Modeling of an Exhaust Gas Cooler in a High-Altitude Test Facility of Large-Area Ratio Rocket Engines

Rajagopal, Manikanda; Rajamanohar, D.

doi:10.1061/(asce)as.1943-5525.0000378

Cited by 3 publications

(1 citation statement)

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“…Therefore, modeling disciplines like combustion chamber, weight, structure, and nozzle design and cooling is necessary to discover the specifications and practical characteristics of the LPEs. [2][3][4][5][6] The interactions between these disciplines in the design cycle lead to increase in costs and design duration.…”

Section: Introductionmentioning

confidence: 99%

Liquid propellant engine conceptual design by using a fuzzy-multi-objective genetic algorithm (MOGA) optimization method

Mirshams

Naseh

Taei

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part G:

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This paper presents an extension of fuzzy-multi-objective genetic algorithm (MOGA) optimization methodology that could effectively be used to find the overall satisfaction of objective functions (selecting the design variables) in the early stages of design process. The coupling of objective functions due to design variables in an engineering design process will result in difficulties in design optimization problems. The primary application of this methodology is the design of a liquid propellant engine with the maximum specific impulse and the minimum weight. The independent design variables in this model are combustion chamber pressure, exit pressure, oxidizer to fuel mass flow rate. To handle the mentioned problems, a fuzzy-multi-objective genetic algorithm optimization methodology is developed based on Pareto optimal set. Liquid propellant engine, F-1 is modeled to illustrate accuracy and efficiency of proposed methodology.

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