Researchers at EPFL have developed a method that uses artificial intelligence to design next-generation heat-pump compressors.
These systems draw in thermal energy from the surrounding environment - such as from the ground, air, or a nearby lake or river - and turn it into heat for buildings.
While today's heat pumps generally work well and are environmentally friendly, they still have substantial room for improvement.
Using a machine-learning process called symbolic regression, the researchers came up with simple equations for quickly calculating the optimal dimensions of a turbocompressor for a given heat pump.
Their research just won the Best Paper Award at the 2019 Turbo Expo Conference held by the American Society of Mechanical Engineers.
The researchers' method drastically simplifies the first step in designing turbochargers.