AI searched 100 million possibilities and found a cheaper way to 3D-print a NASA rocket alloy
Researchers used AI to search through more than 100 million possible settings for 3D-printing a high-performance NASA alloy. After only 40 experiments, the system identified six successful configurations, including one that worked at a record-low 500 watts. That could allow GRCop
The use of AI to optimize 3D-printing settings for a high-performance NASA alloy is a significant development, particularly in the context of certification. The ability to rapidly search through vast parameter spaces and identify optimal settings can greatly accelerate the certification process for new materials and manufacturing techniques. This is especially important in industries like aerospace, where material properties and performance are critical to safety and reliability.
The fact that the AI system was able to identify successful configurations, including one that worked at a record-low 500 watts, after only 40 experiments is a testament to its efficiency. Traditional trial-and-error approaches can be time-consuming and costly, and may not always yield optimal results. By leveraging AI, researchers can explore a much larger design space and identify promising solutions that might have gone undiscovered through conventional means.
As the use of AI in materials development and manufacturing continues to grow, it's likely that we'll see increased emphasis on certification and qualification of AI-optimized processes and materials. To watch next: how regulatory bodies and industry leaders will adapt to the use of AI in certification, and what new standards and guidelines will emerge to ensure the safe and reliable deployment of AI-optimized materials and processes.
Originally reported by sciencedaily.com. CertificationNews adds analysis for science & discovery readers.