Design of Dual-Mode Engine Flowpaths for Hypersonic Vehicles Using Reduced-Order Models

Torrez, Sean M.; Dalle, Derek J.; Driscoll, James F.

doi:10.2514/6.2011-2380

Cited by 4 publications

(10 citation statements)

References 10 publications

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“…The authors have developed another model, called MASIV [3,5,6,24,25], which contains analysis of effects such as shock interactions, finite-rate chemistry, fuel-air mixing, and a ram-mode solver. Like the model developed in this paper, it is a tip-to-tail vehicle model that contains trim analysis.…”

Section: A Trajectory Simulationmentioning

confidence: 99%

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Continuous Differentiation of Complex Systems Applied to a Hypersonic Vehicle

Dalle

Driscoll

2012

AIAA Atmospheric Flight Mechanics Conference

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An implementation of a three-dimensional model for an air-breathing hypersonic vehicle using algorithmic differentiation is presented. Motivation for this work is given in terms of difficulties encountered while calculating the linearized flight dynamics of another hypersonic vehicle model. The new model automatically calculates derivatives with respect to flight condition variables, control variables, model parameters, and design variables. The differentiation approach used here is unique in that it calculates both left-and right-hand derivatives at first-order discontinuities. Other approaches including complex step and finite difference are compared with the present implementation. Difficulties encountered in the derivation include handling of if statements, iterative solution of systems, and sorting. Hypersonic flight for a simple climbing and accelerating trajectory is considered to demonstrate the use of the model, and the effect of ballast mass on the short-period and Dutch-roll modes is also shown. Nomenclature a = local speed of sound C = transformation matrix e = eccentricity F, F = force or specific force f = mass capture fraction f = vector equations of motion function g = gravity vector H = height h = altitude I = inertia tensor J = Jacobian L = length or geodetic latitude M = Mach number M = moment (torque) or specific moment m = number of external inlet shockṡ m = mass flow rate n = number of internal inlet shocks n = normal vector n = unit normal vector P = roll rate p = pressure Q = pitch rate q = dynamic pressure R = yaw rate r = position vector T = temperature u = vector of control variables V, v, v = velocity w = dimensionless width x, y, z = physical coordinates x = vector of state variables α = angle of attack β = sideslip angle γ = ratio of specific heats or flight path angle δ = deflection angle or control input ε = pressure ratio ζ, η, ξ = placeholder variables θ = pitch angle or angle of flow λ = length fraction ρ = density σ = velocity heading angle φ = roll angle ψ = yaw angle ω, ω = angular velocity Subscripts/superscripts + = right-hand derivative − = left-hand derivative * = reference value 0 = stagnation value 1, 2, . . . = station number b= body frame CE = collective (average) elevon value CR = collective (average) rudder value DE = differential (left minus right) elevon value e = Earth-centered, Earth-fixed frame ER = equivalence ratio i = station index or intertial frame N, E, D = north, east, down components n = navigation frame

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Section: A Trajectory Simulationmentioning

confidence: 99%

“…(25). The acceleration vector,ẋ, consists of the velocity and angular velocity derivatives,u,v,ẇ,Ṗ ,Q, andṘ.…”

Section: Trimmentioning

confidence: 99%

Continuous Differentiation of Complex Systems Applied to a Hypersonic Vehicle

Dalle

Driscoll

2012

AIAA Atmospheric Flight Mechanics Conference

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“…These combustors were analyzed in a study, [2], that identified a few features of each that contribute to thrust performance. The overall performance of each design was evaluated over a range of Mach numbers 6 < M < 8 and altitude from 18 km to 28 km.…”

Section: Analysis Of Available Designsmentioning

confidence: 99%

“…Previous work, [1], has shown that a vehicle designed to have high pressure recovery factor (PRF) at a single design point will be likely to have poor performance away from that point. Recent work, [1,2], has attempted to extend this principle into other components with the end goal of using an integrated optimization approach for the entire vehicle, including control and trajectory.…”

Section: Introductionmentioning

confidence: 99%

“…To develop this technique we have concentrated on a few combustor designs available in the literature, which have been examined in experiments, [3,4,5]. The performance of these designs as predicted by the MASIV code, [6], has previously been computed in a trade study that considered a range of operating conditions [2]. The present study seeks to expand previous efforts by using mathematical optimization.…”

Section: Introductionmentioning

confidence: 99%

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Multidisciplinary Optimization of the Fuel Consumption of a Dual Mode Scramjet-Ramjet

Torrez¹,

Dalle²,

Driscoll³

2011

47th AIAA/ASME/SAE/ASEE Joint Propulsion Conference &Amp;amp; Exhibit

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Dual-mode ramjets have design requirements that are distinct from those of other high speed propulsion systems because they are expected to operate over a wide range of conditions. Several previously examined combustor designs are evaluated over a range of operating conditions using a low order model. The designs under consideration are parametrized by three variables: location of fuel injection, angle of wall divergence and location of wall divergence, and multidisciplinary optimization (MDO) is performed to suggest avenues to improve performance over the entire range, as measured by overall fuel consumption.

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