Panel Methods in Computational Fluid Dynamics

Hess, John L.

doi:10.1146/annurev.fl.22.010190.001351

Cited by 180 publications

(77 citation statements)

References 18 publications

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“…Various techniques have been used to analyse and visualize the fluid parameters of the study. Early visualizations made use of glyphs to represent vector fields in the data [40]. Later, line integral convolution (LIC) and texture based approaches [41] were used to depict realistic flow.…”

Section: Post-processingmentioning

confidence: 99%

Bringing out Fluids Experiments from Laboratory to In Silico – A Journey of Hundred Years

Kumar¹,

Philominathan²

2011

AJCM

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By making use of the developments in the fields of numerical methods, computational technology and fluid dynamics models, computational fluid dynamics (CFD) progress forward to play an active role today in various industrial, academic and research activities. In many cases, CFD simulations replace expensive and time consuming laboratory experiments successfully by allowing engineers and scientists to capture pressure, velocity and force distributions. Researchers are now able to test various theoretical conditions unavailable in the laboratory and CFD studies help them to get deeper insights on existing theories. The century-old history started just to solve some stress analysis problems numerically and today CFD methodology is being applied not only in fluid dynamics also in chemical engineering, mineral processing, fire engineering, sports, medical imaging and even in acoustics. This paper reviews the growth of CFD as a discipline and discusses its contemporary methodology.

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Section: Post-processingmentioning

confidence: 99%

Bringing out Fluids Experiments from Laboratory to In Silico – A Journey of Hundred Years

Kumar¹,

Philominathan²

2011

AJCM

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“…The RK2 scheme is e ciently programed as follows: Euler predictor, trapezoidal rule corrector. 4 The BEM code so far For the BEM method so far, we use the formulation with triangular panels of uniform strength 12,13]. No optimization of the iterative method has beencarried out so far.…”

Section: Time Integrationmentioning

confidence: 99%

“…A fast oct-tree code, originally developed for three-dimensional N-body gravitational problems 26{28, 32{34] has been modi ed into (1) a fast N-vortex code for viscous and inviscid vortex ow computations 29] using the regularized vortex particle method (= vortex element method, VEM) 19,20,25, 36{40] combined with the particle strength exchange scheme for viscous di usion 4,21], and (2) a fast N-panel code for solving boundary integral equations in potential ow aerodynamics 41] using the boundary element method (BEM, = panel method) 12,13,15]. The core of the fast tree code remains essentially unchanged between the di erent application codes: gravitation, VEM, BEM, etc.…”

Section: Introductionmentioning

confidence: 99%

Application of fast parallel and sequential tree codes to computing three-dimensional flows with the vortex element and boundary element methods

et al. 1996

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A fast parallel oct-tree code originally developed for three-dimensional N-body gravitational simulations was modi ed into (1) a fast N-vortex code for viscous and inviscid vortex ow computations using the regularized vortex particle method (VEM), and (2) a fast N-panel code for solving boundary integral equations in potential ow aerodynamics using the boundary element method (BEM). The core of the fast tree code remains essentially unchanged between the different application codes: gravitation, VEM, BEM, etc. Only the modules that actually encode the physical model are changed. Particular attention is given to controlling the error introduced by the use of multipole expansions to represent the eld produced by groups of elements, i.e., the tree code error. In particular, the acceptable error bound for use of any m ultipole expansion approximation is a run-time parameter. Program outputs include statistics on the errors 226with sample computational results. For the VEM method, a high order particle redistribution scheme has been incorporated, in an e cient w ay, i n to the parallel tree code. It is applied, if necessary, to ensure that the core overlapping condition remains satis ed in long time computations. In addition, two di erent relaxation schemes have also been incorporated and partially tested. Such s c hemes are applied, if necessary, to ensure that the particle representation of the vorticity eld remains a good representation of the true divergence free vorticity eld in long time computations.

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“…The mass conservation equation can be then rewritten as a Laplace equation for the velocity potential. The family of codes includes the most widely adopted vortex lattice (VLM) and panel methods (see [8] and [4], respectively, for a comprehensive review of the two methods). Both methods involve similar computational steps.…”

Section: Introductionmentioning

confidence: 99%

Accelerating low-fidelity aerodynamic codes on multi- and many-core architectures

Chrust

Laurendeau

Ostiguy³

2015

J Supercomput

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Vortex lattice and panel methods belong to a broad family of aerodynamic codes based on potential flow theory. They are used in preliminary aerodynamic studies in early stages of aircraft design where hundreds of thousands candidate configurations are analyzed. In this paper, we describe their efficient implementation on modern multiand many-core architectures. We show how to bridge the 'ninja gap', defined as the performance gap between an unoptimized C/C++ code and best optimized CPU code. We port the Vortex Lattice Method to a Graphics Processing Unit using the OpenACC standard. An elegant solution for implementation of data movements for C++ classes is also presented.

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Panel Methods in Computational Fluid Dynamics

Cited by 180 publications

References 18 publications

Bringing out Fluids Experiments from Laboratory to In Silico – A Journey of Hundred Years

Bringing out Fluids Experiments from Laboratory to In Silico – A Journey of Hundred Years

Application of fast parallel and sequential tree codes to computing three-dimensional flows with the vortex element and boundary element methods

Accelerating low-fidelity aerodynamic codes on multi- and many-core architectures

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