871 resultados para Dynamic Model Averaging
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The difference between the rate of change of cerebral blood volume (CBV) and cerebral blood flow (CBF) following stimulation is thought to be due to circumferential stress relaxation in veins (Mandeville, J.B., Marota, J.J.A., Ayata, C., Zaharchuk, G., Moskowitz, M.A., Rosen, B.R., Weisskoff, R.M., 1999. Evidence of a cerebrovascular postarteriole windkessel with delayed compliance. J. Cereb. Blood Flow Metab. 19, 679–689). In this paper we explore the visco-elastic properties of blood vessels, and present a dynamic model relating changes in CBF to changes in CBV. We refer to this model as the visco-elastic windkessel (VW) model. A novel feature of this model is that the parameter characterising the pressure–volume relationship of blood vessels is treated as a state variable dependent on the rate of change of CBV, producing hysteresis in the pressure–volume space during vessel dilation and contraction. The VW model is nonlinear time-invariant, and is able to predict the observed differences between the time series of CBV and that of CBF measurements following changes in neural activity. Like the windkessel model derived by Mandeville, J.B., Marota, J.J.A., Ayata, C., Zaharchuk, G., Moskowitz, M.A., Rosen, B.R., Weisskoff, R.M., 1999. Evidence of a cerebrovascular postarteriole windkessel with delayed compliance. J. Cereb. Blood Flow Metab. 19, 679–689, the VW model is primarily a model of haemodynamic changes in the venous compartment. The VW model is demonstrated to have the following characteristics typical of visco-elastic materials: (1) hysteresis, (2) creep, and (3) stress relaxation, hence it provides a unified model of the visco-elastic properties of the vasculature. The model will not only contribute to the interpretation of the Blood Oxygen Level Dependent (BOLD) signals from functional Magnetic Resonance Imaging (fMRI) experiments, but also find applications in the study and modelling of the brain vasculature and the haemodynamics of circulatory and cardiovascular systems.
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Models for water transfer in the crop-soil system are key components of agro-hydrological models for irrigation, fertilizer and pesticide practices. Many of the hydrological models for water transfer in the crop-soil system are either too approximate due to oversimplified algorithms or employ complex numerical schemes. In this paper we developed a simple and sufficiently accurate algorithm which can be easily adopted in agro-hydrological models for the simulation of water dynamics. We used a dual crop coefficient approach proposed by the FAO for estimating potential evaporation and transpiration, and a dynamic model for calculating relative root length distribution on a daily basis. In a small time step of 0.001 d, we implemented algorithms separately for actual evaporation, root water uptake and soil water content redistribution by decoupling these processes. The Richards equation describing soil water movement was solved using an integration strategy over the soil layers instead of complex numerical schemes. This drastically simplified the procedures of modeling soil water and led to much shorter computer codes. The validity of the proposed model was tested against data from field experiments on two contrasting soils cropped with wheat. Good agreement was achieved between measurement and simulation of soil water content in various depths collected at intervals during crop growth. This indicates that the model is satisfactory in simulating water transfer in the crop-soil system, and therefore can reliably be adopted in agro-hydrological models. Finally we demonstrated how the developed model could be used to study the effect of changes in the environment such as lowering the groundwater table caused by the construction of a motorway on crop transpiration. (c) 2009 Elsevier B.V. All rights reserved.
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This paper presents an in-depth critical discussion and derivation of a detailed small-signal analysis of the Phase-Shifted Full-Bridge (PSFB) converter. Circuit parasitics, resonant inductance and transformer turns ratio have all been taken into account in the evaluation of this topology’s open-loop control-to-output, line-to-output and load-to-output transfer functions. Accordingly, the significant impact of losses and resonant inductance on the converter’s transfer functions is highlighted. The enhanced dynamic model proposed in this paper enables the correct design of the converter compensator, including the effect of parasitics on the dynamic behavior of the PSFB converter. Detailed experimental results for a real-life 36V-to-14V/10A PSFB industrial application show excellent agreement with the predictions from the model proposed herein.1
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We study a dynamic model of coordination with timing frictions and payoff heterogeneity. There is a unique equilibrium, characterized by thresholds that determine the choices of each type of agent. We characterize equilibrium for the limiting cases of vanishing timing frictions and vanishing shocks to fundamentals. A lot of conformity emerges: despite payoff heterogeneity, agents’ equilibrium thresholds partially coincide as long as there exists a set of beliefs that would make this coincidence possible – though they never fully coincide. In case of vanishing frictions, the economy behaves almost as if all agents were equal to an average type. Conformity is not inefficient. The efficient solution would have agents following others even more often and giving less importance to the fundamental
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In this paper a model, called ELLOBO running in STELLA II, was set to describe the plankton system of the Broa reservoir (SP). The three state variables of the model are: phytoplankton, zooplankton, and the fish Astyanax fasciatus. The forcing variables are: temperature, nitrate, phosphorus and solar radiation. The model did not consider the cycling of nutrients inside the reservoir. The results show that: temperature is the principal forcing variable in the phytoplankton dynamic and in the subsequent evolution of the whole system. The zooplankton predation was described by Odum's equation, and there is a strong random component in zooplankton grazing, which was essential for the model, because zooplankton estimates have high variance. One must collect data in a short space of time (maybe daily) to better explain the zooplankton and phytoplankton variation. Validation was performed using simple statistics (arithmetic mean, standard deviation) and the results show concordance between observed and simulated values. Overhead was used to calibrate some parameters and to validate the model. The highest overhead value (5%) imply in the better accordance between estimated and;observed state variables values. We believe this approach in Broa reservoir will provide an useful tool for future research and it could be used comparatively in other continental aquatic ecosystems. (C) 2000 Elsevier B.V. B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This work focuses on the dynamic modeling of a flexible robotic manipulator with two flexible links and two revolute joints, which rotates in the horizontal plane. The dynamic equations are derived using the Newton-Euler formulation and the finite element method, based on elementary beam theory. Computer simulation results are presented to illustrate this study. The dynamic model becomes necessary for use in future design and control applications.
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We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.
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We consider a generalized two-species population dynamic model and analytically solve it for the amensalism and commensalism ecological interactions. These two-species models can be simplified to a one-species model with a time dependent extrinsic growth factor. With a one-species model with an effective carrying capacity one is able to retrieve the steady state solutions of the previous one-species model. The equivalence obtained between the effective carrying capacity and the extrinsic growth factor is complete only for a particular case, the Gompertz model. Here we unveil important aspects of sigmoid growth curves, which are relevant to growth processes and population dynamics. (C) 2011 Elsevier B.V. All rights reserved.
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Parallel kinematic structures are considered very adequate architectures for positioning and orienti ng the tools of robotic mechanisms. However, developing dynamic models for this kind of systems is sometimes a difficult task. In fact, the direct application of traditional methods of robotics, for modelling and analysing such systems, usually does not lead to efficient and systematic algorithms. This work addre sses this issue: to present a modular approach to generate the dynamic model and through some convenient modifications, how we can make these methods more applicable to parallel structures as well. Kane’s formulati on to obtain the dynamic equations is shown to be one of the easiest ways to deal with redundant coordinates and kinematic constraints, so that a suitable c hoice of a set of coordinates allows the remaining of the modelling procedure to be computer aided. The advantages of this approach are discussed in the modelling of a 3-dof parallel asymmetric mechanisms.
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[EN]Ensemble forecasting [1] is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in [2]. The wind _eld forecasting is based on a mass-consistent model and a log-linear wind pro_le using as input data the resulting forecast wind from Harmonie [3], a Non-Hydrostatic Dynamic model. The mass-consistent model parameters are estimated by using genetic algorithms [4]. The mesh is generated using the meccano method [5] and adapted to the geometry. The main source of uncertainties in this model is the parameter estimation and the in- trinsic uncertainties of the Harmonie Model…
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[EN]Ensemble forecasting is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in. The wind field forecasting is based on a mass-consistent model and a log-linear wind profile using as input data the resulting forecast wind from Harmonie, a Non-Hydrostatic Dynamic model used experimentally at AEMET with promising results. The mass-consistent model parameters are estimated by using genetic algorithms. The mesh is generated using the meccano method and adapted to the geometry…
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The research is aimed at contributing to the identification of reliable fully predictive Computational Fluid Dynamics (CFD) methods for the numerical simulation of equipment typically adopted in the chemical and process industries. The apparatuses selected for the investigation, specifically membrane modules, stirred vessels and fluidized beds, were characterized by a different and often complex fluid dynamic behaviour and in some cases the momentum transfer phenomena were coupled with mass transfer or multiphase interactions. Firs of all, a novel modelling approach based on CFD for the prediction of the gas separation process in membrane modules for hydrogen purification is developed. The reliability of the gas velocity field calculated numerically is assessed by comparison of the predictions with experimental velocity data collected by Particle Image Velocimetry, while the applicability of the model to properly predict the separation process under a wide range of operating conditions is assessed through a strict comparison with permeation experimental data. Then, the effect of numerical issues on the RANS-based predictions of single phase stirred tanks is analysed. The homogenisation process of a scalar tracer is also investigated and simulation results are compared to original passive tracer homogenisation curves determined with Planar Laser Induced Fluorescence. The capability of a CFD approach based on the solution of RANS equations is also investigated for describing the fluid dynamic characteristics of the dispersion of organics in water. Finally, an Eulerian-Eulerian fluid-dynamic model is used to simulate mono-disperse suspensions of Geldart A Group particles fluidized by a Newtonian incompressible fluid as well as binary segregating fluidized beds of particles differing in size and density. The results obtained under a number of different operating conditions are compared with literature experimental data and the effect of numerical uncertainties on axial segregation is also discussed.
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This dissertation consists of three self-contained papers that are related to two main topics. In particular, the first and third studies focus on labor market modeling, whereas the second essay presents a dynamic international trade setup.rnrnIn Chapter "Expenses on Labor Market Reforms during Transitional Dynamics", we investigate the arising costs of a potential labor market reform from a government point of view. To analyze various effects of unemployment benefits system changes, this chapter develops a dynamic model with heterogeneous employed and unemployed workers.rn rnIn Chapter "Endogenous Markup Distributions", we study how markup distributions adjust when a closed economy opens up. In order to perform this analysis, we first present a closed-economy general-equilibrium industry dynamics model, where firms enter and exit markets, and then extend our analysis to the open-economy case.rn rnIn Chapter "Unemployment in the OECD - Pure Chance or Institutions?", we examine effects of aggregate shocks on the distribution of the unemployment rates in OECD member countries.rn rnIn all three chapters we model systems that behave randomly and operate on stochastic processes. We therefore exploit stochastic calculus that establishes clear methodological links between the chapters.