977 resultados para Simulation platform
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Is numerical mimicry a third way of establishing truth? Kevin Heng received his M.S. and Ph.D. in astrophysics from the Joint Institute for Laboratory Astrophysics (JILA) and the University of Colorado at Boulder. He joined the Institute for Advanced Study in Princeton from 2007 to 2010, first as a Member and later as the Frank & Peggy Taplin Member. From 2010 to 2012 he was a Zwicky Prize Fellow at ETH Z¨urich (the Swiss Federal Institute of Technology). In 2013, he joined the Center for Space and Habitability (CSH) at the University of Bern, Switzerland, as a tenure-track assistant professor, where he leads the Exoplanets and Exoclimes Group. He has worked on, and maintains, a broad range of interests in astrophysics: shocks, extrasolar asteroid belts, planet formation, fluid dynamics, brown dwarfs and exoplanets. He coordinates the Exoclimes Simulation Platform (ESP), an open-source set of theoretical tools designed for studying the basic physics and chemistry of exoplanetary atmospheres and climates (www.exoclime.org). He is involved in the CHEOPS (Characterizing Exoplanet Satellite) space telescope, a mission approved by the European Space Agency (ESA) and led by Switzerland. He spends a fair amount of time humbly learning the lessons gleaned from studying the Earth and Solar System planets, as related to him by atmospheric, climate and planetary scientists. He received a Sigma Xi Grant-in-Aid of Research in 2006
Plataforma de simulación en Matlab-Simulink de un accionamiento regulado para emular aerogeneradores
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En este proyecto se desarrolla un modelo de simulación de un accionamiento controlado que emula el comportamiento de una turbina eólica, el cual se ha llevado a cabo a través del programa para simulación Matlab/Simulink. Su desarrollo se ha estructurado de la siguiente forma: Tras una breve introducción a la energía eólica y a las máquinas eléctricas objeto de estudio en este proyecto, se procede a la caracterización y representación de dichas maquinas dentro de la plataforma de simulación virtual Simulink. Posteriormente se explican posibles estrategias de control de la máquina de inducción, las cuales son aplicadas para la realización de un control de velocidad. Asimismo, se realiza un control vectorial de par de la máquina de inducción de modo que permita un seguimiento efectivo del par de referencia demandado por el usuario, ante distintas condiciones. Finalmente, se añade el modelo de turbina eólica de manera que, definiendo los valores de velocidad de viento, ángulo de paso y velocidad del eje, permite evaluar el par mecánico desarrollado por la turbina. Este modelo se valida comprobando su funcionamiento para diferentes puntos de operación ante diversas condiciones del par de carga. Las condiciones de carga se establecen acoplando al modelo de la turbina, un generador síncrono de imanes permanentes conectado a una carga resistiva. ! II! ABSTRACT In this project, the simulation model of a controlled drive that emulates the behaviour of a wind turbine is developed. It has been carried out through the platform for multidomian simulation called Matlab/Simulink. Its development has been structured as follows: After a brief introduction to the wind energy and the electrical machines studied in this project, these machines are characterized and represented into the virtual simulation platform, Simulink. Subsequently, the possible control strategies for the induction machine are explained and applied in order to carry out a speed control. Additionally, a torque vector control of the induction machine is performed, so as to enable an effective monitoring of the reference torque requested by the user, under different conditions. Finally, the wind turbine model is implemented so as to assess the turbine mechanical torque, after defining the wind speed, the pitch angle and the shaft speed values. This model is validated by testing its functionality for different operating points under various load torques. The load conditions are set up by attaching a permanent magnets synchronous machine, with a resistive load, to the turbine model.
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The objective of the thesis was to analyse several process configurations for the production of electricity from biomass. Process simulation models using AspenPlus aimed at calculating the industrial performance of power plant concepts were built, tested, and used for analysis. The criteria used in analysis were performance and cost. All of the advanced systems appear to have higher efficiencies than the commercial reference, the Rankine cycle. However, advanced systems typically have a higher cost of electricity (COE) than the Rankine power plant. High efficiencies do not reduce fuel costs enough to compensate for the high capital costs of advanced concepts. The successful reduction of capital costs would appear to be the key to the introduction of the new systems. Capital costs account for a considerable, often dominant, part of the cost of electricity in these concepts. All of the systems have higher specific investment costs than the conventional industrial alternative, i.e. the Rankine power plant; Combined beat and power production (CUP) is currently the only industrial area of application in which bio-power costs can be considerably reduced to make them competitive. Based on the results of this work, AsperiPlus is an appropriate simulation platform. How-ever, the usefulness of the models could be improved if a number of unit operations were modelled in greater detail. The dryer, gasifier, fast pyrolysis, gas engine and gas turbine models could be improved.
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The paper presents the simulation of the pyrolysis vapors condensation process using an Eulerian approach. The condensable volatiles produced by the fast pyrolysis of biomass in a 100 g/h bubbling fluidized bed reactor are condensed in a water cooled condenser. The vapors enter the condenser at 500 °C, and the water temperature is 15 °C. The properties of the vapor phase are calculated according to the mole fraction of its individual compounds. The saturated vapor pressure is calculated for the vapor mixture using a corresponding states correlation and assuming that the mixture of the condensable compounds behave as a pure fluid. Fluent 6.3 has been used as the simulation platform, while the condensation model has been incorporated to the main code using an external user defined function. © 2011 American Chemical Society.
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People with foot problems need special healthcare: foot care. Customized insoles can provide this care. They are inserts that are placed in the shoes. They correct biomechanical and postural inaccuracies in foot. Insole production contains four phases: foot image scanning, image validation, insole design and insole manufacturing. Currently, image scanning and validation is separated in location and time, i.e. podiatrists take images and insole designers validate them at different location and at different time. A cloud-based solution, the CloudSME one-stop shop simulation platform, enables remote access to image validation and insole design service deployed and running on the Cloud. The remote access allows podiatrists validating scanned image while the patient is in their offices. The simulation platform also supports remote design of customized insoles.
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The European CloudSME project that incorporated 24 European SMEs, besides five academic partners, has finished its funded phase in March 2016. This presentation will provide a summary of the results of the project, and will analyze the challenges and differences when developing “SME Gateways”, when compared to “Science Gateways”. CloudSME started in 2013 with the aim to develop a cloud-based simulation platform for manufacturing and engineering SMEs. The project was based around industry use-cases, five of which were incorporated in the project from the start, and seven additional ones that were added as an outcome of an open call in January 2015. CloudSME utilized science gateway related technologies, such as the commercial CloudBroker Platform and the WS-PGRADE/gUSE Gateway Framework that were developed in the preceding SCI-BUS project. As most important outcome, the project successfully implemented 12 industry quality demonstrators that showcase how SMEs in the manufacturing and engineering sector can utilize cloud-based simulation services. Some of these solutions are already market-ready and currently being rolled out by the software vendor companies. Some others require further fine-tuning and the implementation of commercial interfaces before being put into the market. The CloudSME use-cases came from a very wide application spectrum. The project implemented, for example, an open marketplace for micro-breweries to optimize their production and distribution processes, an insole design validation service to be used by podiatrists and shoe manufacturers, a generic stock management solution for manufacturing SMEs, and also several “classical” high-performance computing case-studies, such as fluid dynamics simulations for model helicopter design, and dual-fuel internal combustion engine simulation. As the project generated significant impact and interest in the manufacturing sector, 10 CloudSME stakeholders established a follow-up company called CloudSME UG for the future commercialization of the results. Besides the success stories, this talk would also like to highlight the difficulties when transferring the outcomes of an academic research project to real commercial applications. The different mindset and approach of academic and industry partners presented a real challenge for the CloudSME project, with some interesting and valuable lessons learnt. The academic way of supporting SMEs did not always work well with the rather different working practices and culture of many participants. Also, the quality of support regarding operational solutions required by the SMEs is well beyond the typical support services academic institutions are prepared for. Finally, a clear lack of trust in academic solutions when compared to commercial solutions was also imminent. The talk will highlight some of these challenges underpinned by the implementation of the CloudSME use-cases.
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Scientific workflows orchestrate the execution of complex experiments frequently using distributed computing platforms. Meta-workflows represent an emerging type of such workflows which aim to reuse existing workflows from potentially different workflow systems to achieve more complex and experimentation minimizing workflow design and testing efforts. Workflow interoperability plays a profound role in achieving this objective. This paper is focused at fostering interoperability across meta-workflows that combine workflows of different workflow systems from diverse scientific domains. This is achieved by formalizing definitions of meta-workflow and its different types to standardize their data structures used to describe workflows to be published and shared via public repositories. The paper also includes thorough formalization of two workflow interoperability approaches based on this formal description: the coarse-grained and fine-grained workflow interoperability approach. The paper presents a case study from Astrophysics which successfully demonstrates the use of the concepts of meta-workflows and workflow interoperability within a scientific simulation platform.
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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Eletrotécnica Ramo de Automação e Eletrónica Industrial
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Model predictive control (MPC) has often been referred to in literature as a potential method for more efficient control of building heating systems. Though a significant performance improvement can be achieved with an MPC strategy, the complexity introduced to the commissioning of the system is often prohibitive. Models are required which can capture the thermodynamic properties of the building with sufficient accuracy for meaningful predictions to be made. Furthermore, a large number of tuning weights may need to be determined to achieve a desired performance. For MPC to become a practicable alternative, these issues must be addressed. Acknowledging the impact of the external environment as well as the interaction of occupants on the thermal behaviour of the building, in this work, techniques have been developed for deriving building models from data in which large, unmeasured disturbances are present. A spatio-temporal filtering process was introduced to determine estimates of the disturbances from measured data, which were then incorporated with metaheuristic search techniques to derive high-order simulation models, capable of replicating the thermal dynamics of a building. While a high-order simulation model allowed for control strategies to be analysed and compared, low-order models were required for use within the MPC strategy itself. The disturbance estimation techniques were adapted for use with system-identification methods to derive such models. MPC formulations were then derived to enable a more straightforward commissioning process and implemented in a validated simulation platform. A prioritised-objective strategy was developed which allowed for the tuning parameters typically associated with an MPC cost function to be omitted from the formulation by separation of the conflicting requirements of comfort satisfaction and energy reduction within a lexicographic framework. The improved ability of the formulation to be set-up and reconfigured in faulted conditions was shown.
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This paper presents real-time simulation models of electrical machines on FPGA platform. Implementation of the real-time numerical integration methods with digital logic elements is discussed. Several numerical integrations are presented. A real-time simulation of DC machine is carried out on this FPGA platform and important transient results are presented. These results are compared to simulation results obtained through a commercial off-line simulation software.
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This paper presents real-time simulation models of electrical machines on FPGA platform. Implementation of the real-time numerical integration methods with digital logic elements is discussed. Several numerical integrations are presented. A real-time simulation of DC machine is carried out on this FPGA platform and important transient results are presented. These results are compared to simulation results obtained through a commercial off-line simulation software