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A magnetostrictive nozzle-flapper servovalve pilot stage is presented in this article, which is directly driven by a giant magnetostrictive actuator and features three nozzles for the development of large flow rate servovalve. Acc...
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A magnetostrictive nozzle-flapper servovalve pilot stage is presented in this article, which is directly driven by a giant magnetostrictive actuator and features three nozzles for the development of large flow rate servovalve. According to the energy conversion sequence in this servovalve, a giant magnetostrictive actuator magnetization model, a giant magnetostrictive material rod eddy loss model and a servovalve dynamic pressure model are all established to enable quantitative depiction and modelling of the dynamic pressure response process of magnetostrictive nozzle-flapper servovalve pilot stage. Consequently, the matched simulation model of the magnetostrictive nozzle-flapper servovalve pilot stage with the mathematic model is followed to be established, and two unknown parameters of complex permeability are determined using the test data from the giant magnetostrictive actuator. By running this simulation model, flapper displacement and output pressure under different structural parameters and variational excited frequencies are determined, certain parameters that are sensitive to the dynamic characteristics of magnetostrictive nozzle-flapper servovalve pilot stage driven by giant magnetostrictive actuator are found and the accompanying rules are revealed. Finally, the experimental system of a magnetostrictive nozzle-flapper servovalve pilot stage driven by giant magnetostrictive actuator was built; both the step-input voltage response curve and the sine-input voltage response curve were captured; and these curves show that the amplitude bandwidth (-3dB) and the phase bandwidth (-90 degrees) of a magnetostrictive nozzle-flapper servovalve pilot stage can approach 150 and 110Hz, respectively, which exhibit good agreement with the simulation results. Therefore, the magnetostrictive nozzle-flapper servovalve pilot stage offers a very promising prospect of the novel servovalves with the high-frequency response and the large flow rate.
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A method for calculating the power demand of the hoist motor in rubber-tired gantry (RTG) cranes with nonparallel cables has been developed to measure the energy consumption in a typical lift cycle. From measurements taken at the...
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A method for calculating the power demand of the hoist motor in rubber-tired gantry (RTG) cranes with nonparallel cables has been developed to measure the energy consumption in a typical lift cycle. From measurements taken at the Port of Felixstowe, it has been observed that the peculiar geometrical characteristics of the hoisting mechanism cause the power demand to increase with the container height in constant rotor speed conditions. The change in the angle of the hoisting ropes causes an increase in torque load and power consumption. By using information extracted from the crane’s geometry, it has been possible to calculate the potential energy increase given the weight and vertical position of the container. The load torque on the hoist motor and the vertical speed of the mass have also been calculated, allowing for the modeling of the hoist motor power consumption when lifting containers with constant rotational speed. The proposed model has been compared to a constant power demand approximation, showing a higher accuracy for masses below 40 t.
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This article surveys empirical research that reveals the variety and diversity of the forms and purposes of causal reasoning, and reveals the myths that have driven philosophical analysis, psychological research, and computational...
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This article surveys empirical research that reveals the variety and diversity of the forms and purposes of causal reasoning, and reveals the myths that have driven philosophical analysis, psychological research, and computational approaches. The intent of the essay is to broaden the horizons for the development of intelligent systems that serve explanatory functions.
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The EU dependence on imported gas is increasing, rising to 67% in the year 2014 with 30% of total gas consumption used for electricity generation that year. With such a dependence on imported gas, gas supply interruptions can have...
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The EU dependence on imported gas is increasing, rising to 67% in the year 2014 with 30% of total gas consumption used for electricity generation that year. With such a dependence on imported gas, gas supply interruptions can have significant impacts on the EU energy system and economy. This points to the need for integrated electricity and gas modelling tools to fully explore the potential impacts of gas supply interruptions. This paper builds and applies a detailed publically available integrated electricity and gas model for the EU-28. We use this model to examine a number of hypothetical scenarios where gas supply routes are interrupted for yearly periods and the impacts on power system operation and gas flow in Europe observed. Model results show that interruption of Russian gas supply to the EU could lead to a rise in average gas prices of 28% and 12% in electricity prices. When supply from North Africa was removed all Southern European states were affected heavily, Spain in particular saw large increases of 30% in gas prices with a corresponding rise of 18% in electricity prices as a result. In addition to supply interruptions, all gas storages were removed from the model to examine the importance of gas storage infrastructure. This resulted in an average increase in power prices of 6% across Europe. These additional insights offer an increased understanding of the interplay between the gas and power systems and identify challenges which may arise when seeking to understand energy systems as a whole. (C) 2017 Elsevier Ltd. All rights reserved.
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High-quality models are essential to the performance of many control-related tasks [1]-[3]. If the structure of the system is known, first principle models can be created (which constitutes the best choice for most uses), especial...
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High-quality models are essential to the performance of many control-related tasks [1]-[3]. If the structure of the system is known, first principle models can be created (which constitutes the best choice for most uses), especially if they should be used as design tools for parametric studies without having to build the corresponding hardware. However, first principle modeling is hardly possible for many real systems, either because the detailed knowledge of the system structure is not available or the model would be too complex to be useful for control design or to be parameterized. It has become common to use data-driven models, that is, correctly reproducing the input-output behavior of the system without trying to correctly describe its physics. For linear systems, data-driven modeling has been intensively studied, and powerful tools exist [4].
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Complex systems modelling is characterized by the often painful decision regarding to what extent abstraction an be carried on without loss or distortion of the facts due to oversimplification. This article looks at a dynamic syst...
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Complex systems modelling is characterized by the often painful decision regarding to what extent abstraction an be carried on without loss or distortion of the facts due to oversimplification. This article looks at a dynamic systems modelling approach that Allows incorporating high and low levels of detail, while maintaining Intact the overall behaviour of the system. Although this infringes On the paradigms of systems theory, it is an effective tool provided Some guidelines are observed. Although the approach appears Intuitive and is perhaps not entirely new, it has not received the Formal status of a modelling technique because it is difficult to Formalize. This work draws attention to it by its constraints rather Than by its novelty. It is illustrated through the case study of an Economic system in a systematic cause-effect approach. The model Uses control systems techniques and agents that interact with each Other.
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The development of contemporary systems is an extremely complex process. One approach to modeling system behavior uses activity diagrams from Unified Modeling Language (UML)/System Modeling Language (SysML), providing a standard o...
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The development of contemporary systems is an extremely complex process. One approach to modeling system behavior uses activity diagrams from Unified Modeling Language (UML)/System Modeling Language (SysML), providing a standard object-oriented graphical notation and enhancing reusability. However, UML/SysML activity diagrams do not directly support the kind of analysis needed to verify the system behavior, such as might be available with a Petri net (PN) model. We show that a behavior model represented by a set of fUML-compliant modeling elements in UML/SysML activity diagrams can be transformed into an equivalent PN, so that the analysis capability of PN can be applied. We define a formal mathematical notation for a set of modeling elements in activity diagrams, show the mapping rules between PN and activity diagrams, and propose a formal transformation algorithm. Two example system behavior models represented by UML/SysML activity diagrams are used for illustration.
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Obesity is a complex system problem involving a broad spectrum of policy, social, economic, cultural, environmental, behavioural, and biological factors and the complex interrelated, cross-sector, non-linear, dynamic relationships...
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Obesity is a complex system problem involving a broad spectrum of policy, social, economic, cultural, environmental, behavioural, and biological factors and the complex interrelated, cross-sector, non-linear, dynamic relationships among them. Systems modelling is an innovative approach with the potential for advancing obesity research. This study examined the applications of systems modelling in obesity research published between 2000 and 2017, examined how the systems models were developed and used in obesity studies and discussed related gaps in current research. We focused on the applications of two main systems modelling approaches: system dynamics modelling and agent-based modelling. The past two decades have seen a growing body of systems modelling in obesity research. The research topics ranged from micro-level to macro-level energy-balance-related behaviours and policies (19 studies), population dynamics (five studies), policy effect simulations (eight studies), environmental (10 studies) and social influences (15 studies) and their effects on obesity rates. Overall, systems analysis in public health research is still in its early stages, with limitations linked to model validity, mixed findings and its actual use in guiding interventions. Challenges in theory and modelling practices need to be addressed to realize the full potential of systems modelling in future obesity research and interventions.
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The Gaussian-process (GP) model is an example of a probabilistic, nonparametric model with uncertainty predictions. It can be used for the modelling of complex nonlinear systems arid also for dynamic systems identification. The ou...
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The Gaussian-process (GP) model is an example of a probabilistic, nonparametric model with uncertainty predictions. It can be used for the modelling of complex nonlinear systems arid also for dynamic systems identification. The output of the GP model is a normal distribution, expressed in terms of the mean and variance. At present it is applied mostly for the modelling of dynamic systems with one output. A possible channel structure for multiple-input multiple-output model and a case study for the modelling of a system with more than one output, namely a gas-liquid separator, is given in this paper.
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In recent years, simulation, design and control of systems with parametric uncertainties for the entire range of operation gained much importance. This paper presents a new method for reducing order of Large Scale Interval systems...
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In recent years, simulation, design and control of systems with parametric uncertainties for the entire range of operation gained much importance. This paper presents a new method for reducing order of Large Scale Interval systems. The proposed method involves simple computations, and is efficient as it needs the formulation of only one Routh type tabulation, avoiding the necessity of formulating two tables viz., γ and δ tables, and avoids the computation of time moments of the original high order Interval system beforehand, unlike other available methods. The proposed Simplified Routh Approximation method (SRAM) always generates stable reduced order Interval systems, retaining the initial time moments of the original high order system. The proposed simplified method is extended for the reduction of high order Muitivariable and Discrete Interval systems to overcome the limitations and drawbacks of some of the existing methods in literature. Typical numerical examples are considered to illustrate the flexibility and effectiveness of the proposed method.
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