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Genetic Algorithm Optimization of a Cost Competitive Hybrid Rocket Booster
Author(s) -
George Story
Publication year - 2015
Publication title -
51st aiaa/sae/asee joint propulsion conference
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2015-4203
Subject(s) - booster (rocketry) , solid fuel rocket , genetic algorithm , computer science , propulsion , aerospace engineering , rocket (weapon) , engineering , systems engineering , propellant , machine learning
Performance, reliability and cost have always been drivers in the rocket business. Hybrid rockets have been late entries into the launch business due to substantial early development work on liquid rockets and later on solid rockets. Slowly the technology readiness level of hybrids has been increasing due to various large scale testing and flight tests of hybrid rockets. A remaining issue is the cost of hybrids vs the existing launch propulsion systems. This paper will review the known state of the art hybrid development work to date and incorporate it into a genetic algorithm to optimize the configuration based on various parameters. A cost module will be incorporated to the code based on the weights of the components. The design will be optimized on meeting the performance requirements at the lowest cost.

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