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Wolfgang Schröder

Bio: Wolfgang Schröder is an academic researcher from RWTH Aachen University. The author has contributed to research in topics: Turbulence & Reynolds number. The author has an hindex of 44, co-authored 490 publications receiving 8224 citations. Previous affiliations of Wolfgang Schröder include Technical University of Berlin & German Aerospace Center.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a family of acoustic perturbation equations for the simulation of flow-induced acoustic fields in time and space is derived, which are excited by source terms determined from a simulation of the compressible or the incompressible flow problem.

584 citations

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TL;DR: In this paper, large-eddy simulations of spatially developing planar turbulent jets are performed using a compact finite-difference scheme of sixth-order and an advective upstream splitting method-based method of second-order accuracy.

264 citations

Journal ArticleDOI
TL;DR: In this article, a hybrid method is applied to predict trailing edge noise based on a large eddy simulation (LES) of the compressible flow problem and acoustic perturbation equations (APE) for the time-dependent simulation of the acoustic field.

176 citations

Journal ArticleDOI
TL;DR: This outcome analysis of patients with low comorbidity undergoing ttMIE may serve as a reference to evaluate surgical performance in major esophageal resection.
Abstract: Objective:To define “best possible” outcomes in total minimally invasive transthoracic esophagectomy (ttMIE).Background:TtMIE, performed by experts in patients with low comorbidity, may serve as a benchmark procedure for esophagectomy.Patients and Methods:From a cohort of 1057 ttMIE, performed over

174 citations

Journal ArticleDOI
TL;DR: An accurate moving boundary formulation based on the varying discretization operators yielding a cut-cell method which avoids discontinuities in the hydrodynamic forces exerted on the moving boundary is developed.

170 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, a tomographic particle image velocimetry (tomographic-PIV) system based on the illumination, recording and reconstruction of tracer particles within a 3D measurement volume is described.
Abstract: This paper describes the principles of a novel 3D PIV system based on the illumination, recording and reconstruction of tracer particles within a 3D measurement volume The technique makes use of several simultaneous views of the illuminated particles and their 3D reconstruction as a light intensity distribution by means of optical tomography The technique is therefore referred to as tomographic particle image velocimetry (tomographic-PIV) The reconstruction is performed with the MART algorithm, yielding a 3D array of light intensity discretized over voxels The reconstructed tomogram pair is then analyzed by means of 3D cross-correlation with an iterative multigrid volume deformation technique, returning the three-component velocity vector distribution over the measurement volume The principles and details of the tomographic algorithm are discussed and a parametric study is carried out by means of a computer-simulated tomographic-PIV procedure The study focuses on the accuracy of the light intensity field reconstruction process The simulation also identifies the most important parameters governing the experimental method and the tomographic algorithm parameters, showing their effect on the reconstruction accuracy A computer simulated experiment of a 3D particle motion field describing a vortex ring demonstrates the capability and potential of the proposed system with four cameras The capability of the technique in real experimental conditions is assessed with the measurement of the turbulent flow in the near wake of a circular cylinder at Reynolds 2,700

1,159 citations

Journal ArticleDOI
TL;DR: A theoretical framework in which dynamic mode decomposition is defined as the eigendecomposition of an approximating linear operator, which generalizes DMD to a larger class of datasets, including nonsequential time series, and shows that under certain conditions, DMD is equivalent to LIM.
Abstract: Originally introduced in the fluid mechanics community, dynamic mode decomposition (DMD) has emerged as a powerful tool for analyzing the dynamics of nonlinear systems. However, existing DMD theory deals primarily with sequential time series for which the measurement dimension is much larger than the number of measurements taken. We present a theoretical framework in which we define DMD as the eigendecomposition of an approximating linear operator. This generalizes DMD to a larger class of datasets, including nonsequential time series. We demonstrate the utility of this approach by presenting novel sampling strategies that increase computational efficiency and mitigate the effects of noise, respectively. We also introduce the concept of linear consistency, which helps explain the potential pitfalls of applying DMD to rank-deficient datasets, illustrating with examples. Such computations are not considered in the existing literature, but can be understood using our more general framework. In addition, we show that our theory strengthens the connections between DMD and Koopman operator theory. It also establishes connections between DMD and other techniques, including the eigensystem realization algorithm (ERA), a system identification method, and linear inverse modeling (LIM), a method from climate science. We show that under certain conditions, DMD is equivalent to LIM.

1,067 citations

Journal ArticleDOI
01 Jan 1957-Nature
TL;DR: The Structure of Turbulent Shear Flow by Dr. A.Townsend as mentioned in this paper is a well-known work in the field of fluid dynamics and has been used extensively in many applications.
Abstract: The Structure of Turbulent Shear Flow By Dr. A. A. Townsend. Pp. xii + 315. 8¾ in. × 5½ in. (Cambridge: At the University Press.) 40s.

1,050 citations

01 Apr 1992
TL;DR: In this paper, the authors proposed a monotone integrated large eddy simulation approach, which incorporates a form of turbulence modeling applicable when the large-scale flows of interest are intrinsically time dependent, thus throwing common statistical models into question.
Abstract: Fluid dynamic turbulence is one of the most challenging computational physics problems because of the extremely wide range of time and space scales involved, the strong nonlinearity of the governing equations, and the many practical and important applications. While most linear fluid instabilities are well understood, the nonlinear interactions among them makes even the relatively simple limit of homogeneous isotropic turbulence difficult to treat physically, mathematically, and computationally. Turbulence is modeled computationally by a two-stage bootstrap process. The first stage, direct numerical simulation, attempts to resolve the relevant physical time and space scales but its application is limited to diffusive flows with a relatively small Reynolds number (Re). Using direct numerical simulation to provide a database, in turn, allows calibration of phenomenological turbulence models for engineering applications. Large eddy simulation incorporates a form of turbulence modeling applicable when the large-scale flows of interest are intrinsically time dependent, thus throwing common statistical models into question. A promising approach to large eddy simulation involves the use of high-resolution monotone computational fluid dynamics algorithms such as flux-corrected transport or the piecewise parabolic method which have intrinsic subgrid turbulence models coupled naturally to the resolved scales in the computed flow. The physical considerations underlying and evidence supporting this monotone integrated large eddy simulation approach are discussed.

849 citations