Dual-fuel propulsion in single-stage Advanced Manned Launch System Vehicle

Lepsch, Roger A.; Stanley, Douglas O.; Unal, Resit

doi:10.2514/3.26631

Cited by 29 publications

(2 citation statements)

References 9 publications

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“…In some cases, liftoff gross weight is selected as the minimization variable [15,16]. However, realizing that propellant is relatively inexpensive, most of the recent concepts have been design to minimum dry weight [17][18][19][20][21][22]. It is often claimed that vehicle development costs tend to vary as a function of dry weight, this minimum dry weight vehicle may be considered a minimum development cost concept.…”

Section: B Performance Indexmentioning

confidence: 99%

Multidisciplinary Design Optimization Approach for a Small Solid Propellant Launch Vehicle Conceptual Design Using Hybrid Simulated Annealing

Roshanian

Barzinpour

2011

AMM

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Multidisciplinary Design Optimization (MDO) of a two-stage Small Solid Propellant Launch Vehicle (SSPLV) by simulated annealing (SA) Method is investigated. Propulsion, weight, aerodynamic (geometry) and 3degree of freedom (3DOF) trajectory simulation disciplines are used in an appropriate combination. Suitable design variables, technological-functional constraints and minimum launch weight objective function are considered. To handle constraints augmentation of constraints to cost using penalty coefficients are used. Results are compared with gradient-base method that shows the ability of SA to escape local optimums.

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Section: B Performance Indexmentioning

confidence: 99%

Multidisciplinary Design Optimization Approach for a Small Solid Propellant Launch Vehicle Conceptual Design Using Hybrid Simulated Annealing

Roshanian

Barzinpour

2011

AMM

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“…24,25) However, realizing that propellant is relatively inexpensive, most concepts have been designed to minimize dry weight. [26][27][28][29][30][31] Since it is often claimed that vehicle development costs tend to vary as a function of dry weight, this minimum dry weight vehicle may be considered a minimum development cost concept. However, as demonstrated by Brown et al 32) such an assertion is not rigorously true even when a weight-based cost model is used.…”

Section: Performance Indexmentioning

confidence: 99%

Multi-level of Fidelity Multi-Disciplinary Design Optimization of Small, Solid-Propellant Launch Vehicles

Roshanian

Jodei

Mirshams

et al. 2010

Trans. Japan Soc. Aero. S Sci.

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A new automated multi-level of fidelity Multi-Disciplinary Design Optimization (MDO) methodology has been developed at the MDO Laboratory of K.N. Toosi University of Technology. This paper explains a new design approach by formulation of developed disciplinary modules. A conceptual design for a small, solid-propellant launch vehicle was considered at two levels of fidelity structure. Low and medium level of fidelity disciplinary codes were developed and linked. Appropriate design and analysis codes were defined according to their effect on the conceptual design process. Simultaneous optimization of the launch vehicle was performed at the discipline level and system level. Propulsion, aerodynamics, structure and trajectory disciplinary codes were used. To reach the minimum launch weight, the Low LoF code first searches the whole design space to achieve the mission requirements. Then the medium LoF code receives the output of the low LoF and gives a value near the optimum launch weight with more details and higher fidelity.

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Multidisciplinary aerospace design optimization: survey of recent developments

Sobieszczanski

Raphael

1997

Structural Optimization

815

239

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The increased computational burden may simply reflect the increased size of the MDO problem, with the number of analysis variables and of design variables adding up with each additional discipline.A case of tens of thousands of analysis variables and several thousands of design variables, reported in Berkes (90) for just the structural part of an airframe design, illustrates the dimensionality of the MDO task one has to prepare for. Since solution times for most analysis and optimization algorithms increase at a superlinear. rate, the computational cost of MDO is usually much higher than the sum of the costs of the single-discipline In MDO of complexsystems we alsoface formidable organizational challenges. Theanalysis codes foreachdiscipline havetobemade tointeract withoneanother forthepurpose ofsystem analysis and systemoptimization. The kind andbreadthof interaction is affectedby the MDO formulation. Decisions on thechoice of design variables andon whether tousesingle-level optimization ormultilevel optimization have profound effects onthecoordination anddatatransferbetween analysis codesandthe optimization codeandon the degree of human interactions required. Theinteraction between the modules in thesoftware system ononesideandthe multitude of users organized in disciplinary groups on theothersidemaybecomplicated by departmental divisions intheorganization that performs theMDO.Onemaydiscern three categories ofapproaches to MDO problems,dependingon the way the organizational challenge hasbeen addressed. Twoof these categories represent approaches that concentrated on problem formulationsthat circumventthe organizational challenge, whilethethirddeals with attempts toaddress thischallenge directly.1. Thefirstcategory includes problems withtwo or threeinteracting disciplines where a single analyst canacquire alltherequired expertise. At theanalysis level, thismayleadtothecreation ofa newdiscipline that focuseson the interactionof the involved disciplines, suchasaeroelasticity or thermoelasticity. Thismayleadto MDOwhere designvariables in several disciplines have tobeobtained simultaneously toensure efficient design. Thepast twodecades have created thediscipline ofstructural control, withanalysts whoarewell versed in bothstructures andcontrol system analysis anddesign. There hasalsobeen much workonsimultaneous optimization of structures and control systems (e.g., Haftka, 90). Most ofthepapers inthiscategory represent asingle group of researchers or practitioners workingwith a singlecomputer program, so that organizational challenges were minimized. Because ofthis,it iseasier forresearchers working onproblems inthiscategory todeal withsome oftheissues of complexity of MDOproblems, such as theneed formultiobjective optimization (e.g., Gupta andJoshi, 90,RaoandVenkayya, 92,Grandhi etal., 92,and Dovi andWrenn, 90 In some applications, one may identify a cluster of modules in a system model that exchange very large volumes of data that are not amenable to condensation.In such cases, the computational cost may be subst...

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Dual-fuel propulsion in single-stage Advanced Manned Launch System Vehicle

Cited by 29 publications

References 9 publications

Multidisciplinary Design Optimization Approach for a Small Solid Propellant Launch Vehicle Conceptual Design Using Hybrid Simulated Annealing

Multidisciplinary Design Optimization Approach for a Small Solid Propellant Launch Vehicle Conceptual Design Using Hybrid Simulated Annealing

Multi-level of Fidelity Multi-Disciplinary Design Optimization of Small, Solid-Propellant Launch Vehicles

Multidisciplinary aerospace design optimization: survey of recent developments

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