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

The focus of this paper is on acceleration of strong partitioned coupling algorithms for fluid-structure interaction. Strong partitioned coupling requires the solution of a coupled problem at each time step during the simulation. Hereto, an interface residual is defined such that the kinematic and dynamic interface conditions on the fluid-structure interface are satisfied when it amounts to zero. Subsequently, the coupled problem is formulated as a minimization problem of the interface residual which can efficiently be performed using Newton’s method. However, Newton’s method cannot be applied when the fluid and structure solvers are considered black-boxes since the Jacobian of the interface residual is not available. For this reason, Quasi-Newton methods were developed that approximate either the Jacobian or the inverse Jacobian of the interface residual directly from input/output information. In this contribution we present a new algorithm that uses a technique from multifidelity optimization – called space-mapping – to efficiently perform the minimization of the interface residual. The space-mapping technique exploits a computationally inexpensive lowfidelity model in order to accelerate an expensive high-fidelity model using black-box information only. The space-mapping algorithm is applied to the supersonic panel flutter problem in order to demonstrate its effectiveness. The speedup – defined with respect to a Quasi-Newton algorithm – is found to be 1-1.5 for typical time step sizes. It is expected that higher speedups can be obtained when problems are considered that require strong coupling as the time step decreases, e.g. due to the added mass effect when the structure is in interaction with an incompressible fluid.

/pdf/accelerated-partitioned-fluid-structure-interaction-using-4tz0i88foq.pdf

Accelerated partitioned fluid-structure interaction using space-mapping

An efficient uncertainty quantification method for unsteady problems is presented in order to achieve a constant accuracy in time for a constant number of samples. The approach is applied to the aeroelastic problems of a transonic airfoil flutter system and the AGARD 445.6 wing benchmark with uncertainties in the flow and the structure.

Efficient uncertainty quantification in unsteady aeroelastic simulations

It is recognized in the engineering community that there is an increasing need to move towards unsteady simulations in computational fluid dynamics. This trend also dictates an increasing application of uncertainty quantification methods to unsteady problems. In this paper, an Unsteady Adaptive Stochastic Finite Elements method based on interpolation at constant phase (UASFE-cp) is introduced for resolving the effect of random parameters in unsteady simulations. It achieves a constant accuracy in time with a constant number of samples, in contrast with the usually fast increasing number of samples required by other non-intrusive methods. Results for the stochastic bifurcation behavior of an elastically mounted airfoil with nonlinearity in the flow and the structure are presented.

/pdf/unsteady-adaptive-stochastic-finite-elements-for-aeroelastic-3e5wbz2atf.pdf

Unsteady Adaptive Stochastic Finite Elements for Aeroelastic Systems with Randomness

The long-term periodic limit cycle oscillation (LCO) response of unsteady uid-structure interaction systems can be sensitive to physical input variations. Polynomial Chaos expansions can however fail to predict the eect of uncertainties in long-term time integration problems. In this paper, a non-intrusive Polynomial Chaos formulation for modeling the eect 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 utter model and the uid-structure interaction of an elastically-mounted cylinder are presented.

Quantifying the eect of physical uncertainties in unsteady uid-structure interaction problems

A robust and efficient uncertainty quantification method is presented for resolving the effect of uncertainty on the behavior of multi-physics systems. The extrema diminishing method in probability space maintains a bounded error due to the interpolation of deterministic samples at constant phase in a transonic airfoil flutter problem.

/pdf/a-robust-and-efficient-uncertainty-quantification-method-for-1e763s0dv0.pdf

Hester Bijl

Papers

Accelerated partitioned fluid-structure interaction using space-mapping

Efficient uncertainty quantification in unsteady aeroelastic simulations

Unsteady Adaptive Stochastic Finite Elements for Aeroelastic Systems with Randomness

Quantifying the eect of physical uncertainties in unsteady uid-structure interaction problems

A robust and efficient uncertainty quantification method for coupled fluid-structure interaction problems