2,385 research outputs found

    Canada\u27s Evergreen Playground: A History of Snow in Vancouver

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    The City of Vancouver is not as snowy as the rest of Canada; rain, not snow, is its defining weather feature. But snow is a common seasonal occurrence, having fallen there nearly every winter since the 1850s. This dissertation places snow at the centre of the City of Vancouver’s history. It demonstrates how cultural and natural factors influenced human experiences and relationships with snow on the coast between the 1850s and 2000s. Following Vancouver’s incorporation, commercial and civic boosters constructed – and settlers adopted – what I call an evergreen mentality. Snow was reconceptualized as a rare and infrequent phenomenon. The evergreen mentality was not completely false, but it was not entirely true, either. This mindset has framed human relationships with snow in Vancouver ever since. While this idea was consistent, how coastal residents experienced snow evolved in response to societal developments (such as the rise of the automobile and the adoption of new snow-clearing technologies) and regional climate change. I show that the history of snow in Vancouver cannot be fully understood without incorporating the southern Coast Mountains. Snow was a connecting force between the coastal metropolis and mountainous hinterland. Settlers drew snowmelt to the urban environment for its energy potential and life-sustaining properties; snow drew settlers to the mountains for recreation and economic opportunities. Mountain snow became a valuable resource for coastal residents throughout the twentieth century. Human relationships with snow in the mountains were shaped, as they were in the city, by seasonal expectations, societal circumstances, and shifting climate conditions. In charting a history of snow in Vancouver and the southern Coast Mountains, this dissertation clears a new path in Canadian environmental historiography by bringing snow to the historiographical forefront. It does so in an urban space not known for snow, broadening the existing geography of snow historiography. In uncovering snow’s impact on year-round activities, this work also expands the field’s temporal boundaries. Through this work, one sees how snow helped to make Canada’s Evergreen Playground

    Adaptive Data-driven Optimization using Transfer Learning for Resilient, Energy-efficient, Resource-aware, and Secure Network Slicing in 5G-Advanced and 6G Wireless Systems

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    Title from PDF of title page, viewed January 31, 2023Dissertation advisor: Cory BeardVitaIncludes bibliographical references (pages 134-141)Dissertation (Ph.D)--Department of Computer Science and Electrical Engineering. University of Missouri--Kansas City, 20225G–Advanced is the next step in the evolution of the fifth–generation (5G) technology. It will introduce a new level of expanded capabilities beyond connections and enables a broader range of advanced applications and use cases. 5G–Advanced will support modern applications with greater mobility and high dependability. Artificial intelligence and Machine Learning will enhance network performance with spectral efficiency and energy savings enhancements. This research established a framework to optimally control and manage an appropriate selection of network slices for incoming requests from diverse applications and services in Beyond 5G networks. The developed DeepSlice model is used to optimize the network and individual slice load efficiency across isolated slices and manage slice lifecycle in case of failure. The DeepSlice framework can predict the unknown connections by utilizing the learning from a developed deep-learning neural network model. The research also addresses threats to the performance, availability, and robustness of B5G networks by proactively preventing and resolving threats. The study proposed a Secure5G framework for authentication, authorization, trust, and control for a network slicing architecture in 5G systems. The developed model prevents the 5G infrastructure from Distributed Denial of Service by analyzing incoming connections and learning from the developed model. The research demonstrates the preventive measure against volume attacks, flooding attacks, and masking (spoofing) attacks. This research builds the framework towards the zero trust objective (never trust, always verify, and verify continuously) that improves resilience. Another fundamental difficulty for wireless network systems is providing a desirable user experience in various network conditions, such as those with varying network loads and bandwidth fluctuations. Mobile Network Operators have long battled unforeseen network traffic events. This research proposed ADAPTIVE6G to tackle the network load estimation problem using knowledge-inspired Transfer Learning by utilizing radio network Key Performance Indicators from network slices to understand and learn network load estimation problems. These algorithms enable Mobile Network Operators to optimally coordinate their computational tasks in stochastic and time-varying network states. Energy efficiency is another significant KPI in tracking the sustainability of network slicing. Increasing traffic demands in 5G dramatically increase the energy consumption of mobile networks. This increase is unsustainable in terms of dollar cost and environmental impact. This research proposed an innovative ECO6G model to attain sustainability and energy efficiency. Research findings suggested that the developed model can reduce network energy costs without negatively impacting performance or end customer experience against the classical Machine Learning and Statistical driven models. The proposed model is validated against the industry-standardized energy efficiency definition, and operational expenditure savings are derived, showing significant cost savings to MNOs.Introduction -- A deep neural network framework towards a resilient, efficient, and secure network slicing in Beyond 5G Networks -- Adaptive resource management techniques for network slicing in Beyond 5G networks using transfer learning -- Energy and cost analysis for network slicing deployment in Beyond 5G networks -- Conclusion and future scop

    Effect of constituent materials in cementitious composites on the durability of military airfield rigid pavements

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    Military airbases face challenges such as high temperatures from jet exhaust, spills of aviation oil during refuelling and maintenance, and other factors. The combination of these factors leads to spalling, which is the deterioration of the concrete pavement. Spalling creates debris that poses a risk to jets and maintenance crews. This research aims to understand the causes of spalling in military pavements and develop suitable cementitious materials by adjusting the binder, aggregate, and incorporating different types of fibres. To simulate airfield conditions, the laboratory used an electric oven to generate heat similar to jet exhaust and spills of aviation fuel, engine oil, and hydraulic oil on the pavement. Various concrete specimens like cylinders, cubes, and beams were tested for their mechanical and thermal properties. The research focused on creating spalling-resistant cementitious composites by adjusting the Portland cement concrete mix ratios, geopolymer concrete, aggregates, silica fume, and steel/polyvinyl alcohol fibres. The degradation and decomposition of concrete mineral components were assessed using FTIR, XRD, and TG/DSC tests. The chemical composition of aviation oils was also analysed. The presence of fatty acid esters and phosphates in aviation oil react with concrete, forming harmful salts and reducing mechanical properties at high temperatures. Since aggregates make up a significant portion of concrete, lightweight aggregates, which perform better under high temperatures, were evaluated alongside normal-weight aggregates. Geopolymer concrete, incorporating 20% silica fume and hybrid fibres, was tested for its resistance to spalling due to its excellent fire resistance. The addition of hybrid fibres significantly enhanced the performance of the concrete. Overall, this cementitious matrix demonstrated the best performance under simulated airfield conditions. Therefore, the study recommends using geopolymer concrete with 20% silica fume, partially replacing basalt aggregate with lightweight brick chips, and incorporating 0.7% hybrid fibres for cementitious matrices in military airbases

    State machine-based architecture to control system processes in a hybrid fuel cell electric vehicle

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    This paper presents the development and implementation of a system supervisory controller in a hydrogen-based fuel cell electric vehicle. The controller's primary function is to ensure the safe control of the fuel cell system processes while facilitating coordination among various subsystems, including the balance of plant subsystems, vehicle control unit, diagnosis unit, and powertrain. The supervisory controller comprises of three primary parts: a State Machine, an Optimal Setpoint Generator, and a Power Limit Calculator. The State Machine, which serves as the central part of the supervisory controller, coordinates the fuel cell system's different operational states, including the complex processes of start-up and shutdown. To maximize the fuel cell system's efficiency and minimize the stack's degradation, the Optimal Setpoint Generator produces the subsystem's setpoints by solving an optimization problem and considering the manufacturer's requirements. The Power Limit Calculator assesses the stack's power output capability and calculates the current setpoint for the DC/DC converter. It then provides this data to the Energy Management System (EMS), which oversees the distribution of power between the fuel cell system and the batteries. The proposed fuel cell system supervisory controller is verified using the Worldwide Harmonized Light Vehicles Test Cycles (WLTC) in a real-world car. The designed control structure is implemented in a prototype hydrogen-based electric car at both PowerCell and CEVT facilities under the framework of the INN-BALANCE Horizon 2020 European project

    A distributed and energy‑efficient KNN for EEG classification with dynamic money‑saving policy in heterogeneous clusters

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    Universidad de Granada/CBUASpanish Ministry of Science, Innovation, and Universities under Grants PGC2018-098813-B-C31,PID2022-137461NB-C32ERDF fund. Funding for open access charge: University of Granada/ CBU

    2022 comprehensive permanent improvement plan for the plan years 2023-2027 statewide

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    This planning document tells the costs and funding sources for capital improvements of state agencies for the plan years 2023-2027. Each agency has a summary of proposed permanent improvement projects including funding source, functional group and business area

    An investigation of energy saving behaviour for residential buildings in Nigeria

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    Threats of climate change, global warming and uncertainty about future energy prices have sparked a global discussion about energy efficiency, particularly energy saving behaviour in residential buildings. Numerous challenges have been faced in achieving energy savings, with specific concern on energy consumption behaviour of building occupants. Accordingly, governments have set targets through policies for the reduction of energy emission, these have been adopted by the building industry through policies on energy efficiency in buildings including public private partnership in energy management and the development of near zero energy buildings.Previous studies have shown that occupant behaviour can result in a significant amount of variance in building energy use. To address these challenges in line with objectives of sustainable development goal (clean and sustainable energy and climate action), as well as energy efficiency in residential buildings, this research investigated key factors as well as practices that determine and limit energy saving behaviour in residential buildings from a different cultural perspective. Nigeria has been constantly confronted with an electricity demand that exceeded supply capacity. The increased demand for electricity can be attributed to growing populations, increased commercial activity and industrialisation. Households are a significant contributor to the rapidly increasing electricity demand as identified. Energy providers resort to ‘load shedding’ of electricity supply between communities and industries and even long-term electrical outage due to limited supply. It is also important to understand how the actions of occupants affect energy consumption behaviour in residential buildings. To reduce electricity demand and save energy, this research exploited literature on energy saving behaviour and behaviour change. The research study was conducted based on a sequential exploratory mixed method and consists of two key phases. Firstly, qualitative data was collected using semi-structure interview with eighteen experts in the energy and construction industry in Nigeria. The purpose of which was to provide an insight into residential energy consumption behaviour and the barriers faced in the adoption of sustainable energy sources. Analysis from the result shows that cost of energy is a major driver to the adoption of energy saving practices as there are no compulsory regulatory agencies to enforce and facilitate the migration to a more sustainable and innovative society. Furthermore, results also show that there is a need for continuous awareness on energy saving behavioural change, a need for government subsidies on renewable energy, government checks and standardization of energy efficient appliances imported into the country could improve the trust towards sustainable choices and promote efficient energy use. The second phase involved a household survey with 317 households from the case study area. The survey instrument was developed based on the constructs of energy culture framework, sociodemographic factors and physical environment. The hypothesised relationship from the conceptual model were tested using structural equation modelling (SEM). The results indicated that energy practices, material culture, attitude perception cognitive and social norms with behaviour changes were statistically significant, with attitude perception cognitive and social norms having the least impact on behaviour change. Additionally, the correlations from the constructs shows a direct relationship with behaviour change in achieving energy efficiency and energy saving approach while a deliberate policy to achieve energy efficiency and energy saving practices is vital to achieve sustainable development goals. The outcome from this work provided a better understanding of drivers and barriers to energy use behaviour and will inform future energy policy and interventions related to household energy saving. It also will contribute to the existing body of knowledge as well as give policy direction of governments towards climate action and some specific objectives of sustainable development goals

    The Political Dynamics of Electricity Sector Performance in Ghana and Côte d'Ivoire

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    What factors drive variation in policy choices related to the electricity sector and, ultimately, in sectoral performance over time? This dissertation argues that differences in the form and intensity of competitive political pressures affect the choice and implementation of electricity sector policies and thus sectoral performance. First, I explore bivariate relationships between commonly cited external factors – natural resource endowments, economic shocks, investment climate, droughts, and civil wars – and sectoral performance across Sub-Saharan Africa. The findings confirm associations between these factors and sectoral performance. Yet they indicate considerable unexplained variation in sectoral performance, which requires qualitative analysis. Second, I analyze the politics of electricity sector management in Ghana and Côte d’Ivoire. In the 1980s and 1990s, these two countries faced similar economic and climatic crises that brought the electricity sector to its knees. Yet when the World Bank and the IMF pushed neoliberal policies as solutions for sectoral challenges, they responded differently. Liberalization and privatization policies moved forward more quickly in Côte d’Ivoire than in Ghana. Moreover, electricity sector performance differed in the two countries during 1990-2019. Electrification rates accelerated in Ghana, but they slowed in Côte d’Ivoire. Côte d’Ivoire improved the reliability of electricity supply more than Ghana. Electricity prices also reflected costs of service in Côte d’Ivoire but not in Ghana. The comparative political analysis traces how different forms and intensity of competitive political pressures, especially coups d’état, electoral threats, civil wars, and risks of civil wars, affect the implementation of electricity sector policies and then sectoral performance in Ghana and Côte d’Ivoire. I argue that intense political competition encourages Ghanaian politicians to extend electricity access to rural areas to mobilize political support and to set artificially low tariffs to appease urban residents and swing voters. Politically motivated low tariffs, coupled with unpaid subsidies and governments’ failure to pay their own electricity bills, result in inadequate investments in power utilities and, in turn, recurrent power shortages and outages. On the other hand, I argue that existential threats, mainly contestations over Ivorian identity and citizenship and civil war, slowed electrification programs with governments prioritizing regime and national stability. My study shows that (the risks of) civil wars crowd out ordinary concerns like electricity provision. However, when political life returns to normal, high competition drives governments to mollify voters by extending access to electricity and setting below-cost tariffs. Low competition allows governments to make policy changes they view as solutions for sectoral challenges but might defer short-term voter gratification. I demonstrate that low electoral threats encouraged the privatization of the state-owned electricity company in Côte d’Ivoire. In contrast, intense political competition discouraged ruling elites from privatizing the national electricity distributor in Ghana

    INTEGRATED PROTONIC CERAMIC ELECTROCHEMICAL CELL FOR SUSTAINABLE ENERGY ECONOMY USING WATER-ENERGY NEXUS FRAMEWORK

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    Reliance on fossil fuels will continue for the next decades even though there are global pushes away from it to mitigate the overarching climate challenge, most especially by its highest consumers and availability. While there is a hastening global shift away from fossil fuel, integrating its assets into this technology helps limit the risk and future losses of stranded assets and reduce the cost of investment in the new technologies. Moreover, the generation of electricity from intermittent renewable sources like solar and wind has witnessed a significant surge in recent years, leading to a pressing demand for practical energy storage systems. Electrical energy storage is anticipated to play a pivotal role in the future global energy system, facilitating load-leveling operations to support the greater integration of renewable and distributed generation. Reversible electrochemical cells (RECs) offer a promising option for addressing the fossil fuel assets integration and energy storage challenges through the interconversion between electrical and chemical energy and concurrent utilizing carbon emission. In their electrolysis mode, the RECs convert electricity into durable, storable, and portable valuable chemical fuels such as syngas and methane. Conversely, the produced chemical fuels can be used as reactants in the fuel cell mode to generate electricity on demand with minimal (hydrocarbons) or zero when H2 or NH3 is used emissions. However, a challenging goal for this type of technology remains to achieve optimal operation and high roundtrip efficiencies, which has hindered the deployment of previous electrochemical cells. This dissertation demonstrates how reversible protonic ceramic electrochemical cells (RePCECs) can be integrated with fossil fuel power plants and renewable energy sources as a potential energy storage system. In this work, integrated RePCEC systems are designed and examined using computational modeling at scales to determine appropriate system configurations and operating conditions that achieve high roundtrip efficiencies. Cell level design of the PCEC is the first approach, several cells are assembled for the stack level model that is integrated into combined cycle powerplant and solar photovoltaic for the system level model. After critical literature review, this answered the operational and integration research questions proposed to address these challenges. The designed systems perform two functions, utilizing captured CO2 and storing renewable energy through co-electrolysis of steam and CO2. The co-electrolysis reaction involves endothermic water electrolysis and exothermic methanation reaction. To enhance high roundtrip efficiency, there is a need for thermal balance and management in the electrolysis mode. This involves operating the RePCEC stack under conditions that favor methane production to balance out heat needed by water electrolysis, it crucial for the RePCEC system operation. Methanation is enhanced by low temperatures. Leveraging on fabricated BCZYYb-electrolyte RePCEC, the cell model designed revealed that the optimum temperature for methane production is 450℃ at atmospheric pressure. Thus, to achieve optimum system performance, operating in the temperature range 450-525℃ is recommended at the given configuration, combining between the optimum temperature for methane production and temperature for the optimum stack roundtrip efficiency. Configuration with carbon capture system and purge stream is the optimum configuration from the seven conceptualized and evaluated. The modeling outcomes include a thermodynamic examination of integrated RePCEC systems, calibration of cell and stack level models, and steady-state simulation and integration into a 600MW combined cycle power plant retrofitted with two two-stage membrane-based carbon capture system and a wastewater treatment and recovery unit. At 100% powerplant loading, the stack and system roundtrip efficiencies are 72% and 51.37% respectively. Adding a purge stream for produced hydrogen at the system downstream improves the efficiencies to 74 and 55.48% respectively. At atmospheric pressure and 525℃, the system model suggests that a stack roundtrip of 82% is achievable, and overall system efficiency increases by reducing the energy consumption by the balance of plant components for steam generation and storage. Economic analysis of the process gives levelized cost of methane as 2.24/MMBtulowerthantheconventionalproductionroutethatrangebetween2.24/MMBtu lower than the conventional production route that range between 3.46/MMBtu and $9.85/MMBtu. The lifecycle analysis shows that the global warming potential for the production of methane and hydrogen from the RePCEC system is 3.83 kg CO2 eq which is lower than 9.35 kg CO2 eq emission during steam methane reforming for hydrogen production. This answered both the environmental and economic concerns in the raised research question. The proposed RePCEC configuration and analysis carried out in this dissertation to address the surge in renewable energy and challenges with PCEC technology hold significant potential in achieving large-scale energy storage while simultaneously reducing carbon emissions. These advancements, coupled with suitable governmental policies and incentive programs, have the potential to economically disrupt the natural gas industries by using RePCEC systems for methane production, thereby making them more favorable for eventual implementation and commercialization
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