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Optimization of Turbo-Machinery Blade Using Genetic Algorithms

This study demonstrates the optimization of a rotor blade in a supersonic turbofan engine through Genetic Algorithms (GA). GAs are used to achieve better performance parameters and reduce noise levels. The results show improvements in efficiency, thrust, and noise reduction. The GA process involves selecting the population size, crossover type, and mutation rate. The study highlights the importance of fine-tuning GA parameters for optimal results, as well as the potential for further advancements in turbo-machinery design using evolutionary algorithms.

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Optimization of Turbo-Machinery Blade Using Genetic Algorithms

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  1. http://www.grc.nasa.gov/WWW/RT/2006/RT/RTB-nguyen3.html

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