Discrete Data Transfer Technique for Fluid-Structure Interaction

Samareh, Jamshid A.

doi:10.2514/6.2007-4309

Cited by 58 publications

(32 citation statements)

References 12 publications

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“…When aerodynamic pressure is calculated using CFD, the data transfer technique is required for the state variable conversion such as pressure onto the nodes of FE mesh because of dissimilar meshes between CFD and FEM. [21] As shown in Fig. 9, the aerodynamic load is transferred on each node of FE mesh from three nearest nodes of CFD mesh, which are found through a spatial proximity search.…”

Section: Load Generationmentioning

confidence: 99%

Development of a Physics-Based Design Framework for Aircraft Design using Parametric Modeling

Hong¹,

Park²,

Kim³

2015

International Journal of Aeronautical and Space Sciences

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Handling constantly evolving configurations of aircraft can be inefficient and frustrating to design engineers, especially true in the early design phase when many design parameters are changeable throughout trade-off studies. In this paper, a physics-based design framework using parametric modeling is introduced, which is designated as DIAMOND/AIRCRAFT and developed for structural design of transport aircraft in the conceptual and preliminary design phase. DIAMOND/AIRCRAFT can relieve the burden of labor-intensive and time-consuming configuration changes with powerful parametric modeling techniques that can manipulate ever-changing geometric parameters for external layout of design alternatives. Furthermore, the design framework is capable of generating FE model in an automated fashion based on the internal structural layout, basically a set of design parameters describing the structural members in terms of their physical properties such as location, spacing and quantities. The design framework performs structural sizing using the FE model including both primary and secondary structural levels. This physics-based approach improves the accuracy of weight estimation significantly as compared with empirical methods. In this study, combining a physics-based model with parameter modeling techniques delivers a high-fidelity design framework, remarkably expediting otherwise slow and tedious design process of the early design phase.

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Section: Load Generationmentioning

confidence: 99%

Development of a Physics-Based Design Framework for Aircraft Design using Parametric Modeling

Hong¹,

Park²,

Kim³

2015

International Journal of Aeronautical and Space Sciences

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“…The line loadsl aerodynamics are computed by integrating nondimensional pressure coefficients from the vehicle surface using the FUN3D solution. 28 Further details regarding the data transfer, the static aeroelastic solution method and FRILLS formulation are discussed elsewhere. 9 In the quasi-steady formulation the dynamic response of the vehicle can be computed by linearizing the line loads around the local static α l , β l and static generalized force G s .…”

Section: B Dynamic Aeroelastic Analysis Based On Line Loads Includinmentioning

confidence: 99%

A Quasi-Steady Flexible Launch Vehicle Stability Analysis Using Steady CFD with Unsteady Aerodynamic Enhancement

Bartels

2011

49th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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Launch vehicles frequently experience a reduced stability margin through the transonic Mach number range. This reduced stability margin is caused by an undamping of the aerodynamics in one of the lower frequency flexible or rigid body modes. Analysis of the behavior of a flexible vehicle is routinely performed with quasi-steady aerodynamic lineloads derived from steady rigid computational fluid dynamics (CFD). However, a quasi-steady aeroelastic stability analysis can be unconservative at the critical Mach numbers where experiment or unsteady computational aeroelastic (CAE) analysis show a reduced or even negative aerodynamic damping. This paper will present a method of enhancing the quasi-steady aeroelastic stability analysis of a launch vehicle with unsteady aerodynamics. The enhanced formulation uses unsteady CFD to compute the response of selected lower frequency modes. The response is contained in a time history of the vehicle lineloads. A proper orthogonal decomposition of the unsteady aerodynamic lineload response is used to reduce the scale of data volume and system identification is used to derive the aerodynamic stiffness, damping and mass matrices. The results of the enhanced quasi-static aeroelastic stability analysis are compared with the damping and frequency computed from unsteady CAE analysis and from a quasi-steady analysis. The results show that incorporating unsteady aerodynamics in this way brings the enhanced quasi-steady aeroelastic stability analysis into close agreement with the unsteady CAE analysis.

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“…25 Modes were interpolated to the surface mesh using the method developed by Samareh. 26 The BSCW dynamic analysis was performed in a two-step process. First, the steady CFD solution was obtained on the rigid body.…”

Section: Dynamic Analysismentioning

confidence: 99%

FUN3D Analyses in Support of the First Aeroelastic Prediction Workshop

Chwalowski

Heeg

2013

51st AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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This paper presents the computational aeroelastic results generated in support of the first Aeroelastic Prediction Workshop for the Benchmark Supercritical Wing (BSCW) and the HIgh REynolds Number AeroStructural Dynamics (HIRENASD) configurations and compares them to the experimental data. The computational results are obtained using FUN3D, an unstructured grid Reynolds-averaged Navier-Stokes solver developed at NASA Langley Research Center. The analysis results for both configurations include aerodynamic coefficients and surface pressures obtained for steady-state or static aeroelastic equilibrium (BSCW and HIRENASD, respectively) and for unsteady flow due to a pitching wing (BSCW) or modally-excited wing (HIRENASD). Frequency response functions of the pressure coefficients with respect to displacement are computed and compared with the experimental data. For the BSCW, the shock location is computed aft of the experimentallylocated shock position. The pressure distribution upstream of this shock is in excellent agreement with the experimental data, but the pressure downstream of the shock in the separated flow region does not match as well. For HIRENASD, very good agreement between the numerical results and the experimental data is observed at the mid-span wing locations.

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Discrete Data Transfer Technique for Fluid-Structure Interaction

Cited by 58 publications

References 12 publications

Development of a Physics-Based Design Framework for Aircraft Design using Parametric Modeling

Development of a Physics-Based Design Framework for Aircraft Design using Parametric Modeling

A Quasi-Steady Flexible Launch Vehicle Stability Analysis Using Steady CFD with Unsteady Aerodynamic Enhancement

FUN3D Analyses in Support of the First Aeroelastic Prediction Workshop

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