30 resultados para second-order inelastic analysis


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Semi-implicit, second order temporal and spatial finite volume computations of the flow in a differentially heated rotating annulus are presented. For the regime considered, three cyclones and anticyclones separated by a relatively fast moving jet of fluid or "jet stream" are predicted. Two second order methods are compared with, first order spatial predictions, and experimental measurements. Velocity vector plots are used to illustrate the predicted flow structure. Computations made using second order central differences are shown to agree best with experimental measurements, and to be stable for integrations over long time periods (> 1000s). No periodic smoothing is required to prevent divergence.

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This paper presents an achievable second-order rate region for the discrete memoryless multiple-access channel. The result is obtained using a random-coding ensemble in which each user's codebook contains codewords of a fixed composition. It is shown that this ensemble performs at least as well as i.i.d. random coding in terms of second-order asymptotics, and an example is given where a strict improvement is observed. © 2013 IEEE.

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The dynamic analysis of a deepwater floating platform and the associated mooring/riser system should ideally be fully coupled to ensure a reliable response prediction. It is generally held that a time domain analysis is the only means of capturing the various coupling and nonlinear effects accurately. However, in recent work it has been found that for an ultra-deepwater floating system (2000m water depth), the highly efficient frequency domain approach can provide highly accurate response predictions. One reason for this is the accuracy of the drag linearization procedure over both first and second order motions, another reason is the minimal geometric nonlinearity displayed by the mooring lines in deepwater. In this paper, the aim is to develop an efficient analysis method for intermediate water depths, where both mooring/vessel coupling and geometric nonlinearity are of importance. It is found that the standard frequency domain approach is not so accurate for this case and two alternative methods are investigated. In the first, an enhanced frequency domain approach is adopted, in which line nonlinearities are linearized in a systematic way. In the second, a hybrid approach is adopted in which the low frequency motion is solved in the time domain while the high frequency motion is solved in the frequency domain; the two analyses are coupled by the fact that (i) the low frequency motion affects the mooring line geometry for the high frequency motion, and (ii) the high frequency motion affects the drag forces which damp the low frequency motion. The accuracy and efficiency of each of the methods are systematically compared. Copyright © 2007 by ASME.

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An existing hybrid finite element (FE)/statistical energy analysis (SEA) approach to the analysis of the mid- and high frequency vibrations of a complex built-up system is extended here to a wider class of uncertainty modeling. In the original approach, the constituent parts of the system are considered to be either deterministic, and modeled using FE, or highly random, and modeled using SEA. A non-parametric model of randomness is employed in the SEA components, based on diffuse wave theory and the Gaussian Orthogonal Ensemble (GOE), and this enables the mean and variance of second order quantities such as vibrational energy and response cross-spectra to be predicted. In the present work the assumption that the FE components are deterministic is relaxed by the introduction of a parametric model of uncertainty in these components. The parametric uncertainty may be modeled either probabilistically, or by using a non-probabilistic approach such as interval analysis, and it is shown how these descriptions can be combined with the non-parametric uncertainty in the SEA subsystems to yield an overall assessment of the performance of the system. The method is illustrated by application to an example built-up plate system which has random properties, and benchmark comparisons are made with full Monte Carlo simulations. © 2012 Elsevier Ltd. All rights reserved.

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This paper deals with the experimental evaluation of a flow analysis system based on the integration between an under-resolved Navier-Stokes simulation and experimental measurements with the mechanism of feedback (referred to as Measurement-Integrated simulation), applied to the case of a planar turbulent co-flowing jet. The experiments are performed with inner-to-outer-jet velocity ratio around 2 and the Reynolds number based on the inner-jet heights about 10000. The measurement system is a high-speed PIV, which provides time-resolved data of the flow-field, on a field of view which extends to 20 jet heights downstream the jet outlet. The experimental data can thus be used both for providing the feedback data for the simulations and for validation of the MI-simulations over a wide region. The effect of reduced data-rate and spatial extent of the feedback (i.e. measurements are not available at each simulation time-step or discretization point) was investigated. At first simulations were run with full information in order to obtain an upper limit of the MI-simulations performance. The results show the potential of this methodology of reproducing first and second order statistics of the turbulent flow with good accuracy. Then, to deal with the reduced data different feedback strategies were tested. It was found that for small data-rate reduction the results are basically equivalent to the case of full-information feedback but as the feedback data-rate is reduced further the error increases and tend to be localized in regions of high turbulent activity. Moreover, it is found that the spatial distribution of the error looks qualitatively different for different feedback strategies. Feedback gain distributions calculated by optimal control theory are presented and proposed as a mean to make it possible to perform MI-simulations based on localized measurements only. So far, we have not been able to low error between measurements and simulations by using these gain distributions.

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The Statistics Anxiety Rating Scale (STARS) was adapted into German to examine its psychometric properties (n = 400). Two validation studies (n = 66, n = 96) were conducted to examine its criterion-related validity. The psychometric properties of the questionnaire were very similar to those previously reported for the original English version in various countries and other language versions. Confirmatory factor analysis indicated 2 second-order factors: One was more closely related to anxiety and the other was more closely related to negative attitudes toward statistics. Predictive validity of the STARS was shown both in an experimental exam-like situation in the laboratory and during a real examination situation. Taken together, the findings indicate that statistics anxiety as assessed by the STARS is a useful construct that is more than just an expression of a more general disposition to anxiety.

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We propose an algorithm for solving optimization problems defined on a subset of the cone of symmetric positive semidefinite matrices. This algorithm relies on the factorization X = Y Y T , where the number of columns of Y fixes an upper bound on the rank of the positive semidefinite matrix X. It is thus very effective for solving problems that have a low-rank solution. The factorization X = Y Y T leads to a reformulation of the original problem as an optimization on a particular quotient manifold. The present paper discusses the geometry of that manifold and derives a second-order optimization method with guaranteed quadratic convergence. It furthermore provides some conditions on the rank of the factorization to ensure equivalence with the original problem. In contrast to existing methods, the proposed algorithm converges monotonically to the sought solution. Its numerical efficiency is evaluated on two applications: the maximal cut of a graph and the problem of sparse principal component analysis. © 2010 Society for Industrial and Applied Mathematics.

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In the present paper we consider second order compact upwind schemes with a space split time derivative (CABARET) applied to one-dimensional compressible gas flows. As opposed to the conventional approach associated with incorporating adjacent space cells we use information from adjacent time layer to improve the solution accuracy. Taking the first order Roe scheme as the basis we develop a few higher (i.e. second within regions of smooth solutions) order accurate difference schemes. One of them (CABARET3) is formulated in a two-time-layer form, which makes it most simple and robust. Supersonic and subsonic shock-tube tests are used to compare the new schemes with several well-known second-order TVD schemes. In particular, it is shown that CABARET3 is notably more accurate than the standard second-order Roe scheme with MUSCL flux splitting.