862 resultados para modelling and simulation
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Subsidence is a natural hazard that affects wide areas in the world causing important economic costs annually. This phenomenon has occurred in the metropolitan area of Murcia City (SE Spain) as a result of groundwater overexploitation. In this work aquifer system subsidence is investigated using an advanced differential SAR interferometry remote sensing technique (A-DInSAR) called Stable Point Network (SPN). The SPN derived displacement results, mainly the velocity displacement maps and the time series of the displacement, reveal that in the period 2004–2008 the rate of subsidence in Murcia metropolitan area doubled with respect to the previous period from 1995 to 2005. The acceleration of the deformation phenomenon is explained by the drought period started in 2006. The comparison of the temporal evolution of the displacements measured with the extensometers and the SPN technique shows an average absolute error of 3.9±3.8 mm. Finally, results from a finite element model developed to simulate the recorded time history subsidence from known water table height changes compares well with the SPN displacement time series estimations. This result demonstrates the potential of A-DInSAR techniques to validate subsidence prediction models as an alternative to using instrumental ground based techniques for validation.
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We have measured experimental adsorption isotherms of water in zeolite LTA4A, and studied the regeneration process by performing subsequent adsorption cycles after degassing at different temperatures. We observed incomplete desorption at low temperatures, and cation rearrangement at successive adsorption cycles. We also developed a new molecular simulation force field able to reproduce experimental adsorption isotherms in the range of temperatures between 273 K and 374 K. Small deviations observed at high pressures are attributed to the change in the water dipole moment at high loadings. The force field correctly describes the preferential adsorption sites of water at different pressures. We tested the influence of the zeolite structure, framework flexibility, and cation mobility when considering adsorption and diffusion of water. Finally, we performed checks on force field transferability between different hydrophilic zeolite types, concluding that classical, non-polarizable water force fields are not transferable.
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Numerical modelling methodologies are important by their application to engineering and scientific problems, because there are processes where analytical mathematical expressions cannot be obtained to model them. When the only available information is a set of experimental values for the variables that determine the state of the system, the modelling problem is equivalent to determining the hyper-surface that best fits the data. This paper presents a methodology based on the Galerkin formulation of the finite elements method to obtain representations of relationships that are defined a priori, between a set of variables: y = z(x1, x2,...., xd). These representations are generated from the values of the variables in the experimental data. The approximation, piecewise, is an element of a Sobolev space and has derivatives defined in a general sense into this space. The using of this approach results in the need of inverting a linear system with a structure that allows a fast solver algorithm. The algorithm can be used in a variety of fields, being a multidisciplinary tool. The validity of the methodology is studied considering two real applications: a problem in hydrodynamics and a problem of engineering related to fluids, heat and transport in an energy generation plant. Also a test of the predictive capacity of the methodology is performed using a cross-validation method.
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Comunicação apresentada no CYTEF 2016/VIII Congresso Ibérico | VI Congresso Ibero-Americano de Ciências e Técnicas do Frio, 3-6 maio 2016, Coimbra, Portugal
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"UILU Eng 79 1709."
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"Contract no. US AEC AT (11-1)1469."
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Mode of access: Internet.
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We present new simulation results for the packing of single-center and three-center models of carbon dioxide at high pressure in carbon slit pores. The former shows a series of packing transitions that are well described by our density functional theory model developed earlier. In contrast, these transitions are absent for the three-center model. Analysis of the simulation results shows that alternations of flat-lying molecules and rotated molecules can occur as the pore width is increased. The presence or absence of quadrupoles has negligible effect on these high-density structures.
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Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.
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While it is well known that reading is highly heritable, less has been understood about the bases of these genetic influences. In this paper, we review the research that we have been conducting in recent years to examine genetic and environmental influences on the particular reading processes specified in the dual-route cognitive model of reading. We argue that a detailed understanding of the role of genetic factors in reading acquisition requires the delineation and measurement of precise phenotypes, derived from well-articulated models of the reading process. We report evidence for independent genetic influences on the lexical and nonlexical reading processes represented in the dual-route model, based on studies of children with particular subtypes of dyslexia, and on univariate and multivariate genetic modelling of reading performance in the normally reading population.
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Fuzzy data has grown to be an important factor in data mining. Whenever uncertainty exists, simulation can be used as a model. Simulation is very flexible, although it can involve significant levels of computation. This article discusses fuzzy decision-making using the grey related analysis method. Fuzzy models are expected to better reflect decision-making uncertainty, at some cost in accuracy relative to crisp models. Monte Carlo simulation is used to incorporate experimental levels of uncertainty into the data and to measure the impact of fuzzy decision tree models using categorical data. Results are compared with decision tree models based on crisp continuous data.
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The concentration of ammonium-nitrogen (NH4+-N) frequently exceeds that of nitrate-N (NO3--N) in Australian wet tropical sugarcane soils. The amount of mineral N in soil is the net result of complex processes in the field, so the objective of this experiment was to investigate nitrification and ammonification in these soils under laboratory conditions. Aerobic and saturated incubations were performed for 1 week on 2 wet tropical soils. Net NO3--N increased significantly in both soils during both types of incubation. A second series of aerobic incubations of these soils treated with NH4+-N and inoculated with subtropical nitrifying soils was conducted for 48 days. Nitrification in the wet tropical soils was not significantly affected by inoculation, and virtually all added N was nitrified during the incubation period. Mineral N behaviour of the 48-day incubations was captured with the APSIM-SoilN model. As nitrification proceeded under laboratory conditions and was able to be captured by the model, it was concluded that nitrification processes in the wet tropical soils studied were not different from those in the subtropical soils. Processes that remove NO3- from the soil, such as leaching and denitrification, may therefore be important factors affecting the proportions of NH4+-N and NO3--N measured under field conditions.
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We present results of the reconstruction of a saccharose-based activated carbon (CS1000a) using hybrid reverse Monte Carlo (HRMC) simulation, recently proposed by Opletal et al. [1]. Interaction between carbon atoms in the simulation is modeled by an environment dependent interaction potential (EDIP) [2,3]. The reconstructed structure shows predominance of sp(2) over sp bonding, while a significant proportion of sp(3) hybrid bonding is also observed. We also calculated a ring distribution and geometrical pore size distribution of the model developed. The latter is compared with that obtained from argon adsorption at 87 K using our recently proposed characterization procedure [4], the finite wall thickness (FWT) model. Further, we determine self-diffusivities of argon and nitrogen in the constructed carbon as functions of loading. It is found that while there is a maximum in the diffusivity with respect to loading, as previously observed by Pikunic et al. [5], diffusivities in the present work are 10 times larger than those obtained in the prior work, consistent with the larger pore size as well as higher porosity of the activated saccharose carbon studied here.