17 resultados para Asymptotic Variance of Estimate

em Universidad Politécnica de Madrid


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The computation of the non-linear vibration dynamics of an aerodynamically unstable bladed-disk is a formidable numerical task, even for the simplified case of aerodynamic forces assumed to be linear. The nonlinear friction forces effectively couple dif- ferent travelling waves modes and, in order to properly elucidate the dynamics of the system, large time simulations are typically required to reach a final, saturated state. Despite of all the above complications, the output of the system (in the friction microslip regime) is basically a superposition of the linear aeroelastic un- stable travelling waves, which exhibit a slow time modulation that is much longer than the elastic oscillation period. This slow time modulation is due to both, the small aerodynamic effects and the small nonlinear friction forces, and it is crucial to deter- mine the final amplitude of the flutter vibration. In this presenta- tion we apply asymptotic techniques to obtain a new simplified model that captures the slow time dynamics of the amplitudes of the travelling waves. The resulting asymptotic model is very re- duced and extremely cheap to simulate, and it has the advantage that it gives precise information about the characteristics of the nonlinear friction models that actually play a role in the satura- tion of the vibration amplitude.

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The computation of the non-linear vibration dynamics of an aerodynamically unstable bladed-disk is a formidable numerical task, even for the simplified case of aerodynamic forces assumed to be linear. The nonlinear friction forces effectively couple dif- ferent travelling waves modes and, in order to properly elucidate the dynamics of the system, large time simulations are typically required to reach a final, saturated state. Despite of all the above complications, the output of the system (in the friction microslip regime) is basically a superposition of the linear aeroelastic un- stable travelling waves, which exhibit a slow time modulation that is much longer than the elastic oscillation period. This slow time modulation is due to both, the small aerodynamic effects and the small nonlinear friction forces, and it is crucial to deter- mine the final amplitude of the flutter vibration. In this presenta- tion we apply asymptotic techniques to obtain a new simplified model that captures the slow time dynamics of the amplitudes of the travelling waves. The resulting asymptotic model is very re- duced and extremely cheap to simulate, and it has the advantage that it gives precise information about the characteristics of the nonlinear friction models that actually play a role in the satura- tion of the vibration amplitude.

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We consider a simplified system of a growing colony of cells described as a free boundary problem. The system consists of two hyperbolic equations of first order coupled to an ODE to describe the behavior of the boundary. The system for cell populations includes non-local terms of integral type in the coefficients. By introducing a comparison with solutions of an ODE's system, we show that there exists a unique homogeneous steady state which is globally asymptotically stable for a range of parameters under the assumption of radially symmetric initial data.

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Suslin analytic sets characterize the sets of asymptotic values of entire holomorphic functions. By a theorem of Ahlfors, the set of asymptotic values is finite for a function with finite order of growth. Quasiregular maps are a natural generalization of holomorphic functions to dimensions n ≥ 3 and, in fact, many of the properties of holomorphic functions have counterparts for quasiregular maps. It is shown that analytic sets also characterize the sets of asymptotic values of quasiregular maps in Rn, even for those with finite order of growth. Our construction is based on Drasin's quasiregular sine function

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Theoretical models for the thermal response of vertical geothermal boreholes often assume that the characteristic time of variation of the heat injection rate is much larger than the characteristic diffusion time across the borehole. In this case, heat transfer inside the borehole and in its immediate surroundings is quasi-steady in the first approximation, while unsteady effects enter only in the far field. Previous studies have exploited this disparity of time scales, incorporating approximate matching conditions to couple the near-borehole region with the outer unsteady temperatura field. In the present work matched asymptotic expansion techniques are used to analyze the heat transfer problem, delivering a rigorous derivation of the true matching condition between the two regions and of the correct definition of the network of thermal resistances that represents the quasi-steady solution near the borehole. Additionally, an apparent temperature due to the unsteady far field is identified that needs to be taken into account by the near-borehole region for the correct computation of the heat injection rate. This temperature differs from the usual mean borehole temperature employed in the literatura.

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Abstract We consider a wide class of models that includes the highly reliable Markovian systems (HRMS) often used to represent the evolution of multi-component systems in reliability settings. Repair times and component lifetimes are random variables that follow a general distribution, and the repair service adopts a priority repair rule based on system failure risk. Since crude simulation has proved to be inefficient for highly-dependable systems, the RESTART method is used for the estimation of steady-state unavailability and other reliability measures. In this method, a number of simulation retrials are performed when the process enters regions of the state space where the chance of occurrence of a rare event (e.g., a system failure) is higher. The main difficulty involved in applying this method is finding a suitable function, called the importance function, to define the regions. In this paper we introduce an importance function which, for unbalanced systems, represents a great improvement over the importance function used in previous papers. We also demonstrate the asymptotic optimality of RESTART estimators in these models. Several examples are presented to show the effectiveness of the new approach, and probabilities up to the order of 10-42 are accurately estimated with little computational effort.

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El estudio de la fiabilidad de componentes y sistemas tiene gran importancia en diversos campos de la ingenieria, y muy concretamente en el de la informatica. Al analizar la duracion de los elementos de la muestra hay que tener en cuenta los elementos que no fallan en el tiempo que dure el experimento, o bien los que fallen por causas distintas a la que es objeto de estudio. Por ello surgen nuevos tipos de muestreo que contemplan estos casos. El mas general de ellos, el muestreo censurado, es el que consideramos en nuestro trabajo. En este muestreo tanto el tiempo hasta que falla el componente como el tiempo de censura son variables aleatorias. Con la hipotesis de que ambos tiempos se distribuyen exponencialmente, el profesor Hurt estudio el comportamiento asintotico del estimador de maxima verosimilitud de la funcion de fiabilidad. En principio parece interesante utilizar metodos Bayesianos en el estudio de la fiabilidad porque incorporan al analisis la informacion a priori de la que se dispone normalmente en problemas reales. Por ello hemos considerado dos estimadores Bayesianos de la fiabilidad de una distribucion exponencial que son la media y la moda de la distribucion a posteriori. Hemos calculado la expansion asint6tica de la media, varianza y error cuadratico medio de ambos estimadores cuando la distribuci6n de censura es exponencial. Hemos obtenido tambien la distribucion asintotica de los estimadores para el caso m3s general de que la distribucion de censura sea de Weibull. Dos tipos de intervalos de confianza para muestras grandes se han propuesto para cada estimador. Los resultados se han comparado con los del estimador de maxima verosimilitud, y con los de dos estimadores no parametricos: limite producto y Bayesiano, resultando un comportamiento superior por parte de uno de nuestros estimadores. Finalmente nemos comprobado mediante simulacion que nuestros estimadores son robustos frente a la supuesta distribuci6n de censura, y que uno de los intervalos de confianza propuestos es valido con muestras pequenas. Este estudio ha servido tambien para confirmar el mejor comportamiento de uno de nuestros estimadores. SETTING OUT AND SUMMARY OF THE THESIS When we study the lifetime of components it's necessary to take into account the elements that don't fail during the experiment, or those that fail by reasons which are desirable to exclude from consideration. The model of random censorship is very usefull for analysing these data. In this model the time to failure and the time censor are random variables. We obtain two Bayes estimators of the reliability function of an exponential distribution based on randomly censored data. We have calculated the asymptotic expansion of the mean, variance and mean square error of both estimators, when the censor's distribution is exponential. We have obtained also the asymptotic distribution of the estimators for the more general case of censor's Weibull distribution. Two large-sample confidence bands have been proposed for each estimator. The results have been compared with those of the maximum likelihood estimator, and with those of two non parametric estimators: Product-limit and Bayesian. One of our estimators has the best behaviour. Finally we have shown by simulation, that our estimators are robust against the assumed censor's distribution, and that one of our intervals does well in small sample situation.

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Pressure measurements on the surface of a 1:230 scale model of Bolund Island are presented. The model is smooth and no boundary layer generation has been considered since the experiment is designed as the simplest possible reference case. Measurement have been taken for a range of Reynolds numbers based on the average undisturbed wind speed U∞ and the maximum height of the island, h [1.7×104, 8.5×104], and for a range of wind directions. Four minutes time series of pressure in more than 400 points have been acquired and analysed to obtain the spatial distribution of both the time average and the variance of the pressure signal. The horizontal extension of the detachment bubble for the different Reynolds numbers and wind directions is identified by isobars and curves of constant value of pressure variance. The applicability of this technique for evaluating the horizontal topology of high turbulence regions associated to detachment bubbles after escarpments in potential wind farm sites is analysed. The results obtained shows that the behaviour of the mean pressure coefficient, Cp, the std. pressure coefficient, Cp, and the skewness of the pressure, Sp can be used to study the bubble over the island to a certain extent. This experiment is part of the set of different analysis on the Bolund test case that is being undertaken within WAUDIT project by the different scientific groups.

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An asymptotic analysis of the Langmuir-probe problem in a quiescent, fully ionized plasma in a strong magnetic field is performed, for electron cyclotron radius and Debye length much smaller than probe radius, and this not larger than either ion cyclotron radius or mean free path. It is found that the electric potential, which is not confined to a sheath, controls the diffusion far from the probe; inside the magnetic tube bounded by the probe cross section the potential overshoots to a large value before decaying to its value in the body of the plasma. The electron current is independent of the shape of the body along the field and increases with ion temperature; due to the overshoot in the potential, (1) the current at negative voltages does not vary exponentially, (2) its magnitude is strongly reduced by the field, and (3) the usual sharp knee at space potential, disappears. In the regions of the C-V diagram studied the ion current is negligible or unaffected by the field. Some numerical results are presented.The theory, which fails beyond certain positive voltage, fields useful results for weak fields, too.

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An asymptotic analysis of electron collection at high bias Fp serves to determine the domain of validity of the orbital-motion-limited regime of cylindrical Langmuir probes, which is basic for the workings of conductive bare tethers. The radius of a wire collecting OML current in an unmagnetized plasma at rest cannot exceed a value, Rmax , which is found to exhibit a minimum as a function of Fp ; atFp values of interest, Rmax is already increasing and is larger than the electron Debye length lDe . The breakdown of the regime relates to conditions far fromthe probe, at electron energies comparable to the ion thermal energy, kTi ; Rmax is found to increase with Ti . It is also found that ~1! the maximumwidth of a thin tape, if used instead of a wire, is 4Rmax ; ~2! the electron thermal gyroradius must be larger than both R and lDe for magnetic effects to be negligible; and ~3! conditions applying to the tether case are such that trapped-orbit effects are negligible.

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An asymptotic analysîs of the Eberstein-Glassman kinetic mechanlsm for the thermal décomposition of hydrazine is carried out. It is shown that at températures near 800°K and near 1000°K,and for hydrazine molar fractions of the order of unity, 10-2 the entire kinetics reduces to a single, overall reaction. Characteristic times for the chemical relaxation of ail active, intermediate species produced in the décomposition, and for the overall reaction, are obtained. Explicit expressions for the overall reaction rate and stoichiometry are given as functions of température, total molar concentration (or pressure)and hydrazine molar fraction. Approximate, patched expressions can then be obtained for values of température and hydrazine molar fraction between 750 and 1000°K, and 1 and 10-3 respectively.

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The analysis of complex nonlinear systems is often carried out using simpler piecewise linear representations of them. A principled and practical technique is proposed to linearize and evaluate arbitrary continuous nonlinear functions using polygonal (continuous piecewise linear) models under the L1 norm. A thorough error analysis is developed to guide an optimal design of two kinds of polygonal approximations in the asymptotic case of a large budget of evaluation subintervals N. The method allows the user to obtain the level of linearization (N) for a target approximation error and vice versa. It is suitable for, but not limited to, an efficient implementation in modern Graphics Processing Units (GPUs), allowing real-time performance of computationally demanding applications. The quality and efficiency of the technique has been measured in detail on two nonlinear functions that are widely used in many areas of scientific computing and are expensive to evaluate.

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Pressure measurements on the surface of a 1:230 scale model of Bolund Island are presented. The model is smooth and no boundary layer generation has been considered since the experiment is designed as the simplest possible reference case. Measurement have been taken for a range of Reynolds numbers based on the average undisturbed wind speed U? and the maximum height of the island, h [1.7×104 , 8.5×104], and for a range of wind directions. Four minutes time series of pressure in more than 400 points have been acquired and analysed to obtain the spatial distribution of both the time average and the variance of the pressure signal. The horizontal extension of the detachment bubble for the different Reynolds numbers and wind directions is identified by isobars and curves of constant value of pressure variance. The applicability of this technique for evaluating the horizontal topology of high turbulence regions associated to detachment bubbles after escarpments in potential wind farm sites is analysed. The results obtained shows that the behaviour of the mean pressure coefficient, Cp, the std. pressure coefficient, C?p, and the skewness of the pressure, Sp can be used to study the bubble over the island to a certain extent. This experiment is part of the set of different analysis on the Bolund test case that is being undertaken within WAUDIT project by the different scientific groups.

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Prediction at ungauged sites is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. Regression models relate physiographic and climatic basin characteristics to flood quantiles, which can be estimated from observed data at gauged sites. However, these models assume linear relationships between variables Prediction intervals are estimated by the variance of the residuals in the estimated model. Furthermore, the effect of the uncertainties in the explanatory variables on the dependent variable cannot be assessed. This paper presents a methodology to propagate the uncertainties that arise in the process of predicting flood quantiles at ungauged basins by a regression model. In addition, Bayesian networks were explored as a feasible tool for predicting flood quantiles at ungauged sites. Bayesian networks benefit from taking into account uncertainties thanks to their probabilistic nature. They are able to capture non-linear relationships between variables and they give a probability distribution of discharges as result. The methodology was applied to a case study in the Tagus basin in Spain.

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Perceptual voice evaluation according to the GRBAS scale is modelled using a linear combination of acoustic parameters calculated after a filter-bank analysis of the recorded voice signals. Modelling results indicate that for breathiness and asthenia more than 55% of the variance of perceptual rates can be explained by such a model, with only 4 latent variables. Moreover, the greatest part of the explained variance can be attributed to only one or two latent variables similarly weighted by all 5 listeners involved in the experiment. Correlation factors between actual rates and model predictions around 0.6 are obtained.