Fluid-Thermal Response of Spherical Dome Under a Mach 6.59 Laminar Boundary Layer

Ostoich, Christopher; Bodony, Daniel J.; Geubelle, Philippe H.

doi:10.2514/1.j051634

Cited by 36 publications

(30 citation statements)

References 44 publications

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“…This leads to: a propensity for nonlinear fluid-structural interactions; a continually evolving structural state; and hierarchical, systemic uncertainties. Furthermore, fully understanding and accounting for these complexities are challenging since: the flight conditions cannot be adequately replicated in ground based facilities; comprehensive flight testing is impractical; and tightly integrated computational analysis, using state-of-the-art tools in all the relevant disciplines, is intractable (Blevins et al, 1993;Liguore and Tzong, 2011;Zuchowski et al, 2011;McNamara and Friedmann, 2011;McNamara, 2010, 2011;Wieting et al, 1991;Bertin and Cummings, 2003;Dugundji and Calligeros, 1962;Miller et al, 2011;Ostoich et al, 2012;Crowell et al, 2011). Thus, basic research is needed in order to identify the relevant physics, and develop tractable multi-disciplinary models for structural lifting.…”

mentioning

confidence: 95%

Response of skin panels to combined self- and boundary layer-induced fluctuating pressure

Deshmukh

Culler

Miller

et al. 2015

Journal of Fluids and Structures

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mentioning

confidence: 95%

Response of skin panels to combined self- and boundary layer-induced fluctuating pressure

Deshmukh

Culler

Miller

et al. 2015

Journal of Fluids and Structures

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“…Note that in addition to the surrogate models discussed, the analytical Chapman and Rubesin method is also included using Eqs. (17) and (23). The "CIM" model produced the lowest errors relative to the 100 test cases, with a mean percent error of 4.10% and a maximum dimensional error of 0.30 W /cm 2 for a test case with a peak heat flux of 3.70 W /cm 2 .…”

Section: Iva2 Comparison Of Aerodynamic Heating Modelsmentioning

confidence: 94%

Robust Treatment of Temperature Feedback in Aerothermodynamic Models for Fluid-Thermal-Structural Analysis

Crowell

Miller

McNamara

2013

54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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One of the primary challenges in the development of high-speed systems is accurate and efficient prediction of the aerodynamic heating, particularly for light-weight systems where the aerothermodynamic loads are strongly coupled with the structural response. This study builds upon previous work focused on using CFD surrogates for prediction of aerothermodynamic loads within a tightly integrated fluid-thermal-structural analysis framework. A novel approach is developed that corrects heat flux predictions from a pointwise dependency on surface temperature in order to account for surface temperature gradients. This enables efficient construction of a CFD surrogate for aerodynamic heating without a priori assumptions on the surface temperature profile; while also accurately maintaining the critical feedback behavior of the surface temperature profile for a coupled fluid-thermal-structural analysis. The method is compared, in terms of accuracy and efficiency, with a hierarchy of approaches for aerodynamic heating prediction. Comparison cases include simple flat plate heating, as well as shock impingements in two dimensional and three dimensional flows. Typically the approach yields less than 5% error relative to full-order CFD predictions, and clearly outperforms all other simple prediction methods in terms of accuracy. Furthermore, it maintains excellent computational efficiency, enabling long time record fluid-thermal-structural analysis in complex, three-dimensional flow environments.

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“…The fluids code has been used in a variety of fluid-only problems involving both laminar and turbulent flows, [25][26][27][28][29][30] and a coupled fluid-thermal problem for which experimental data was available for comparison. 4,9 B. Solid domain…”

Section: A Fluid Domainmentioning

confidence: 99%

Aerothermoelastic response of a panel under a high speed turbulent boundary layer using direct numerical simulation

Ostoich

Bodony

Geubelle³

2013

54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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The interaction between a thin panel and a Mach 2.25 turbulent boundary layer is investigated using a high-accuracy, high-fidelity approach for the simulation of coupled fluid-structure problems. The solid solution is found by integrating the conservation of momentum equation using a non-linear 3D finite element solver, and the direct numerical simulation of the turbulent boundary layer uses a finite-difference compressible NavierStokes solver. The evolution of the panel response progresses from the emergence of low amplitude traveling bending waves to a larger amplitude standing wave type motion. Panel defections exceed 25 wall units into the boundary layer and produce compression waves that oscillate with the panel motion. Turbulence statistics are shown to be modified by the presence of the compliant panel. A large dependence on coupling configuration is shown.= thermodynamic pressure T = thermodynamic temperature ρE = total energy, = ρe + 1 2 ρu i u i ρe = internal energy, = p/(γ − 1) τ = stress tensor, τ ij = µ(∂u i /∂x j + ∂u j /∂x i ) + λ∂u k /∂x k δ ij C = specific heat capacity (J/kgK) γ = gas ratio of specific heats, = C p /C v k = thermal conductivity µ, λ = first and second coefficients of fluid viscosity q j = fluid heat flux vector, = −k∂T /∂x j x = spatial coordinates in current configuration, = (x, y, z) T ξ = computational coordinates, = (ξ, η, ζ) T δ 99 = boundary layer visual thickness δ * = boundary layer displacement thickness θ = boundary layer momentum thickness t = time t = traction ǫ = convergence value B = solid configuration X = spatial coordinates in reference configuration, = (X, Y, Z) T φ = solid domain coordinate transformation, = (φ 1 , φ 2 , φ 3 ) T F = solid domain coordinate deformation gradient, = ∂x/∂X Θ = solid domain temperature β = thermal stretch ratio σ = Cauchy stress tensor P = first Piola-Kirchhoff stress tensor δu = virtual displacement, = (δu 1 , δu 2 , δu 3 ) T δW = virtual work J = JacobianSubscript i, j = direction index w = wall n = normal ref = reference condition 0 = solid reference configuration

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Fluid-Thermal Response of Spherical Dome Under a Mach 6.59 Laminar Boundary Layer

Cited by 36 publications

References 44 publications

Response of skin panels to combined self- and boundary layer-induced fluctuating pressure

Response of skin panels to combined self- and boundary layer-induced fluctuating pressure

Robust Treatment of Temperature Feedback in Aerothermodynamic Models for Fluid-Thermal-Structural Analysis

Aerothermoelastic response of a panel under a high speed turbulent boundary layer using direct numerical simulation

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