Hypersonic Flow Predictions Using Linear and Nonlinear Turbulence Closures

Goldberg, U.; Batten, Paul; Palaniswamy, S.; Chakravarthy, Sukumar; Peroomian, Oshin

doi:10.2514/2.2650

Cited by 64 publications

(19 citation statements)

References 12 publications

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“…CFX is a continuum code, and so the actual quantitative data presented here should be treated with some caution. To provide an independent check on the results without resorting to direct simulation Monte Carlo methods, we repeated this calculation with a completely different code, the density-based continuum code CFD [30]. The results from that DEEPAK, RAY, AND BOYCE calculation were in good agreement with the CFX simulation here and yielded a drag within 1.7% of the CFX value.…”

Section: Resultssupporting

confidence: 75%

Evolutionary Algorithm Shape Optimization of a Hypersonic Flight Experiment Nose Cone

Deepak

Ray

Boyce

2008

Journal of Spacecraft and Rockets

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Hypersonic vehicle development, particularly for hypersonic airbreathers, will require robust-design optimization to achieve performance targets. Vehicle shape optimization will play an important role. This paper presents the first application to hypersonic vehicle shape optimization of a reduced parametric section shape representation coupled with a surrogate-assisted evolutionary-algorithm optimization approach. The particular case considered is the minimization of total drag of the nose cone of a hypersonic flight experiment. The computational fluid dynamics solver used here is ANSYS CFX. Single-point optimization at Mach 3 and Mach 8 is performed at altitudes relevant to those Mach numbers for a typical hypersonic flight experiment ascent trajectory. Without surrogate assistance, the optimized shapes for each Mach number were both found to result in significant drag-force reductions (1.39% at Mach 3 and 1.96% at Mach 8) when compared with the baseline blunted standard ogive nose-cone shape. When the surrogate assistance (which is a radial-basis-function network approximation to the drag dependence on the shape parameters) was introduced, the optimized shapes yielded nearly the same drag reduction as without surrogate assistance, but also resulted in significant savings in the computational cost. Finally, the performance of the optimum shape derived at Mach 3 is evaluated at Mach 8 and vice versa to illustrate the robustness of the nose-cone shapes derived using such an approach. Nomenclature a = real coefficient C = children population C D = drag coefficient I = individual population L = length, m M = individual population M 1 = Mach number P = parent population p = pressure, Pa S = individual from M population U = uniform random number x = initialized variable y = offspring = angle of attack, deg = ratio of specific heats, C p =C v x = wall shear stress Subscripts i = variable number j = constraints k = objectives n = coefficient numbers 1 = freestream conditions

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Section: Resultssupporting

confidence: 75%

Evolutionary Algorithm Shape Optimization of a Hypersonic Flight Experiment Nose Cone

Deepak

Ray

Boyce

2008

Journal of Spacecraft and Rockets

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“…CFD++ has available a large set of turbulence models, nine of which were investigated for their accuracy in prediction of the surface pressure profiles. The models investigated in this study were 1) Menter's k-ω shear stress transport (SST) two-equation model [19], 2) Menter's baseline (BSL) twoequation model [19], 3) the standard (KW) [20] and 4) realizable k-ω (RKW) [18] two-equation models, 5) the Spalart-Allmaras (SA) oneequation model [21], 6) the Spalart-Allmaras one-equation model with rotation/curvature correction (SARC) [22], 7) the realizable k-ε (RKE) two-equation model [23], 8) the cubic k-ε (CKE) nonlinear two-equation model [24], and 9) Goldberg et al's k-ε-R t (KER) three-equation model [25]. In addition, the effect of the compressibility correction term was investigated by comparing solutions modeled with the wall-bounded and free-shear-type flow options and without the correction term.…”

Section: Cfd Solvermentioning

confidence: 99%

Turbulence Model Effects on Cold-Gas Lateral Jet Interaction in a Supersonic Crossflow

DeSpirito

2015

Journal of Spacecraft and Rockets

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Computational fluid dynamic predictions of surface pressures resulting from a sonic lateral jet venting into a supersonic crossflow from a cone-cylinder-flare missile are compared to archival wind-tunnel data. Predictions of axial and azimuthal pressure profiles were found to be very dependent on the turbulence model, with some models performing relatively poorly. Menter's baseline model gave very good to excellent predictions and was used to perform additional validations of other flow conditions, jet nozzle configurations, and jet pressure ratios: again with excellent agreement. The study found that, even with the observed variations in surface pressure, the aerodynamic forces and moments produced by the lateral jet interaction were much less sensitive to the turbulence model. However, an estimate of the trajectory and strength of the counter-rotating vortex pair showed that, although there was little effect of the turbulence model on the location of the vortex pair, the induced vorticity varied by over 30%. This difference can be large enough to impact the prediction of the resultant forces and moments if there are fins or other appendages in the wake of the counter-rotating vortex pair. Nomenclature C A0= axial force coefficient C m0= pitching moment about nose of missile C N = normal force coefficient C p = pressure coefficient C P no-jet = pressure coefficient for case with no jet injection D = diameter of cylindrical section of missile, m d = jet nozzle diameter, m F A0 = axial force, N F j = jet thrust force, N F ji = jet interaction force, N F no-jet = normal force due to α without jet, N F total = total normal force (thrust interaction force due to α), N I t = turbulent intensity K f = jet force amplification factor K m = jet moment amplification factor k = turbulent kinetic energy, m 2 · s −2 l j = distance between missile center of gravity and jet nozzle axis, m l t = turbulent length scale, m M = Mach number M j = moment induced by jet thrust force, N · m M ji = moment about center of gravity induced by jet interaction force, N · m M ji0 = moment about missile nose induced by jet interaction force, N · m M total = moment induced by total normal force, N · m PR = jet total-to-freestream static pressure ratio; p 0 j ∕p ∞ p 0 = freestream total pressure, Pa p 0 j = jet total pressure, Pa p ∞ = freestream static pressure, Pa Re = Reynolds number R t = undamped eddy viscosity T 0 = freestream total temperature, K T ∞ = freestream static temperature, K X = axial distance along missile, m X cp = center of pressure location relative to missile nose, calibers y = nondimensional wall distance α = angle of attack, deg ε = eddy diffusivity, m 2 · s −1 ρ ∞ = freestream gas density, kg · m −3 ϕ = azimuthal distance around missile body, deg ω = specific dissipation, s −1

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“…The CFD simulations presented in this paper were performed using CFD++, developed by Metacomp Technologies [21]. CFD++ can provide unsteady-and steady-state solutions to the Navier-Stokes equations for compressible and incompressible flows with multispecies and finite-rate chemistry modeling.…”

Section: Cfd++mentioning

confidence: 99%

Numerical Investigation into the Combustion Behavior of an Inlet-Fueled Thermal-Compression-Like Scramjet

2015

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A numerical study on the combustion behavior of an inlet-fueled three-dimensional nonuniform-compression scramjet is presented. This paper is an extension to previous work on the combustion processes in a premixed threedimensional nonuniform-compression scramjet, where thermal compression was shown to enhance combustion. This paper demonstrates how thermal compression can be used in a generic scramjet configuration with a realistic fuelinjection method to enhance performance at high flight Mach numbers. Such a scramjet offers an extra degree of freedom in the design process of fixed-geometry scramjets that must operate over a range of flight Mach numbers. In this study, how the combustion processes are affected is investigated, with the added realism of inlet porthole fuel injection. Ignition is established from within a shock-induced boundary-layer separation at the entrance to the combustor. Radicals that form upstream of the combustor within the inlet, from the injection method, enhance combustion. Coupling of the inlet-induced spanwise gradients and thermal compression improves combustion. The results highlight that, although the fuel-injection method imparts local changes to the flow structures, the global flow behavior does not change compared to previous premixed results. This combustion behavior will be reproduced when using other fueling methods that deliver partially premixed fuel and air to the combustor entrance.

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Hypersonic Flow Predictions Using Linear and Nonlinear Turbulence Closures

Cited by 64 publications

References 12 publications

Evolutionary Algorithm Shape Optimization of a Hypersonic Flight Experiment Nose Cone

Evolutionary Algorithm Shape Optimization of a Hypersonic Flight Experiment Nose Cone

Turbulence Model Effects on Cold-Gas Lateral Jet Interaction in a Supersonic Crossflow

Numerical Investigation into the Combustion Behavior of an Inlet-Fueled Thermal-Compression-Like Scramjet

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