981 resultados para Parametric Inverse Modelling.


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Parametric VaR (Value-at-Risk) is widely used due to its simplicity and easy calculation. However, the normality assumption, often used in the estimation of the parametric VaR, does not provide satisfactory estimates for risk exposure. Therefore, this study suggests a method for computing the parametric VaR based on goodness-of-fit tests using the empirical distribution function (EDF) for extreme returns, and compares the feasibility of this method for the banking sector in an emerging market and in a developed one. The paper also discusses possible theoretical contributions in related fields like enterprise risk management (ERM). © 2013 Elsevier Ltd.

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The benthic dinoflagellate O. ovata represents a serious threat for human health and for the ecology of its blooming areas: thanks to its toxicity this microalga has been responsible for several cases of human intoxication and mass mortalities of benthic invertebrates. Although the large number of studies on this dinoflagellate, the mechanisms underpinning O. ovata growth and toxin production are still far to be fully understood. In this work we have enriched the dataset on this species by carrying out a new experiment on an Adriatic O. cf. ovata strain. Data from this experiment (named Beta) and from another comparable experiment previously conducted on the same strain (named Alpha), revealed some interesting aspects of this dinoflagellate: it is able to grow also in a condition of strong intracellular nutrient deficiency (C:P molar ratio > 400; C:N > 25), reaching extremely low values of chlorophyll-a to carbon ratio (0.0004). Was also found a significant inverse relationships (r > -0.7) between cellular toxin to carbon and cellular nutrient to carbon ratios of experiment Alpha. In the light of these result, we hypothesized that in O. cf. ovata nutrient-stress conditions (intended as intracellular nutrient deficiency) can cause: i) an increase in toxin production; ii) a strong decrease in chlorophyll-a synthesis; iii) a lowering of metabolism associated with the formation of a sort of resting stage. We then used a modelling approach to test and critically evaluate these hypotheses in a mechanistic way: newly developed formulation describing toxin production and fate, and ad hoc changes in the already existent formulations describing chlorophyll synthesis, rest respiration, and mortality, have been incorporated in a simplified version of the European Regional Seas Ecosystem Model (ERSEM), together with a new ad hoc parameterization. The adapted model was able to accurately reproduce many of the trends observed in the Alpha experiment, allowing us to support our hypotheses. Instead the simulations of the experiment Beta were not fully satisfying in quantitative terms. We explained this gap with the presumed different physiological behaviors between the algae of the two experiments, due to the different pre-experimental periods of acclimation: the model was not able to reproduce acclimation processes in its simulations of the experiment Beta. Thus we attempt to simulate the acclimation of the algae to nutrient-stress conditions by manual intervention on some parameters of nutrient-stress thresholds, but we received conflicting results. Further studies are required to shed light on this interesting aspect. In this work we also improve the range of applicability of a state of the art marine biogeochemical model (ERSEM) by implementing in it an ecological relevant process such as the production of toxic compounds.

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The solubility parameters of two SBS commercial rubbers with different structures (lineal and radial), and with slightly different styrene content have been determined by inverse gas chromatography technique. The Flory–Huggins interaction parameters of several polymer–solvent mixtures have also been calculated. The influence of the polymer composition, the solvent molecular weight and the temperature over these parameters have been discussed; besides, these parameters have been compared with previous ones, obtained by intrinsic viscosity measurements. From the Flory–Huggins interaction parameters, the infinite dilution activity coefficients of the solvents have been calculated and fitted to the well-known NRTL model. These NRTL binary interaction parameters have a great importance in modelling the separation steps in the process of obtaining the rubber.

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This paper deals with the theoretical method and the modelling problems on the analysis of the Pyrotechnic Shock Propagation in the Vehicle Equipment Bay Structure of the ARIANE 5 during the separation of the upper stage. This work has been developed under a contract with the Spanish Firm Construcciones Aeronáuticas S.A. From all the analysis and the studies it can be concluded that: 1.- The mathematical method used for the study of the pyrotechnic shock phenomena is very well suited for conducting parametric studies. 2.- A careful model of the structure should be developed taking into account the realistic stiffness and dissipation properties at the junctions. 3.- The load produced by the pyrotechnic device should be carefully calibrated to reach a good agreement between theoretical and test results. 4.- In any case with the adquired experience it can be said that with the modelling of continuous elements the order of magnitude of the accelerations can be predicted with the accuracy needed in practical applications.

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Penguin colonies represent some of the most concentrated sources of ammonia emissions to the atmosphere in the world. The ammonia emitted into the atmosphere can have a large influence on the nitrogen cycling of ecosystems near the colonies. However, despite the ecological importance of the emissions, no measurements of ammonia emissions from penguin colonies have been made. The objective of this work was to determine the ammonia emission rate of a penguin colony using inverse-dispersion modelling and gradient methods. We measured meteorological variables and mean atmospheric concentrations of ammonia at seven locations near a colony of Adélie penguins in Antarctica to provide input data for inverse-dispersion modelling. Three different atmospheric dispersion models (ADMS, LADD and a Lagrangian stochastic model) were used to provide a robust emission estimate. The Lagrangian stochastic model was applied both in ‘forwards’ and ‘backwards’ mode to compare the difference between the two approaches. In addition, the aerodynamic gradient method was applied using vertical profiles of mean ammonia concentrations measured near the centre of the colony. The emission estimates derived from the simulations of the three dispersion models and the aerodynamic gradient method agreed quite well, giving a mean emission of 1.1 g ammonia per breeding pair per day (95% confidence interval: 0.4–2.5 g ammonia per breeding pair per day). This emission rate represents a volatilisation of 1.9% of the estimated nitrogen excretion of the penguins, which agrees well with that estimated from a temperature-dependent bioenergetics model. We found that, in this study, the Lagrangian stochastic model seemed to give more reliable emission estimates in ‘forwards’ mode than in ‘backwards’ mode due to the assumptions made.

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One of the outstanding problems of the modelling of temperate ice dynamics is the limited knowledge on the rheology of temperate ice and, in particular, on how the rate factor depends on the liquid water content. Though it is well known that the rate factor depends strongly on the water content, in practice the only available experimentally-based relationship is that by Duval (1977), which is only valid for water contents up to 1%. However, actual water contents found in temperate and polythermal glaciers are sometimes substantially larger.

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The need to modal semi-rigid behaviour of joints to analyze the seismic response of bridges arises when retrofitting devices such as cables or bolts are introduced in otherwise free joints or when the design takes advantage of the plastification of structural sections to impose energy dissipation though their ductile behaviour. The paper presents some preliminary results of a parametric study carried out using s1mplified computational models. Two instances where semirigid connection play a role in the seismic response of bridges have been discussed. The ongoing research from which this paper is extracted is intended to enhance understanding on the effectivness of various bridge retrofitting measures and to provide information that may be used to calibrate some ECS-2 rules. Finally, it is hoped that the development of reliable simplified techniques for nonlinear analysis will provide designers with useful tools to examine behavior and ultimately improve seismic safety in actual bridges.

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Here, Vortex-Induced Vibrations (VIVs) of a circular cylinder are analyzed as a potential source for energy harvesting. To this end, VIV is described by a one-degree-of-freedom model where fluid forces are introduced from experimental data from forced vibration tests. The influence of some influencing parameters, like the mass ratio m∗ or the mechanical damping ζ in the energy conversion factor is investigated. The analysis reveals that: (i) the maximum efficiency ηM is principally influenced by the mass-damping parameter m∗ζ and there is an optimum value of m∗ζ where ηM presents a maximum; (ii) the range of reduced velocities with significant efficiency is mainly governed by m∗, and (iii) it seems that encouraging high efficiency values can be achieved for high Reynolds numbers.

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The present thesis is focused on the development of a thorough mathematical modelling and computational solution framework aimed at the numerical simulation of journal and sliding bearing systems operating under a wide range of lubrication regimes (mixed, elastohydrodynamic and full film lubrication regimes) and working conditions (static, quasi-static and transient conditions). The fluid flow effects have been considered in terms of the Isothermal Generalized Equation of the Mechanics of the Viscous Thin Films (Reynolds equation), along with the massconserving p-Ø Elrod-Adams cavitation model that accordingly ensures the so-called JFO complementary boundary conditions for fluid film rupture. The variation of the lubricant rheological properties due to the viscous-pressure (Barus and Roelands equations), viscous-shear-thinning (Eyring and Carreau-Yasuda equations) and density-pressure (Dowson-Higginson equation) relationships have also been taken into account in the overall modelling. Generic models have been derived for the aforementioned bearing components in order to enable their applications in general multibody dynamic systems (MDS), and by including the effects of angular misalignments, superficial geometric defects (form/waviness deviations, EHL deformations, etc.) and axial motion. The bearing exibility (conformal EHL) has been incorporated by means of FEM model reduction (or condensation) techniques. The macroscopic in fluence of the mixedlubrication phenomena have been included into the modelling by the stochastic Patir and Cheng average ow model and the Greenwood-Williamson/Greenwood-Tripp formulations for rough contacts. Furthermore, a deterministic mixed-lubrication model with inter-asperity cavitation has also been proposed for full-scale simulations in the microscopic (roughness) level. According to the extensive mathematical modelling background established, three significant contributions have been accomplished. Firstly, a general numerical solution for the Reynolds lubrication equation with the mass-conserving p - Ø cavitation model has been developed based on the hybridtype Element-Based Finite Volume Method (EbFVM). This new solution scheme allows solving lubrication problems with complex geometries to be discretized by unstructured grids. The numerical method was validated in agreement with several example cases from the literature, and further used in numerical experiments to explore its exibility in coping with irregular meshes for reducing the number of nodes required in the solution of textured sliding bearings. Secondly, novel robust partitioned techniques, namely: Fixed Point Gauss-Seidel Method (PGMF), Point Gauss-Seidel Method with Aitken Acceleration (PGMA) and Interface Quasi-Newton Method with Inverse Jacobian from Least-Squares approximation (IQN-ILS), commonly adopted for solving uid-structure interaction problems have been introduced in the context of tribological simulations, particularly for the coupled calculation of dynamic conformal EHL contacts. The performance of such partitioned methods was evaluated according to simulations of dynamically loaded connecting-rod big-end bearings of both heavy-duty and high-speed engines. Finally, the proposed deterministic mixed-lubrication modelling was applied to investigate the in fluence of the cylinder liner wear after a 100h dynamometer engine test on the hydrodynamic pressure generation and friction of Twin-Land Oil Control Rings.

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Frequently, population ecology of marine organisms uses a descriptive approach in which their sizes and densities are plotted over time. This approach has limited usefulness for design strategies in management or modelling different scenarios. Population projection matrix models are among the most widely used tools in ecology. Unfortunately, for the majority of pelagic marine organisms, it is difficult to mark individuals and follow them over time to determine their vital rates and built a population projection matrix model. Nevertheless, it is possible to get time-series data to calculate size structure and densities of each size, in order to determine the matrix parameters. This approach is known as a “demographic inverse problem” and it is based on quadratic programming methods, but it has rarely been used on aquatic organisms. We used unpublished field data of a population of cubomedusae Carybdea marsupialis to construct a population projection matrix model and compare two different management strategies to lower population to values before year 2008 when there was no significant interaction with bathers. Those strategies were by direct removal of medusae and by reducing prey. Our results showed that removal of jellyfish from all size classes was more effective than removing only juveniles or adults. When reducing prey, the highest efficiency to lower the C. marsupialis population occurred when prey depletion affected prey of all medusae sizes. Our model fit well with the field data and may serve to design an efficient management strategy or build hypothetical scenarios such as removal of individuals or reducing prey. TThis This sdfsdshis method is applicable to other marine or terrestrial species, for which density and population structure over time are available.

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With increasing industry interest in high pressure roll grinding (HPGR) technology, there is a strong incentive for improved understanding of the nature of grinding pressure that exists in the interior of a compressed particle bed. This corresponds to the crushing region of the HPGR. The relationship between applied pressure (stress) to the particle bed and induced pressure (stress) within particles and at contact points between particles is of particular interest. A detailed parametric investigation is beyond the scope of this exploratory paper. However, this exploratory investigation does suggest some interesting behaviour. The compressed particle bed within an 80 turn diameter piston has been modelled using Particle Flow Code for three dimensions. PFC3D is a discrete element code. The total number of simulated particles was 1225 and 2450 for two beds of different thickness. Particle diameters were uniformly distributed between 4 and 4.5 mm. The results of the simulations show that stress intensity within the simulated particle beds and within the observed particles increased with increase of the applied stress. The intensity of the average vertical stress in the selected particles tended to be comparable with the intensity of the pressure applied to the surface of particle bed and was only occasionally higher. However, the stress at contact points between particles could be several times higher. In a real crusher, such high stress amplification at contacts will quickly decrease due to local crushing and a resultant increase the size of the contact area. Therefore, its significance is likely to be relatively small in an industrial context. The modelling results also suggest that failure within the particle bed will progress from the crushing surface towards the depth of the bed. (c) 2006 Elsevier Ltd. All rights reserved.

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Photo-detection plays a fundamental role in experimental quantum optics and is of particular importance in the emerging field of linear optics quantum computing. Present theoretical treatment of photo-detectors is highly idealized and fails to consider many important physical effects. We present a physically motivated model for photo-detectors which accommodates for the effects of finite resolution, bandwidth and efficiency, as well as dark counts and dead-time. We apply our model to two simple well-known applications, which illustrates the significance of these characteristics.

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Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck's parameters.

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We consider an inversion-based neurocontroller for solving control problems of uncertain nonlinear systems. Classical approaches do not use uncertainty information in the neural network models. In this paper we show how we can exploit knowledge of this uncertainty to our advantage by developing a novel robust inverse control method. Simulations on a nonlinear uncertain second order system illustrate the approach.

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We introduce a novel inversion-based neuro-controller for solving control problems involving uncertain nonlinear systems that could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. In this work a novel robust inverse control approach is obtained based on importance sampling from these distributions. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The performance of the new algorithm is illustrated through simulations with example systems.