Evolved engines
Computer models developed at the University of Wisconsin-Madison not only serve to design engines, but model algorithms help increase fuel performance and reduce pollution. These algorithms are called genetic algorithms and comply with the laws proposed by Darwin.
The models developed by Peter Senecal analyze the combination of billions of factors that can influence the performance of an engine and choose the most suitable. The main advantage of the model is that it allows to increase fuel performance and reduce pollution together, which until now was impossible. Silicon Graphics has designed a diesel engine that, using a supercomputer, emits 3 times less nitric oxide and 50% less ash. At the same time, the engine consumes 15% less.
It starts working with 5 units of different combinations of six parameters of a motor system. The computer model chooses the two best of those 5 and with them a new generation is formed. The process continues to detect the most suitable unit.
According to Senecal, this system reduces calculations because it only performs the best combinations. Thus, the work of the decades can be completed in a few weeks. The same technique can be adapted for other types of motors or parts.
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