다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Statistics for Spatial Data.

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

Adaptive sparse polynomial chaos expansion based on least angle regression

To improve the performance of particle image velocimetry in measuring instantaneous velocity fields, direct cross-correlation of image fields can be used in place of auto-correlation methods of interrogation of double- or multiple-exposure recordings. With improved speed of photographic recording and increased resolution of video array detectors, cross-correlation methods of interrogation of successive single-exposure frames can be used to measure the separation of pairs of particle images between successive frames. By knowing the extent of image shifting used in a multiple-exposure and by a priori knowledge of the mean flow-field, the cross-correlation of different sized interrogation spots with known separation can be optimized in terms of spatial resolution, detection rate, accuracy and reliability.

Theory of cross-correlation analysis of PIV images : Image analysis as measuring technique in flows

Slotted multi-element cone gurations are widely used because they are very effective in increasing themaximum lift of airfoils during takeoff and landing. However, when stall occurs in the leading-edge region of one of the elements,theoutcomeisa suddenanddangerousdropinperformanceofthewholecone guration.Theresultsofthe experimental verie cation of a computer-designed single-slotted e ap are presented. Many realistic cone gurations, including the computed optimum, were tested and compared to the numerical predictions. For a number of these cone gurations, sudden leading-edgestall due to thebursting of a laminarbubblewasdetected on the e ap, followed byseverestallhysteresis.Presentnumericaldesigncodesdo nothelpthedesignermuchinpredictingthisimportant phenomenon, and wind-tunnel testing remains necessary. Therefore, there is a need for better bubble bursting prediction methods. A possible direction for improvement is discussed, focusing on the unsteadiness of the e ow. Nomenclature Cd = drag coefe cient Cl = lift coefe cient Clmax = maximum lift coefe cient Cp = pressure coefe cient c = aerodynamic chord with e ap nested Rk = ree nement ratio Tu = freestream turbulence level, p u 02 =V U = uncertainty V = velocity x; y = coordinates ® = angle of attack ± = displacement thickness µ = momentum thickness

Bubble Bursting and Stall Hysteresis on Single-Slotted Flap High-Lift Configuration

The long-term periodic limit cycle oscillation (LCO) response of unsteady fluid-structure interaction systems can be sensitive to physical input variations. Polynomial Chaos expansions can however fail to predict the effect of uncertainties in long-term time integration problems. In this paper, a non-intrusive Polynomial Chaos formulation for modeling the effect of uncertainties on the periodic response of dynamical systems is proposed. It is based on the application of Probabilistic Collocation (PC) onto a time-independent parametrization of the periodic response of the deterministic realizations, which is referred to as Probabilistic Collocation for limit cycle oscillations (PCLCO). The time-independent parametrization enables PCLCO to resolve the asymptotic stochastic behavior of dynamical systems successfully. Applications to a two-degree-of-freedom airfoil flutter model and the fluid-structure interaction of an elastically-mounted cylinder are presented.

Quantifying the effect of physical uncertainties in unsteady fluid-structure interaction problems

For reliable computational predictions of transonic flows, it is important to resolve the significant effects of physical variations on the shock wave locations. The resulting discontinuities in probability space require extremum diminishing uncertainty quantification to avoid overshoots and undershoots in the response surface approximation. In this paper, the extremum diminishing concept in probability space is extended to infinite parameter domains using inverse distance weighting interpolation of deterministic samples. Based on results for three analytical test functions, the combination of Halton sampling and power parameter limit value c → ∞ is selected. The approach is employed to model spatial-free-stream velocity fluctuations in the highly sensitive transonic AGARD 445.6 wing test case in an up to ten-dimensional probability space. The 0.5% input variations are amplified to a coefficient of variation for the wave drag of cvD = 9.58% in combination with an increase of the mean drag by 1.75% compared to the deterministic value.

Transonic velocity fluctuations simulated using extremum diminishing uncertainty quantification based on inverse distance weighting

Summary
Fluid–structure interactions (FSI) play a crucial role in many engineering fields. However, the computational cost associated with high-fidelity aeroelastic models currently precludes their direct use in industry, especially for strong interactions. The strongly coupled segregated problem—that results from domain partitioning—can be interpreted as an optimization problem of a fluid–structure interface residual. Multi-fidelity optimization techniques can therefore directly be applied to this problem in order to obtain the solution efficiently. In previous work, it is already shown that aggressive space mapping (ASM) can be used in this context. In this contribution, we extend the research towards the use of space mapping for FSI simulations. We investigate the performance of two other approaches, generalized space mapping and output space mapping, by application to both compressible and incompressible 2D problems. Moreover, an analysis of the influence of the applied low-fidelity model on the achievable speedup is presented. The results indicate that output space mapping is a viable alternative to ASM when applied in the context of solver coupling for partitioned FSI, showing similar performance as ASM and resulting in reductions in computational cost up to 50% with respect to the reference quasi-Newton method. Copyright © 2015 John Wiley & Sons, Ltd.

We apply Ordinary Kriging to predict 75,000 terrain survey data from a randomly sampled subset of < 2500 observations. Since such a Kriging prediction requires a considerable amount of CPU time, we aim to reduce its computational cost. In a conventional approach, the cost of the Kriging analysis would be dominated by the optimization routine required to find the maximum likelihood, which provides an estimate of the correlation ranges. We propose to transform the optimization problem to the frequency domain, such that the cost of the optimization is now dominated by that of a single Fourier transform required to find the power spectrum of the observations, as a result of which the computational cost is now virtually independent of the number of optimization steps. For the present application, we find that the proposed approach is as accurate as the conventional approach for a sample size of 100 or more. The CPU time increases with the number of optimization steps for the conventional approach, while it is virtually constant for the proposed approach.

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Hester Bijl

Papers

Bubble Bursting and Stall Hysteresis on Single-Slotted Flap High-Lift Configuration

Quantifying the effect of physical uncertainties in unsteady fluid-structure interaction problems

Transonic velocity fluctuations simulated using extremum diminishing uncertainty quantification based on inverse distance weighting

Analysis of space mapping algorithms for application to partitioned fluid©structure interaction problems

Fast maximum likelihood estimate of the Kriging correlation range in the frequency domain