Morning Overview on MSN
Physics-trained AI models speed engineering design and simulations
When engineers at Sumitomo Riko needed to speed up the design cycle for automotive rubber and polymer components, they turned ...
A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...
(a) A feasible route for developing large materials models capable of describing the structure-property relationship of materials. The universal materials model of DeepH accepts an arbitrary material ...
Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
Researchers from the University of South China and Purdue University have developed ultra-high strength, high-ductility steel ...
As AI's integration in the process of designing and improving industrial infrastructure progresses, governance needs to ...
Morning Overview on MSN
Physics-trained AI models speed up engineering simulations and design work
Running a single physics simulation can take hours or days, depending on the complexity of the geometry and the equations ...
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