102 resultados para Model for bringing into play
Resumo:
In this work we study an agent based model to investigate the role of asymmetric information degrees for market evolution. This model is quite simple and may be treated analytically since the consumers evaluate the quality of a certain good taking into account only the quality of the last good purchased plus her perceptive capacity beta. As a consequence, the system evolves according to a stationary Markov chain. The value of a good offered by the firms increases along with quality according to an exponent alpha, which is a measure of the technology. It incorporates all the technological capacity of the production systems such as education, scientific development and techniques that change the productivity rates. The technological level plays an important role to explain how the asymmetry of information may affect the market evolution in this model. We observe that, for high technological levels, the market can detect adverse selection. The model allows us to compute the maximum asymmetric information degree before the market collapses. Below this critical point the market evolves during a limited period of time and then dies out completely. When beta is closer to 1 (symmetric information), the market becomes more profitable for high quality goods, although high and low quality markets coexist. The maximum asymmetric information level is a consequence of an ergodicity breakdown in the process of quality evaluation. (C) 2011 Elsevier B.V. All rights reserved.
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This paper discusses the integrated design of parallel manipulators, which exhibit varying dynamics. This characteristic affects the machine stability and performance. The design methodology consists of four main steps: (i) the system modeling using flexible multibody technique, (ii) the synthesis of reduced-order models suitable for control design, (iii) the systematic flexible model-based input signal design, and (iv) the evaluation of some possible machine designs. The novelty in this methodology is to take structural flexibilities into consideration during the input signal design; therefore, enhancing the standard design process which mainly considers rigid bodies dynamics. The potential of the proposed strategy is exploited for the design evaluation of a two degree-of-freedom high-speed parallel manipulator. The results are experimentally validated. (C) 2010 Elsevier Ltd. All rights reserved.
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A nonlinear finite element model was developed to simulate the nonlinear response of three-leaf masonry specimens, which were subjected to laboratory tests with the aim of investigating the mechanical behaviour of multiple-leaf stone masonry walls up to failure. The specimens consisted of two external leaves made of stone bricks and mortar joints, and an internal leaf in mortar and stone aggregate. Different loading conditions, typologies of the collar joints, and stone types were taken into account. The constitutive law implemented in the model is characterized by a damage tensor, which allows the damage-induced anisotropy accompanying the cracking process to be described. To follow the post-peak behaviour of the specimens with sufficient accuracy it was necessary to make the damage model non-local, to avoid mesh-dependency effects related to the strain-softening behaviour of the material. Comparisons between the predicted and measured failure loads are quite satisfactory in most of the studied cases. (c) 2007 Elsevier Ltd. All rights reserved.
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This paper presents some improvements in the model proposed by Machado et al. [Machado SL, Carvalho MF, Vilar OM. Constitutive model for municipal solid waste. J Geotech Geoenviron Eng ASCE 2002; 128(11):940-51] now considering the influence of biodegradation of organic matter in the mechanical behavior of municipal solid waste. The original framework considers waste as composed of two component groups; fibers and organic paste. The particular laws of behavior are assessed for each component group and then coupled to represent waste behavior. The improvements introduced in this paper take into account the changes in the properties of fibers and mass loss due to organic matter depletion over time. Mass loss is indirectly calculated considering the MSW gas generation potential through a first order decay model. It is shown that as the biodegradation process occurs the proportion of fibers increases, however, they also undergo a degradation process which tends to reduce their ultimate tensile stress and Young modulus. The way these changes influence the behavior of MSW is incorporated in the final framework which captures the main features of the MSW stress-strain behavior under different loading conditions. (C) 2007 Elsevier Ltd. All rights reserved.
Resumo:
Converting aeroelastic vibrations into electricity for low power generation has received growing attention over the past few years. In addition to potential applications for aerospace structures, the goal is to develop alternative and scalable configurations for wind energy harvesting to use in wireless electronic systems. This paper presents modeling and experiments of aeroelastic energy harvesting using piezoelectric transduction with a focus on exploiting combined nonlinearities. An airfoil with plunge and pitch degrees of freedom (DOF) is investigated. Piezoelectric coupling is introduced to the plunge DOF while nonlinearities are introduced through the pitch DOF. A state-space model is presented and employed for the simulations of the piezoaeroelastic generator. A two-state approximation to Theodorsen aerodynamics is used in order to determine the unsteady aerodynamic loads. Three case studies are presented. First the interaction between piezoelectric power generation and linear aeroelastic behavior of a typical section is investigated for a set of resistive loads. Model predictions are compared to experimental data obtained from the wind tunnel tests at the flutter boundary. In the second case study, free play nonlinearity is added to the pitch DOF and it is shown that nonlinear limit-cycle oscillations can be obtained not only above but also below the linear flutter speed. The experimental results are successfully predicted by the model simulations. Finally, the combination of cubic hardening stiffness and free play nonlinearities is considered in the pitch DOF. The nonlinear piezoaeroelastic response is investigated for different values of the nonlinear-to-linear stiffness ratio. The free play nonlinearity reduces the cut-in speed while the hardening stiffness helps in obtaining persistent oscillations of acceptable amplitude over a wider range of airflow speeds. Such nonlinearities can be introduced to aeroelastic energy harvesters (exploiting piezoelectric or other transduction mechanisms) for performance enhancement.
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Vibration-based energy harvesting has been investigated by several researchers over the last decade. The goal in this research field is to power small electronic components by converting the waste vibration energy available in their environment into electrical energy. Recent literature shows that piezoelectric transduction has received the most attention for vibration-to-electricity conversion. In practice, cantilevered beams and plates with piezoceramic layers are employed as piezoelectric energy harvesters. The existing piezoelectric energy harvester models are beam-type lumped parameter, approximate distributed parameter and analytical distributed parameter solutions. However, aspect ratios of piezoelectric energy harvesters in several cases are plate-like and predicting the power output to general (symmetric and asymmetric) excitations requires a plate-type formulation which has not been covered in the energy harvesting literature. In this paper. an electromechanically coupled finite element (FE) plate model is presented for predicting the electrical power output of piezoelectric energy harvester plates. Generalized Hamilton`s principle for electroelastic bodies is reviewed and the FE model is derived based on the Kirchhoff plate assumptions as typical piezoelectric energy harvesters are thin structures. Presence of conductive electrodes is taken into account in the FE model. The predictions of the FE model are verified against the analytical solution for a unimorph cantilever and then against the experimental and analytical results of a bimorph cantilever with a tip mass reported in the literature. Finally, an optimization problem is solved where the aluminum wing spar of an unmanned air vehicle (UAV) is modified to obtain a generator spar by embedding piezoceramics for the maximum electrical power without exceeding a prescribed mass addition limit. (C) 2009 Elsevier Ltd. All rights reserved.
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This article presents a tool for the allocation analysis of complex systems of water resources, called AcquaNetXL, developed in the form of spreadsheet in which a model of linear optimization and another nonlinear were incorporated. The AcquaNetXL keeps the concepts and attributes of a decision support system. In other words, it straightens out the communication between the user and the computer, facilitates the understanding and the formulation of the problem, the interpretation of the results and it also gives a support in the process of decision making, turning it into a clear and organized process. The performance of the algorithms used for solving the problems of water allocation was satisfactory especially for the linear model.
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Reconciliation can be divided into stages, each stage representing the performance of a mining operation, such as: long-term estimation, short-term estimation, planning, mining and mineral processing. The gold industry includes another stage which is the budget, when the company informs the financial market of its annual production forecast. The division of reconciliation into stages increases the reliability of the annual budget informed by the mining companies, while also detecting and correcting the critical steps responsible for the overall estimation error by the optimization of sampling protocols and equipment. This paper develops and validates a new reconciliation model for the gold industry, which is based on correct sampling practices and the subdivision of reconciliation into stages, aiming for better grade estimates and more efficient control of the mining industry`s processes, from resource estimation to final production.
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This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
A procedure is proposed for the determination of the residence time distribution (RTD) of curved tubes taking into account the non-ideal detection of the tracer. The procedure was applied to two holding tubes used for milk pasteurization in laboratory scale. Experimental data was obtained using an ionic tracer. The signal distortion caused by the detection system was considerable because of the short residence time. Four RTD models, namely axial dispersion, extended tanks in series, generalized convection and PER + CSTR association, were adjusted after convolution with the E-curve of the detection system. The generalized convection model provided the best fit because it could better represent the tail on the tracer concentration curve that is Caused by the laminar velocity profile and the recirculation regions. Adjusted model parameters were well cot-related with the now rate. (C) 2010 Elsevier Ltd. All rights reserved.
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This work proposes a refined technique for the extraction of the generation lifetime in single- and double-gate partially depleted SOI nMOSFETs. The model presented in this paper, based on the drain current switch-off transients, takes into account the influence of the laterally non-uniform channel doping, caused by the presence of the halo implanted region, and the amount of charge controlled by the drain and source junctions on the floating body effect when the channel length is reduced. The obtained results for single- gate (SG) devices are compared with two-dimensional numerical simulations and experimental data, extracted for devices fabricated in a 0.1 mu m SOI CMOS technology, showing excellent agreement. The improved model to determine the generation lifetime in double-gate (DG) devices beyond the considerations previously presented also consider the influence of the silicon layer thickness on the drain current transient. The extracted data through the improved model for DG devices were compared with measurements and two-dimensional numerical simulations of the SG devices also presenting a good adjustment with the channel length reduction and the same tendency with the silicon layer thickness variation.
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Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.
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The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.
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The skin is a large and accessible area of the body, offering the possibility to be used as an alternative route for drug delivery. In the last few years strong progress has been made on the developing of nanoparticulate systems for specific applications. The interaction of such small particles with human skin and their possible penetration attracted some interest from toxicological as well as from drug delivery perspectives. As size is assumed to play a key role, the aim of the present work was to investigate the penetration profile of very small model particles (similar to 4 nm) into excised human skin under conditions chosen to mimic the in vivo situation. Possible application procedures such as massaging the formulation (5 to 10 minutes) were analyzed by non-invasive multiphoton- and confocal laser scanning microscopy (MPM, CLSM). Furthermore, the application on damaged skin was taken into account by deliberately removing parts of the stratum corneum. Although it was clearly observed that the mechanical actions affected the distribution pattern of the QDs on the skin surface, there was no evidence of penetration into the skin in all cases tested. QDs could be found in deeper layers only after massaging of damaged skin for 10 min. Taking these data into account, obtained on the gold standard human skin, the potential applications of nanoparticulate systems to act as carrier delivering drugs into intact skin might be limited and are only of interest for partly damaged skin.
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The course and outcome of infection with mycobacteria are determined by a complex interplay between the immune system of the host and the survival mechanisms developed by the bacilli. Recent data suggest a regulatory role of histamine not only in the innate but also in the adaptive immune response. We used a model of pulmonary Mycobacterium tuberculosis infection in histamine-deficient mice lacking histidine decarboxylase (HDC(-/-)), the histamine-synthesizing enzyme. To confirm that mycobacterial infection induced histamine production, we exposed mice to M. tuberculosis and compared responses in C57BL/6 (wild-type) and HDC(-/-) mice. Histamine levels increased around fivefold above baseline in infected C57BL/6 mice at day 28 of infection, whereas only small amounts were detected in the lungs of infected HDC(-/-) mice. Blocking histamine production decreased both neutrophil influx into lung tissue and the release of proinflammatory mediators, such as interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-alpha), in the acute phase of infection. However, the accumulation and activation of CD4(+) T cells were augmented in the lungs of infected HDC(-/-) mice and correlated with a distinct granuloma formation that contained abundant lymphocytic infiltration and reduced numbers of mycobacteria 28 days after infection. Furthermore, the production of IL-12, gamma interferon, and nitric oxide, as well as CD11c(+) cell influx into the lungs of infected HDC(-/-) mice, was increased. These findings indicate that histamine produced after M. tuberculosis infection may play a regulatory role not only by enhancing the pulmonary neutrophilia and production of IL-6 and TNF-alpha but also by impairing the protective Th1 response, which ultimately restricts mycobacterial growth.