A new approach in multidisciplinary design optimization of upper-stages using combined framework. (September 2015)

• Record Type: Journal Article
• Authors: Adami, Amirhossein; Mortazavi, Mahdi; Nosratollahi, Mehran
• Is Part Of: Acta astronautica. Volume 114(2015)
• Page Start: 174
• Page End: 183
• Publication Date: 2015-09
• Subjects: AAO all at once -- VTank, RTank volume, radius of tanks -- CO collaborative optimization -- Lcyl cylindrical length of tanks -- CSBO Combined Single-level and Bi-level Optimizations -- Rmax maximum permitted radius -- MDO multidisciplinary design optimization -- Zfill filling factor of tanks -- MDF multidisciplinary feasible -- Vfuel, VTank−fuel fuel volume, fuel tank volume -- BLISS bi-level integrated system synthesis -- Vox, VTank−ox oxidant volume, oxidant tank volume -- CSSO concurrent subspace optimization -- Vempty Empty volume of tanks -- O/F, oxidant mass by fuel mass ratio -- VTotal total volume of tanks -- SQP sequential quadratic optimization -- VPress.Tank, RPress.Tank volume, radius of pressurized gas tank -- GA genetic algorithm -- Rgas constant parameter of pressurizer gas -- A⁎, Rt throat area, radius of throat -- T∞ initial temperature -- Pe pressure at exit of the nozzle -- MPress.Gas required mass of pressurizer gas -- Me Mach number of exit nozzle -- Pmax maximum pressure of pressurized gas tank -- γ isentropic exponent -- Lfilm length of film cooling -- ṁ Mass flow of nozzle (thruster) -- ṁfilm mass flow of film cooling -- g0 gravitational acc -- Tvap vaporization temperature of coolant -- Thrustvac vacuum thrust -- ṁvap mass flow of vaporization -- Ae, Re exit area, radius of exit section -- q̇hγ convective heat flux -- Pcomb pressure of combustion chamber -- q̇rγ radiative heat flux -- P⁎ pressure of throat -- hγ convective heat coefficient -- Tcomb temperature of combustion chamber -- Ts wall temperature -- T⁎ Temperature at throat -- εγ radiative coefficient of hot gas -- Te temperature at exit section -- T˜ mean temperature -- R constant parameter of gas (combustion product ) -- Zc correction factor -- Vcomb volume of combustion chamber -- CP specific heat at constant pressure -- Lcomb Length of combustion chamber -- nS.F safety factor -- Vinj injection velocity of propellant -- q̇strr radiative heat flux from structure -- PTank tanks pressure -- δcomb required thickness of combustion chamber -- Dcomb, Rcomb diameter, radius of combustion chamber -- δpres.Gas required thickness of -- θ1 convergent angle -- δTanksph required thickness of spherical tank -- θ2 divergent angle -- δTankcyl required thickness of cylindrical tank -- Zexpantion expansion ratio of nozzle (area) -- δnozzle required thickness of nozzle -- Lcon convergent length of nozzle -- nσ mass correction factor -- Ldiv divergent length of nozzle -- λ2 temperature correction factor; Multidisciplinary design -- Optimization -- Bipropellant thruster -- Upper-stage -- AAO -- CO; Astronautics -- Periodicals; Outer space -- Exploration -- Periodicals; Astronautics; Periodicals; 629.405
• DOI: 10.1016/j.actaastro.2015.04.011
• Languages: English
• ISSNs: 0094-5765

Abstract

Abstract: Optimum design of an upper-stage with bipropellant propulsion system consists of optimization of three major subsystems including thruster, feeding subsystem, and propellant tanks. Optimization of such a complex system involved in optimization of many disciplines including structure, heat transfer, aerothermodynamics, guidance and control, trajectory and propulsion. Hard coupling of the disciplines increase the optimization processing times. Multidisciplinary design optimization algorithm can derive the optimum configuration but more elapsed time is needed for single-level methods such as all at once (AAO) and lower feasibility occurred in multi-level methods such as collaborative optimization (CO). In this paper, a new multidisciplinary design optimization framework is proposed for such coupled disciplines with concentrating on the propulsion system. The proposed framework uses Combined Single-level and Bi-level Optimizations (CSBO) frameworks to minimize numbers of design variables and system constraints when feasibility is increased. For this goal, modeling of every discipline is introduced and the design algorithm validated by redesigning of two real bipropellant thrusters. Three MDO frameworks are applied for our problem including AAO, CO and CSBO. Comparisons between the results show that CSBO can find the optimum solution in shorter elapsed time with lower F-count. Therefore, CSBO is more efficient for complex systems with coupled disciplines. Highlights: The new MDO framework is proposed for a complex system with coupled disciplines. CSBO minimizes the numbers of design variables and the system constrains. The optimum design of an upper-stage is selected as a case study. Three MDO frameworks are applied for our problem including AAO, CO and CSBO. As results, CSBO can find the optimum solution in shorter elapsed.