• 한국전산유체공학회:학술대회논문집
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• 2009.04a
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• pp.19-19
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• 2009

Dynamic Stall is a flow phenomenon which occurs on the retreating side of helicopter rotor blades during forward flight. It also occurs on blades of stall regulated wind turbines under yawing conditions as well as during gust loads. Time scales occurring during this process are comparable on both helicopter and wind turbine blades. Dynamic Stall limits the speed of the helicopter and its manoeuvrability and limits the amount of power production of wind turbines. Extensive numerical as well as experimental investigations have been carried out recently to get detailed insight into the very complex flow structures of the Dynamic Stall process. Numerical codes have to be based on the full equations, i.e. the Navier-Stokes equations to cover the scope of the problems involved: Time dependent flow, unsteady flow separation, vortex development and shedding, compressibility effects, turbulence, transition and 3D-effects, etc. have to be taken into account. In addition to the numerical treatment of the Dynamic Stall problem suitable wind tunnel experiments are inevitable. Comparisons of experimental data with calculated results show us the state of the art and validity of the CFD-codes and the necessity to further improve calculation procedures. In the present paper the phenomenon of Dynamic Stall will be discussed first. This discussion is followed by comparisons of some recently obtained experimental and numerical results for an oscillating helicopter airfoil under Dynamic Stall conditions. From the knowledge base of the Dynamic Stall Problems, the next step can be envisaged: to control Dynamic Stall. The present discussion will address two different Dynamic Stall control methodologies: the Nose-Droop concept and the application of Leading Edge Vortex Generators (LEVoG's) as examples of active and passive control devices. It will be shown that experimental results are available but CFD-data are only of limited comparison. A lot of future work has to be done in CFD-code development to fill this gap. Here mainly 3D-effects as well as improvements of both turbulence and transition modelling are of major concern.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.1-1
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• 2003

In this talk, a reduced-order modeling methodology based on centroidal Voronoi tessellations (CVT's)is introduced. CVT's are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi cells. The discrete data sets, CVT's are closely related to the h-means clustering techniques. Even with the use of good mesh generators, discretization schemes, and solution algorithms, the computational simulation of complex, turbulent, or chaotic systems still remains a formidable endeavor. For example, typical finite element codes may require many thousands of degrees of freedom for the accurate simulation of fluid flows. The situation is even worse for optimization problems for which multiple solutions of the complex state system are usually required or in feedback control problems for which real-time solutions of the complex state system are needed. There hava been many studies devoted to the development, testing, and use of reduced-order models for complex systems such as unsteady fluid flows. The types of reduced-ordered models that we study are those attempt to determine accurate approximate solutions of a complex system using very few degrees of freedom. To do so, such models have to use basis functions that are in some way intimately connected to the problem being approximated. Once a very low-dimensional reduced basis has been determined, one can employ it to solve the complex system by applying, e.g., a Galerkin method. In general, reduced bases are globally supported so that the discrete systems are dense; however, if the reduced basis is of very low dimension, one does not care about the lack of sparsity in the discrete system. A discussion of reduced-ordering modeling for complex systems such as fluid flows is given to provide a context for the application of reduced-order bases. Then, detailed descriptions of CVT-based reduced-order bases and how they can be constructed of complex systems are given. Subsequently, some concrete incompressible flow examples are used to illustrate the construction and use of CVT-based reduced-order bases. The CVT-based reduced-order modeling methodology is shown to be effective for these examples and is also shown to be inexpensive to apply compared to other reduced-order methods.

• Wind and Structures
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• v.34 no.1
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• pp.127-136
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• 2022

In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

• Wind and Structures
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• v.20 no.4
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• pp.549-564
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• 2015

The three-dimensional unsteady incompressible Reynolds-averaged Navier-Stokes equations and k-${\varepsilon}$ double equations turbulent model were used to investigate the effect on the measurements of anemometers due to a passing high-speed train. Sliding mesh technology in Fluent was utilized to treat the moving boundary problem. The high-speed train considered in this paper was with bogies and inter-carriage gaps. Combined with the results of the wind tunnel test in a published paper, the accuracy of the present numerical method was validated to be used for further study. In addition, the difference of slipstream between three-car and eight-car grouping models was analyzed, and a series of numerical simulations were carried out to study the influences of the anemometer heights, the train speeds, the crosswind speeds and the directions of the induced slipstream on the measurements of the anemometers. The results show that the influence factors of the train-induced slipstream are the passing head car and tail car. Using the three-car grouping model to analyze the train-induced flow is reasonable. The maxima of horizontal slipstream velocity tend to reduce as the height of the anemometer increases. With the train speed increasing, the relationship between $V_{train}$ and $V_{induced\;slipstream}$ can be expressed with linear increment. In the absence of natural wind conditions, from the head car arriving to the tail car leaving, the induced wind direction changes about $330^{\circ}$, while under the crosswind condition the wind direction fluctuates around $-90^{\circ}$. With the crosswind speed increasing, the peaks of $V_X,{\mid}V_{XY}-V_{wind}{\mid}$ of the head car and that of $V_X$ of the tail car tend to enlarge. Thus, when anemometers are installed along high-speed railways, it is important to study the effect on the measurements of anemometers due to the train-induced slipstream.