348 resultados para Nonlinear processes


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Characteristics of the process of entrainment in plane mixing layers, and the changes with compressibility and heat release, were studied using temporal DNS with simultaneous fluid packet tracking. Convective Mach numbers of the simulations are 0.15, 0.7 and 1.1. The Reynolds number is quite high (between 11 000 and 37 000 based on layer width and velocity difference), and is above the mixing transition. The study agrees with recent findings in round jets: first, engulfed fluid volume and its growth rate are both very small compared with the volume of the turbulent region and its growth rate, respectively. Secondly, most often, the process occurs close to the turbulent-nonturbulent boundaries. A new finding is that both compressibility and heat release retard the entrainment process so that it takes an O(1) time for vorticity or scalar levels to grow even after growth has been initiated. This delay is manifested as the fall in mixing layer growth rates as compressibility and heat release levels increase.

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Bulk Ge15Te83Si2 glass has been found to exhibit memory-type switching for 1 mA current with a threshold electric field of 7.3 kV/cm. The electrical set and reset processes have been achieved with triangular and rectangular pulses, respectively, of 1 mA amplitude. In situ Raman scattering studies indicate that the degree of disorder in Ge15Te83Si2 glass is reduced from off to set state. The local structure of the sample under reset condition is similar to that in the off state. The Raman results are consistent with the switching results which indicate that the Ge15Te83Si2 glass can be set and reset easily. (C) 2007 American Institute of Physics.

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STOAT has been extensively used for the dynamic simulation of an activated sludge based wastewater treatment plant in the Titagarh Sewage Treatment Plant, near Kolkata, India. Some alternative schemes were suggested. Different schemes were compared for the removal of Total Suspended Solids (TSS), b-COD, ammonia, nitrates etc. A combination of IAWQ#1 module with the Takacs module gave best results for the existing scenarios of the Titagarh Sewage Treatment Plant. The modified Bardenpho process was found most effective for reducing the mean b-COD level to as low as 31.4 mg/l, while the mean TSS level was as high as 100.98 mg/l as compared to the mean levels of TSS (92 62 mg/l) and b-COD (92.0 mg/l) in the existing plant. Scheme 2 gave a better scenario for the mean TSS level bringing it down to a mean value of 0.4 mg/l, but a higher mean value for the b-COD level at 54.89 mg/l. The Scheme Final could reduce the mean TSS level to 2.9 mg/l and the mean b-COD level to as low as 38.8 mg/l. The Final Scheme looks to be a technically viable scheme with respect to the overall effluent quality for the plant. (C) 2009 Elsevier B.V. All rights reserved.

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We report the surface laser damage threshold in sodium p-nitrophenolate dihydrate, a nonlinear optical crystal. The experiment is performed with a pulsed Nd:YAG laser in TEM00 mode. The single shot damage thresholds are 11.16 +/- 0.28GWcm(-2) and 1.25 +/- 0.02GWcm(-2) for 1064 nm and 532 nm laser wavelengths respectively. A close correlation between the laser damage threshold and mechanical hardness is observed. A possible mechanism of laser damage is discussed.

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In this paper a nonlinear optimal controller has been designed for aerodynamic control during the reentry phase of the Reusable Launch Vehicle (RLV). The controller has been designed based on a recently developed technique Optimal Dynamic Inversion (ODI). For full state feedback the controller has required full information about the system states. In this work an Extended Kalman filter (EKF) is developed to estimate the states. The vehicle (RLV) has been has been consider as a nonlinear Six-Degree-Of-Freedom (6-DOF) model. The simulation results shows that EKF gives a very good estimation of the states and it is working well with ODI. The resultant trajectories are very similar to those obtained by perfect state feedback using ODI only.

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The problem of identifying parameters of nonlinear vibrating systems using spatially incomplete, noisy, time-domain measurements is considered. The problem is formulated within the framework of dynamic state estimation formalisms that employ particle filters. The parameters of the system, which are to be identified, are treated as a set of random variables with finite number of discrete states. The study develops a procedure that combines a bank of self-learning particle filters with a global iteration strategy to estimate the probability distribution of the system parameters to be identified. Individual particle filters are based on the sequential importance sampling filter algorithm that is readily available in the existing literature. The paper develops the requisite recursive formulary for evaluating the evolution of weights associated with system parameter states. The correctness of the formulations developed is demonstrated first by applying the proposed procedure to a few linear vibrating systems for which an alternative solution using adaptive Kalman filter method is possible. Subsequently, illustrative examples on three nonlinear vibrating systems, using synthetic vibration data, are presented to reveal the correct functioning of the method. (c) 2007 Elsevier Ltd. All rights reserved.

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A method of testing for parametric faults of analog circuits based on a polynomial representation of fault-free function of the circuit is presented. The response of the circuit under test (CUT) is estimated as a polynomial in the applied input voltage at relevant frequencies in addition to DC. Classification or Cur is based on a comparison of the estimated polynomial coefficients with those of the fault free circuit. This testing method requires no design for test hardware as might be added to the circuit fly some other methods. The proposed method is illustrated for a benchmark elliptic filter. It is shown to uncover several parametric faults causing deviations as small as 5% from the nominal values.

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The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. Many of these approaches aim at only analyzing the chaotic nature and not its prediction. In the present study, an attempt is made to identify chaos using various techniques and prediction is also done by generating ensembles in order to quantify the uncertainty involved. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha, Mahanadi and All-India for the period 1955-2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series. Correlation dimension method is done on th phase randomized and first derivative of the data series to check whether the saturation of the dimension is due to the inherent linear correlation structure or due to low dimensional dynamics. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996-2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are done from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. (C) 2010 Elsevier Ltd. All rights reserved.

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In this paper, we describe how to analyze boundary value problems for third-order nonlinear ordinary differential equations over an infinite interval. Several physical problems of interest are governed by such systems. The seminumerical schemes described here offer some advantages over solutions obtained by using traditional methods such as finite differences, shooting method, etc. These techniques also reveal the analytic structure of the solution function. For illustrative purposes, several physical problems, mainly drawn from fluid mechanics, are considered; they clearly demonstrate the efficiency of the techniques presented here.

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In this paper, we describe how to analyze boundary value problems for third-order nonlinear ordinary differential equations over an infinite interval. Several physical problems of interest are governed by such systems. The seminumerical schemes described here offer some advantages over solutions obtained by using traditional methods such as finite differences, shooting method, etc. These techniques also reveal the analytic structure of the solution function. For illustrative purposes, several physical problems, mainly drawn from fluid mechanics, are considered; they clearly demonstrate the efficiency of the techniques presented here.

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A general asymptotic method based on the work of Krylov-Bogoliubov is developed to obtain the response of nonlinear over damped systems. A second-order system with both roots real is treated first and the method is then extended to higher-order systems. Two illustrative examples show good agreement with results obtained by numerical integration.

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A simple new series, using an expansion of the velocity profile in parabolic cylinder functions, has been developed to describe the nonlinear evolution of a steady, laminar, incompressible wake from a given arbitrary initial profile. The first term in this series is itself found to provide a very satisfactory prediction of the decay of the maximum velocity defect in the wake behind a flat plate or aft of the recirculation zone behind a symmetric blunt body. A detailed analysis, including higher order terms, has been made of the flat plate wake with a Blasius profile at the trailing edge. The same method yields, as a special case, complete results for the development of linearized wakes with arbitrary initial profile under the influence of arbitrary pressure gradients. Finally, for purposes of comparison, a simple approximate solution is obtained using momentum integral methods, and found to predict satisfactorily the decay of the maximum velocity defect. © 1970 Wolters-Noordhoff Publishing.

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Some new concepts characterizing the response of nonlinear systems are developed. These new concepts are denoted by the terms, the transient system equivalent, the response vector, and the space-phase components. This third concept is analyzed in comparison with the well-known technique of symmetrical components. The performance of a multiplicative feedback control system is represented by a nonlinear integro-differential equation; its solution is obtained by the principle of variation of parameters. The system response is treated as a vector and is resolved into its space-phase components. The individual effects of these components on the performance of the system are discussed. The suitability of the technique for the transient analysis of higher order nonlinear control systems is discussed.

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The scope of application of Laplace transforms presently limited to the study of linear partial differential equations, is extended to the nonlinear domain by this study. This has been achieved by modifying the definition of D transforms, put forth recently for the study of classes of nonlinear lumped parameter systems. The appropriate properties of the new D transforms are presented to bring out their applicability in the analysis of nonlinear distributed parameter systems.