AI to calculate materials’ stress- researchers from MIT have designed a new tool. The new AI tool helps the material engineers measure the material’s stress with the help of photographs. Engineers, physicists, and scientists have always spent lots of time and effort solving arduous equations. These equations would help them find the stress, strain, and other parameters for materials. But the new suggested tool helps avoid the conventional method and simply see through these parameters with the help of pictures.
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AI to calculate materials’ stress– real-time estimation
Zhenze Yang, Chi-Hua and Markus Buehler are the MIT co-authors of the study. Their research is published in the journal called Science Advances. And the researchers claim that the approach could generate material’s stress estimates in real-time instead of slogging on heavy equations. Zhenze quotes, “it’s a brand new approach. And completes the whole process without any domain knowledge of physics.” While Buehler adds, “Many generations of mathematicians and engineers have written down these equations and then figured out how to solve them on computers”. Now, the generative adversarial neural network is the AI to calculate material stress that these researchers have turned to. They used a huge number of paired images to train this neural network. And established a relation between the material’s microstructure and its mechanical aspects, the stress and strain. The AI model thus also utilizes the concept of game theory as well.
Final Thoughts:
As, the model of AI to calculate materials’ stress, uses some concepts of game theory, machine learning, and neural network, it promises to be a better approach. This picture-co relation approach is especially advantageous for a set of complex and composite materials. And materials’ microstructure is different at the atomic scale and it is different at the macroscale. So, the model is also capable of operating at these levels. Not just the model will be extremely helpful for engineers and material architects alike, but will also help the non-engineers in developing a good understanding of materials.
