Leap 71 used its Noyrn AI tool to design a rocket engine that was then 3D-printed in copper. (Image Credit: Leap 71)
Leap 71, an AI engineering company, has created a rocket engine using Noyron, the company's AI tool that designs sophisticated machinery and products. Noyron embodies engineers' knowledge, incorporating physics like thermal models, manufacturing rules, and the logic of various engineering fields in a framework. It's worth noting that the AI tool is always improving by learning from real-world tests and manufacturing outcomes.
What's great about Noyron is that it relies on its integrated data to produce parts that meet the necessary specifications. Plus, it's capable of predicting how a produced object functions in the real world. This AI tool uses machine learning to solve problems like a human engineer. It designs engines with certain specifications, such as thrust.
Leap 71 recently used the software to design a rocket engine for the first time. The company partnered up with the University of Sheffield and AMCM to develop and test the rocket engine. It runs on cryogenic liquid oxygen and kerosene. The engine with 5 kN of thrust generated 20,000 horsepower and completed all its tests.
The rocket engine underwent successful testing and achieved 20,000 horsepower. (Image Credit: Leap 71)
Placed in a U.K.-based WW2 bunker, the rocket engine underwent two test burns. The first burn, lasting three seconds, had fire shooting out of the exhaust. It then saw a second test burn that lasted 13 seconds, verifying reliability and stability. This proved that the AI tool could design a working rocket engine.
Thanks to this technology, the engine functioned after printing from the CAD file. Noyron only takes minutes to design a rocket engine that would otherwise take a human engineer weeks or months to achieve. Those tests could point toward a future where engineers work with AI to optimize designs. For instance, engineers working with Noyron get a better idea of the overall design and can fine-tune the AI model's logic or inputs for better outcomes.
Rapid iteration is also crucial since Noyron speeds up the process to pass the requirements of aerospace systems by refining designs. It only takes minutes to come up with different design iterations. Engineers can then look at various configurations and choose the best solution. Even with a prompt, the AI tool always produces the same results, making it reliable in an important field.
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