Multigrid Adaptive-Mesh Turbulent Simulations of Launch Vehicle Flows

Bigarella, E. D. V.; Basso, Edson; Azevedo, João Luiz F.

doi:10.2514/6.2003-4076

Cited by 9 publications

(5 citation statements)

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“…This analysis tended to confirm the destabilizing effects predicted by the earlier analyses of Ericsson [4]. The use of CFD in the analysis of launch vehicles has expanded over the last several decades [6][7][8][9][10][11][12]. For current and future launch vehicles, it can be expected that CFD will be an integral part of the design from the conceptual stage.…”

Section: Introductionmentioning

confidence: 53%

Computational Aeroelastic Analysis of the Ares Crew Launch Vehicle During Ascent

Bartels

Chwalowski

Massey

et al. 2010

28th AIAA Applied Aerodynamics Conference

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Static and dynamic aeroelastic analyses have been performed for the Ares I crew launch vehicle during atmospheric ascent. It is shown that, through the transonic speed range, there is a rapid change in the static aeroelastic center-of-pressure increment with increasing Mach number. The greatest sensitivity to grid resolution is observed through the transonic range. Dynamic aeroelastic analyses are also performed to assess the aeroelastic stability of the launch vehicle. Flexible dynamic linearized quasi-steady analyses using steady rigid line loads are compared with fully coupled aeroelastic time-marching computational fluid dynamic analyses. There are significant differences between the methods through the transonic Mach number range. The largest difference is at Mach 1. At that Mach number, the linearized quasi-steady method produces strong damping in modes 1 and 2. The unsteady computational aeroelastic method indicates that the first mode is significantly undamped, while mode 2 is strongly damped. The cause of the disparity in damping between modes 1 and 2 is also investigated. A vehicle with no protuberances other than rings produced damping values in modes 1 and 2 that were nearly identical. It is shown that the disparity in damping of modes one and two is due to asymmetric placement of protuberances around the vehicle circumference.

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Section: Introductionmentioning

confidence: 53%

Computational Aeroelastic Analysis of the Ares Crew Launch Vehicle During Ascent

Bartels

Chwalowski

Massey

et al. 2010

28th AIAA Applied Aerodynamics Conference

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“…The current multigrid method has been successfully validated within the present 3-D unstructured computational code for inviscid to turbulent viscous simulations, as shown in [31]. To improve the multigrid algorithm as well as the computational method, the simulations start at the coarsest grid level.…”

Section: A Multigrid Methodologymentioning

confidence: 97%

Centered and Upwind Multigrid Turbulent Flow Simulations of Launch Vehicle Configurations

Bigarella

Azevedo

Scalabrin

2007

Journal of Spacecraft and Rockets

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The paper discusses results obtained with a finite-volume code that simulates viscous, turbulent flows for 3-D, adaptive, unstructured meshes. The implementation uses a cell-centered, face-based data structure. A fully explicit, second-order accurate, five-stage, Runge-Kutta time stepping scheme is used to perform the time marching of the flow equations. Spatial discretization of the Reynolds-averaged Navier-Stokes equations can be performed with second-order centered or upwind schemes. Automatic grid refinement routines are considered to adapt the original mesh. A sensor based on density gradients selects the volumes to be refined. The code is able to handle tetrahedra, hexahedra, wedges, and pyramids. A full multigrid scheme is available to accelerate convergence to steady state. Coarse grid levels are constructed through an agglomeration procedure. One-and two-equation turbulence models are implemented to include the turbulent effects into the numerical formulation. The mentioned features integrated in one single code allow the Brazilian aerospace program to simulate complex flow conditions for sounding rockets and satellite launch vehicles with accuracy and reasonable computational resources. Good agreement with theoretical or experimental results is obtained with the present numerical tool. Nomenclature a = speed of sound C = convective operator Cp = pressure coefficient D = artificial dissipation operator d = minimum distance to the wall e = total energy per unit volume e i = internal energy f = source term of the multigrid method k = specific turbulent kinetic energy p = static pressure P e = inviscid flux vector P v = viscous flux vector Q = vector of conserved properties q = heat flux vector RHS = right-hand side operator S = absolute value of the mean strain-rate tensor S = area vector S ij = mean strain-rate tensor component T = static temperature u, v, w = Cartesian velocity components V = viscous operator v = Cartesian velocity vector x, y, z = Cartesian coordinates = angle of attack 1 . . . 5 = Runge-Kutta control parameters = ratio of specific heats t = time step = von Karman constant = dynamic viscosity coefficient = kinematic viscosity coefficient = modified Spalart-Allmaras eddy-viscosity coefficient = density = viscous stress tensor = gradient ratio for limiter computation = control volume limiter ! = turbulent dissipation = absolute value of the mean rotation tensor ij = mean rotation tensor component Subscripts f, k = face index i, m = grid control volume indices ' = laminar property L, R = interface left and right properties t = turbulent property 1 = freestream property Superscripts (m) = current grid of the multigrid method n = time instant * = dimensional property

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“…The AoA for the numerical computation is assumed as α = 0 0 . Simulations have been carried out at two transonic Mach numbers (M = 0.8 & M = 0.9) using PARAS-3D to compute the C p distributions [10]. Figure 2 shows the variation of C p along X/L Direction at slanted nose cone angle 20 0 with various nose radius values at M = 0.8 and M = 0.9.…”

Section: Effects Of Various Slanted Strap-on Nose Radius On the Launcmentioning

confidence: 99%

Numerical simulation over a multi-body launch vehicle module at various transonic Mach numbers

Rathnavel¹,

Das²,

Ralphin³

et al. 2017

FME Transactions

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Simulations have been carried out for a multi-body launch vehicle configuration using CFD code "PARAS-3D". PARAS-3D is a Reynolds Averaged Navier Stokes equations (RANS) solver with k-ε turbulence model. The transonic regime is a critical regime for any launch vehicle configuration because of its typical aerodynamic characteristics such as shock wave disturbances. CFD flow simulations are done at zero degree angle of attack for various strap-on nose cone angle, nose radius and Mach numbers 0.8, 0.9, 0.95, 1.05. For different positions of strap-on obtained through forward and backward shift from its original position, the influence of strap-on on fore body of the core of launch vehicle is investigated. In this article, the results pertaining to the pressure distribution and Mach contour over launch vehicle configuration is presented.

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Multigrid Adaptive-Mesh Turbulent Simulations of Launch Vehicle Flows

Cited by 9 publications

References 0 publications

Computational Aeroelastic Analysis of the Ares Crew Launch Vehicle During Ascent

Computational Aeroelastic Analysis of the Ares Crew Launch Vehicle During Ascent

Centered and Upwind Multigrid Turbulent Flow Simulations of Launch Vehicle Configurations

Numerical simulation over a multi-body launch vehicle module at various transonic Mach numbers

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