introduced technologies but require large investments to increase the renewable sources penetration in the energy mix and large availability of H2. Therefore, alternative pathways for an earlier decarbonization of hard-to-abate industries and for large scale syngas/H2 production need to be considered. In Chapter 3, a novel process scheme is proposed involving chemical looping for syngas production. The CO2 content in blast furnace gases is separated with a calcium looping cycle and subsequently injected with H2O into the oxidation reactor of a chemical looping cycle. Assuming an inlet stream of pure CO2, mass balances on the chemical looping plant are carried out to compare the performance of nickel ferrites and iron oxides in terms of required oxygen carrier flow rate to process 1 t/h of CO2. Computational fluid dynamics simulations with integrated reaction kinetics are then carried out to validate the assumptions on the oxygen carrier conversion and syngas compositions. In Chapter 4 and 5, experimental evaluations are carried out on two crucial aspects for the successful operation of a chemical looping plant aiming at syngas production. In Chapter 4, the syngas productivity by CO2 and H2O splitting over a Fe bed is investigated. This is a very important step, and the effect of various parameters was considered. Firstly, the CO2 splitting is analysed for different temperatures with an inlet flow rate of 1 NL/min to ensure a substantial dissociation of the CO2. Subsequently, combined streams of CO2 and H2O are evolved in the reactor. The effect of the total flow rate, reactants molar ratio and bed height is investigated and from the results, the optimal syngas composition is identified. SEM and XRD are used to assess the morphological evolution and the phase changes of the material during the test. On the contrary, in Chapter 5 the effect of high-pressure operation on the redox abilities of two NiFe aluminates is assessed. The aluminates present similar Fe loadings, but different Ni loadings. High pressure operation is crucial for the development of this technology because it facilitates downstream processing of the syngas to liquid fuels. For a comparative analysis, preliminary tests at low pressure are carried out at three temperatures. Subsequently, the effect of reactants flow rate, temperature, total pressure, gas composition is analysed at high pressure conditions. Finally, long term tests are performed both at ambient and high-pressure conditions. Material characterization by SEM, XRD and H2-TPR is used to support the comparative analysis. In Chapter 6, a techno-economic analysis on a process scheme encompassing methanol and ammonia production from chemical looping gases is carried out. Chemical looping hydrogen production is a very versatile technology and allows for the combined production of power and H2 or syngas. With proper calibration of the flow rates, a stream of high purity N2 can also be obtained at the air reactor outlet and used for ammonia synthesis. Back up with an alkaline electrolyser is considered for the supply of the required amount of hydrogen. Sensitivity analyses are carried out on the chemical looping plant to evaluate the effect of fuel flow rate, steam flow rate, and oxygen carrier inlet temperature to the fuel reactor. Subsequently, a techno-economic analysis is carried out evaluating several parameters among which: the specific CO2 emissions, the energy intensity, and the levelized cost of methanol and ammonia. Finally, a comparison with benchmark technologies and other clean alternatives is presented. In this way, the benefits as well as the drawbacks of chemical looping in terms of environmental and economic parameters are assessed and the missing elements to reach industrial competitivity are clarified

    Mapping the Focal Points of WordPress: A Software and Critical Code Analysis

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    Programming languages or code can be examined through numerous analytical lenses. This project is a critical analysis of WordPress, a prevalent web content management system, applying four modes of inquiry. The project draws on theoretical perspectives and areas of study in media, software, platforms, code, language, and power structures. The applied research is based on Critical Code Studies, an interdisciplinary field of study that holds the potential as a theoretical lens and methodological toolkit to understand computational code beyond its function. The project begins with a critical code analysis of WordPress, examining its origins and source code and mapping selected vulnerabilities. An examination of the influence of digital and computational thinking follows this. The work also explores the intersection of code patching and vulnerability management and how code shapes our sense of control, trust, and empathy, ultimately arguing that a rhetorical-cultural lens can be used to better understand code\u27s controlling influence. Recurring themes throughout these analyses and observations are the connections to power and vulnerability in WordPress\u27 code and how cultural, processual, rhetorical, and ethical implications can be expressed through its code, creating a particular worldview. Code\u27s emergent properties help illustrate how human values and practices (e.g., empathy, aesthetics, language, and trust) become encoded in software design and how people perceive the software through its worldview. These connected analyses reveal cultural, processual, and vulnerability focal points and the influence these entanglements have concerning WordPress as code, software, and platform. WordPress is a complex sociotechnical platform worthy of further study, as is the interdisciplinary merging of theoretical perspectives and disciplines to critically examine code. Ultimately, this project helps further enrich the field by introducing focal points in code, examining sociocultural phenomena within the code, and offering techniques to apply critical code methods

    Multi-Objective Density Diagrams Developed With Machine Learning Models to Optimize Sustainability and Cost-Efficiency of UHPC Mix Design

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    The emergence of ultra-high-performance concrete (UHPC) as an attractive solution for precast and prestressed applications has coincided with global efforts towards sustainable construction. The increasing need for tools capable of intuitively demonstrating the effect of concrete mixture composition on mechanical performance, cost and eco-efficiency concurrently has motivated this work in an effort to promote design of more sustainable solutions to help meet environmental goals. Such tools are needed to effectively evaluate the environmental impact of UHPC given the outstanding mechanical properties of the material coupled with high volumetric embodied CO2. Meanwhile, artificial intelligence (AI) techniques have emerged as a great opportunity for game-changing tools capable of effectively modeling the synergistic relationships between mix proportions and material performance. This work couples machine learning models with orthogonal arrays to generate machine-learning-based tools to evaluate the tradeoffs between emissions, cost and mechanical performance concurrently. Random forest and k-nearest neighbors’ models are ensembled to predict the compressive strength of UHPC mixtures and generate Performance Density Diagrams (PDDs). These predicted strengths are then coupled with volumetric environmental factors and unit costs to generate eco- and cost-efficiency density diagrams. The makeup of these tools facilitates the evaluation of rather complicated trends associated with mix proportions and multi-objective outcomes, allowing AI-based tools to be of easy use by industry personnel on a daily basis, while serving as decision-making aids during mix design stages and provide proof of mixture optimization that could be introduced in Environmental Product Declarations. The PDD developed herein enabled the design of a mix with compressive strength of 155 MPa, while keeping the aggregate-to-cementitious ratio above unit. Other mixtures were developed from these models and compared to several different concretes from the literature. Results show that high paste content, high strength (and ultra-high strength) concrete technologies are not necessarily detrimental to cost or eco efficiencies. For the different indices evaluated, optimum solutions were mostly obtained with these types of concrete, which means that industry trends toward requiring minimization of embodied CO2 in concrete on a per volume basis are misguided and do not minimize the embodied CO2 in concrete structures

    SCENARIO DEVELOPMENT FOR URBAN WATER MANAGEMENT PLANNING FOR UNCERTAINTY

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    The urban water sector is confronted with a multitude of challenges. Rapid population growth, changing political landscapes, aging water infrastructures, and the worsening climate crisis are creating a range of uncertainties in the sector around managing water. Scenarios have been used extensively in the environmental domain to plan for and capture uncertainties to develop plausible futures, including the field of urban water management. Scenarios are key in enabling plans and creating roadmaps to attain desired futures. Despite the advantages and opportunities that scenarios offer for planning, they also have limitations; generally, and within the urban water space. Firstly, the growing uncertainty surrounding urban water management systems necessitates a focused review specifically aimed at the use of scenarios in urban water management. This thesis presents a systematic review to empirically investigate the crucial dimensions of urban water scenarios. Through this review, key knowledge gaps are highlighted, and recommendations are proposed to address these gaps. Secondly, scenarios often depict distressing, almost dystopian futures. Though negative future visions help understand the consequences of present trends and aid in anticipating imminent threats, the limited exploration of positive future visions can make it challenging to find the direction to transform. Optimistic scenarios delve into what people want for the future and capture how their aspirations shape them. Imagining positive visions encourage innovative thinking, creates agency, and creates pathways to desired futures. There is therefore a recognition to move towards more positive, desirable futures. This thesis uses a narrative, participatory scenario process, the SEEDS method, to develop positive visions of urban water futures. The Greater Sydney region in New South Wales, Australia is used as a case study to evaluate the applicability of this approach for urban water management. The urban water sector in the Greater Sydney region faces a multitude of challenges including impacts from climate change, managing diverse water supply sources, and meeting future water demand. These challenges create an increasingly uncertain future for the water sector, where the scale and nature of water services needed in the Greater Sydney region can be unclear. Hence, the Greater Sydney region is selected as the case study region to apply the SEEDS method and develop scenarios for urban water management to plan for future uncertainties. Thirdly, only a few scenario studies include surprises, the unexpected events, which make scenarios useful for planning. Challenges around capturing surprises in scenarios include a lack of structured approaches as well as a lack of evaluation of those methods that have been developed. This thesis discusses the effectiveness and suitability of various surprise methods for scenario development. These methods have been applied in the context of the SEEDS method for urban water management. Finally, there is a lack of evaluation of the tools used to cope with surprises as well as a lack of evaluation efforts of urban water management scenario studies. The assessment of the SEEDS approach for urban water management as well as the different surprise methods for scenario development requires evaluation criteria. This thesis develops and presents an evaluation criteria list based on existing literature that captures key criteria required for adequate assessment of the surprise methods and the scenario process. This thesis contributes to the fields of scenario development and urban water management, and the use of surprises within scenarios. Critical gaps in existing urban water management scenario practices are highlighted and key recommendations are proposed to fill the gaps. Through the pilot study and full-scale implementation of a positive-visioning, narrative-based scenario approach - the SEEDS method, the thesis demonstrates that the SEEDS method is applicable for urban water planning and shows potential for use at different stages of water planning. The positive visions generated through the SEEDS method highlight fundamental aspirations for the urban water sector, possible challenges, and conflicts, and discuss pathways to achieve positive future visions. By using in-situ experimentation and engaging participants with expertise in the relevant field, this thesis provides a realistic evaluation of the scenario process and surprise methods. This thesis thus fills the critical gap about the lack of evaluation in urban water management scenario processes by assessing the scenario method using selected evaluation criteria. Further, the thesis contributes towards the development of quality surprise methods through application and evaluation, thus addressing the gap about the lack of evaluation of the methods used to explore surprise events. Finally, the lack of surprises in scenarios is addressed by presenting different methods that can be used to explore surprise events. Guidance is provided to researchers working with scenario development to understand the different surprise methods available and for choosing the appropriate method(s) to plan for uncertain futures

    Enhancement of Charging Resource Utilization of Electric Vehicle Fast Charging Station with Heterogeneous EV Users

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    This thesis presents innovative charging resource allocation and coordination strategies that maximize the limited charging resources at FCS with heterogeneous EV users. It allows opportunistic EV users (OEVs) to exploit available charging resources with dynamic event-driven charging resource allocation and coordination strategies apart from primary EV users (PEVs) (registered or scheduled EV users). Moreover, developed strategies focus on the limited charging resources that are allocated for primary/ registered EV users (PEVs) of the FCS who access the FCS with specific privileges according to prior agreements. But the available resources are not optimally utilized due to various uncertainties associated with the EV charging process such as EV mobility-related uncertainties, EVSE failures, energy price uncertainties, etc. Developed strategies consider that idle chargers and vacant space for EVs at the FCS is an opportunity for further utilizing them with OEVs using innovative charging resource coordination strategies. This thesis develops an FCS-centric performance assessment framework that evaluates the performance of developed strategies in terms of charging resource utilization, charging completion and the quality of service (QoS) aspects of EV users. To evaluate QoS of EV charging process, various parameters such as EV blockage, charging process preemptage, mean waiting time, mean charging time, availability of FCS, charging reliability, etc are derived and analyzed. In addition, the developed innovative charging resource allocation and coordination strategies with resource aggregation and demand elasticity further enhance the charging resource utilization while providing a high QoS in EV charging for both PEVs and OEVs.publishedVersio

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This ïŹfth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ïŹelds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiïŹed Proportional ConïŹ‚ict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiïŹers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiïŹcation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiïŹcation. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiïŹcation, and hybrid techniques mixing deep learning with belief functions as well

    Comparing the production of a formula with the development of L2 competence

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    This pilot study investigates the production of a formula with the development of L2 competence over proficiency levels of a spoken learner corpus. The results show that the formula in beginner production data is likely being recalled holistically from learners’ phonological memory rather than generated online, identifiable by virtue of its fluent production in absence of any other surface structure evidence of the formula’s syntactic properties. As learners’ L2 competence increases, the formula becomes sensitive to modifications which show structural conformity at each proficiency level. The transparency between the formula’s modification and learners’ corresponding L2 surface structure realisations suggest that it is the independent development of L2 competence which integrates the formula into compositional language, and ultimately drives the SLA process forward
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