Nuclear reactor designers use genetic algorithms to better explore a complex design space Simulated evolution will come up with some systems that were not thought of before. It won’t replace the experts or come up with a finished design, but it makes it possible to consider options they wouldn’t have had otherwise. For very complex problems, such as nuclear reactor design it is important to combine genetic algorithms with sophisticated methods of simulation and analysis. Research is now focused on integrating genetic algorithms with other techniques and more powerful computation.
Exhaustive automated searches and automated initial evaluations will improve the searches for optimal designs. The optimization can be adjusted quickly by changing the evaluation parameters.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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