Multivariate interpolation for fluid-structure-interaction problems using radial basis functions

Beckert, Armin; Wendland, Holger

doi:10.1016/s1270-9638(00)01087-7

Cited by 296 publications

(175 citation statements)

References 10 publications

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“…R expresses the correlations between all observed data locations and r stands for the correlations between the observed data locations and a locationz. These correlations are calculated using the Wendland's C4 radial basis function (RBF) 23) in this study. Hyper-parameters to define the width of the RBF for each input variable are estimated by maximizing the likelihood (joint probability) function of the given samples.…”

Section: Inexpensive Monte-carlo Simulation (Imcs) Onmentioning

confidence: 99%

Stochastic Drag Analysis via Polynomial Chaos Uncertainty Quantification

Yamazaki

2015

Trans. Japan Soc. Aero. S Sci.

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In this paper, uncertainty quantification approaches are applied to an aerodynamic uncertainty quantification problem with a far-field drag breakdown approach. Two uncertainty quantification approaches, a non-intrusive polynomial chaos approach and an inexpensive Monte-Carlo simulation approach on a response surface model are compared and investigated for more advanced aerodynamic uncertainty quantification. Using the drag breakdown approach, total drag of a body can be decomposed into three physical and one unphysical drag components: wave, viscous, induced and spurious drag components. The drag source distribution can also be visualized on the flowfield using this approach. An uncertainty quantification problem of two-dimensional airfoil with four uncertain input variables is analyzed with the drag breakdown approach to extract more aerodynamic design information about its uncertainty propagation.

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Section: Inexpensive Monte-carlo Simulation (Imcs) Onmentioning

confidence: 99%

Stochastic Drag Analysis via Polynomial Chaos Uncertainty Quantification

Yamazaki

2015

Trans. Japan Soc. Aero. S Sci.

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“…where φ is a conditionally positive de¦nite function of a certain order m and p is a polynomial of degree m − 1 [4,5]. As is made by many authors, only m = 2 is considered in this work.…”

Section: Radial Basis Functions Methodsmentioning

confidence: 99%

Variable transfer methods for fluid-structure interaction computations with staggered solvers

Vaassen¹,

Klapka²,

Leonard³

et al. 2009

Progress in Propulsion Physics

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This paper intends to study methods that have been tested to transfer variables from one skin mesh to another (the two meshes being nonconform) in order to compute §uid structure interaction (FSI) problems with staggered solvers. The methods are a contact elements method developed by Stam, and di¨erent radial basis functions methods. The structure code is OOFELIE R developed at Open-Engineering (Belgium) and the §uid code is FINE TM /Hexa developed at Numeca International (Belgium). The paper presents the performances of the methods on a simple variable transfer, and testcases that have been performed with the solver developed by the two companies.

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“…It is a common approach in the literature to apply the principle of virtual work [1,46,49,53] to define a conservative transfer scheme. Brown [52] and Farhat [1] have introduced projection methods that apply the conservation of virtual work to the problem of transferring load and deformations in FSI problems on non-matching meshes.…”

Section: Spatial Couplingmentioning

confidence: 99%

Assessment of the Fluid-Structure Interaction Capabilities for Aeronautical Applications of the Open-Source Solver Su2.

Sánchez¹,

Kline²,

Thomas³

et al. 2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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Abstract. We report on an international effort to develop an open-source computational environment for high-fidelity fluid-structure interaction analysis. In particular, we will focus on verification of the implementation for application in computational aeroelasticity. The capabilities of the SU2 code for aeroelastic analysis have been further enhanced both by developing natively embedded tools for the study of largely deformable solids, and by wrapping it using Python tools for an improved communication with external solvers. Both capabilities will be demonstrated on relevant test cases, including rigid-airfoil solutions with indicial functions, the Isogai Wing Section, test cases from the AIAA 2nd Aeroelastic Prediction Workshop, and the vortex-induced vibrations of a flexible cantilever in the wake of a square cylinder. Results show very good performance both in terms of accuracy and computational efficiency. The modularity and versatility of the baseline suite allows for a flexible framework for multidisciplinary computational analysis. The software libraries have been freely shared with the community to encourage further engagement in the improvement, validation and further development of this open-source project.

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Multivariate interpolation for fluid-structure-interaction problems using radial basis functions

Cited by 296 publications

References 10 publications

Stochastic Drag Analysis via Polynomial Chaos Uncertainty Quantification

Stochastic Drag Analysis via Polynomial Chaos Uncertainty Quantification

Variable transfer methods for fluid-structure interaction computations with staggered solvers

Assessment of the Fluid-Structure Interaction Capabilities for Aeronautical Applications of the Open-Source Solver Su2.

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