Simulating an earthquake is not impossible and scaled models in both fluid and solid mechanics are still useful in determining whether the design satisfies the requirements or not. CAE is useful in reducing the number of physical prototype iterations in physical testing. Before CAE lets say 20 physical prototypes needed to be created and lab-tested to arrive at the preliminary design, after CAE only 8 would be needed as the remainder 12 would have been eliminated by virtually in the computer itself.
Good job Pritish! A very straight forward approach to CAE. Refreshing to see
Thank you for the valuable content for CAE.
Nothing is mentioned about machine learning .. absolutely misleading ...
Nothing about AI? Title misleading ?
Yea LOL, I kept waiting until I realized the video is about to end.
Simulating an earthquake is not impossible and scaled models in both fluid and solid mechanics are still useful in determining whether the design satisfies the requirements or not. CAE is useful in reducing the number of physical prototype iterations in physical testing. Before CAE lets say 20 physical prototypes needed to be created and lab-tested to arrive at the preliminary design, after CAE only 8 would be needed as the remainder 12 would have been eliminated by virtually in the computer itself.
Most interesting and amazing vidwo
Thank you🎉
Thank you sir👍
Then why you use machine learning in tagline .
No single word about AI? Title misleading?