Topic: Evolving nuclear propulsion systems

[Nemesis]

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As in nature, genetic algorithms have evolved by removing poor solutions or designs that do not perform well, and repopulating the next generation of computations only with combinations – or mutations – of better designs. Over time and with successive generations only the best options remain.

Unlike traditional design analyses, which are limited to the specific input of engineers, complete with their biases, genetic algorithms show great promise for improving designs with virtually no boundaries. The technique reaches each solution without sequential design information, the researchers said, resulting in novel approaches that would likely never be generated with conventional methods.