907 resultados para Hyperbolic Dynamic System
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257 p.
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Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.
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Part 10: Sustainability and Trust
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We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge–Kutta total variation diminishing for time integration.
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Most of the current domestic installations are single phase, with contracted power equal to or less than 15 kW and with a potential difference of 230 V. When consumption is expected to be higher you choose to use three different alternating currents with a difference voltage of 400 V between them, which are called phases. This enables the subdivision of the installation in different single-phase circuits, fed independently with the neutral installation. These couples have, in turn, a difference in voltage of 230 V. The neutral is common for all three phases so that, if the system is balanced, no current flows through it. The problem with these installations is that they are designed to work in an offset manner, using phase loads, and simultaneously an equal amount of energy consumed by the three phases of the network. Connection to each of the phases makes independent single-phase loads or disturbance of the operation of the original phase circuit and, consequently, the corresponding increases in consumption, heating of engines, etc.
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Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.
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Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system’s dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.
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Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.
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The objective of this study was to determine the dynamics and diversity of Escherichia coli populations in animal and environmental lines of a commercial farrow-to-finish pig farm in Spain along a full production cycle (July 2008 to July 2009), with special attention to antimicrobial resistance and the presence of integrons. In the animal line, a total of 256 isolates were collected from pregnant sows (10 samples and 20 isolates), 1-week-old piglets (20 samples and 40 isolates), unweaned piglets (20 samples and 38 isolates), growers (20 samples and 40 isolates), and the finishers' floor pen (6 samples and 118 isolates); from the underfloor pits and farm slurry tank environmental lines, 100 and 119 isolates, respectively, were collected. Our results showed that E. coli populations in the pig fecal microbiota and in the farm environment are highly dynamic and show high levels of diversity. These issues have been proven through DNA-based typing data (repetitive extragenic palindromic PCR [REP-PCR]) and phenotypic typing data (antimicrobial resistance profile comprising 19 antimicrobials). Clustering of the sampling groups based on their REP-PCR typing results showed that the spatial features (the line) had a stronger weight than the temporal features (sampling week) for the clustering of E. coli populations; this weight was less significant when clustering was performed based on resistotypes. Among animals, finishers harbored an E. coli population different from those of the remaining animal populations studied, considering REP-PCR fingerprints and resistotypes. This population, the most important from a public health perspective, demonstrated the lowest levels of antimicrobial resistance and integron presence.
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In this article the authors use two EERA networks as a case for a discussion on the development of research networks within the European Educational Research Association (EERA). They contend that EERA networks through their way of working create a European research space. As their case shows, the development of networks is diverse. The emergence of networks and the current group of thirty-one networks do not display a coherent and unified system. Thus they argue that EERA networks have to be studied as an open complex system in order to comprehend the multiplicity and creative and innovative space that these networks represent. They create a space for knowledge production in a European context, enabling educational researchers to see and experience their research in a more diverse setting.
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Predicting the evolution of a coastal cell requires the identification of the key drivers of morphology. Soft coastlines are naturally dynamic but severe storm events and even human intervention can accelerate any changes that are occurring. However, when erosive events such as barrier breaching occur with no obvious contributory factors, a deeper understanding of the underlying coastal processes is required. Ideally conclusions on morphological drivers should be drawn from field data collection and remote sensing over a long period of time. Unfortunately, when the Rossbeigh barrier beach in Dingle Bay, County Kerry, began to erode rapidly in the early 2000’s, eventually leading to it breaching in 2008, no such baseline data existed. This thesis presents a study of the morphodynamic evolution of the Inner Dingle Bay coastal system. The study combines existing coastal zone analysis approaches with experimental field data collection techniques and a novel approach to long term morphodynamic modelling to predict the evolution of the barrier beach inlet system. A conceptual model describing the long term evolution of Inner Dingle Bay in 5 stages post breaching was developed. The dominant coastal processes driving the evolution of the coastal system were identified and quantified. A new methodology of long term process based numerical modelling approach to coastal evolution was developed. This method was used to predict over 20 years of coastal evolution in Inner Dingle Bay. On a broader context this thesis utilised several experimental coastal zone data collection and analysis methods such as ocean radar and grain size trend analysis. These were applied during the study and their suitability to a dynamic coastal system was assessed.
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In this paper, dynamic simulation was used to compare the energy performance of three innovativeHVAC systems: (A) mechanical ventilation with heat recovery (MVHR) and micro heat pump, (B) exhaustventilation with exhaust air-to-water heat pump and ventilation radiators, and (C) exhaust ventilationwith air-to-water heat pump and ventilation radiators, to a reference system: (D) exhaust ventilation withair-to-water heat pump and panel radiators. System A was modelled in MATLAB Simulink and systems Band C in TRNSYS 17. The reference system was modelled in both tools, for comparison between the two.All systems were tested with a model of a renovated single family house for varying U-values, climates,infiltration and ventilation rates.It was found that A was the best system for lower heating demand, while for higher heating demandsystem B would be preferable. System C was better than the reference system, but not as good as A or B.The difference in energy consumption of the reference system was less than 2 kWh/(m2a) betweenSimulink and TRNSYS. This could be explained by the different ways of handling solar gains, but also bythe fact that the TRNSYS systems supplied slightly more than the ideal heating demand.
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Metadata that is associated with either an information system or an information object for purposes of description, administration, legal requirements, technical functionality, use and usage, and preservation, plays a critical role in ensuring the creation, management, preservation and use and re-use of trustworthymaterials, including records. Recordkeeping1 metadata, of which one key type is archival description, plays a particularly important role in documenting the reliability and authenticity of records and recordkeeping systemsas well as the various contexts (legal-administrative, provenancial, procedural, documentary, and technical) within which records are created and kept as they move across space and time. In the digital environment, metadata is also the means by which it is possible to identify how record components – those constituent aspects of a digital record that may be managed, stored and used separately by the creator or the preserver – can be reassembled to generate an authentic copy of a record or reformulated per a user’s request as a customized output package.Issues relating to the creation, capture, management and preservation of adequate metadata are, therefore, integral to any research study addressing the reliability and authenticity of digital entities, regardless of the community, sector or institution within which they are being created. The InterPARES 2 Description Cross-Domain Group (DCD) examined the conceptualization, definitions, roles, and current functionality of metadata and archival description in terms of requirements generated by InterPARES 12. Because of the needs to communicate the work of InterPARES in a meaningful way across not only other disciplines, but also different archival traditions; to interface with, evaluate and inform existing standards, practices and other research projects; and to ensure interoperability across the three focus areas of InterPARES2, the Description Cross-Domain also addressed its research goals with reference to wider thinking about and developments in recordkeeping and metadata. InterPARES2 addressed not only records, however, but a range of digital information objects (referred to as “entities” by InterPARES 2, but not to be confused with the term “entities” as used in metadata and database applications) that are the products and by-products of government, scientific and artistic activities that are carried out using dynamic, interactive or experiential digital systems. The nature of these entities was determined through a diplomatic analysis undertaken as part of extensive case studies of digital systems that were conducted by the InterPARES 2 Focus Groups. This diplomatic analysis established whether the entities identified during the case studies were records, non-records that nevertheless raised important concerns relating to reliability and authenticity, or “potential records.” To be determined to be records, the entities had to meet the criteria outlined by archival theory – they had to have a fixed documentary format and stable content. It was not sufficient that they be considered to be or treated as records by the creator. “Potential records” is a new construct that indicates that a digital system has the potential to create records upon demand, but does not actually fix and set aside records in the normal course of business. The work of the Description Cross-Domain Group, therefore, addresses the metadata needs for all three categories of entities.Finally, since “metadata” as a term is used today so ubiquitously and in so many different ways by different communities, that it is in peril of losing any specificity, part of the work of the DCD sought to name and type categories of metadata. It also addressed incentives for creators to generate appropriate metadata, as well as issues associated with the retention, maintenance and eventual disposition of the metadata that aggregates around digital entities over time.
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This paper is on a wind energy conversion system simulation of a transient analysis due to a blade pitch control malfunction. The aim of the transient analysis is the study of the behavior of a back-to-back multiple point clamped five-level full-power converter implemented in a wind energy conversion system equipped with a permanent magnet synchronous generator. An alternate current link connects the system to the grid. The drive train is modeled by a three-mass model in order to simulate the dynamic effect of the wind on the tower. The control strategy is based on fractional-order control. Unbalance voltages in the DC-link capacitors are lessen due to the control strategy, balancing the capacitor banks voltages by a selection of the output voltage vectors. Simulation studies are carried out to evaluate not only the system behavior, but also the quality of the energy injected into the electric grid.
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An integrated mathematical model for the simulation of an offshore wind system performance is presented in this paper. The mathematical model considers an offshore variable-speed turbine in deep water equipped with a permanent magnet synchronous generator using multiple point full-power clamped three-level converter, converting the energy of a variable frequency source in injected energy into the electric network with constant frequency, through a HVDC transmission submarine cable. The mathematical model for the drive train is a concentrate two mass model which incorporates the dynamic for the blades of the wind turbine, tower and generator due to the need to emulate the effects of the wind and the floating motion. Controller strategy considered is a proportional integral one. Also, pulse width modulation using space vector modulation supplemented with sliding mode is used for trigger the transistors of the converter. Finally, a case study is presented to access the system performance.