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 ...
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Predicting material failure: Machine learning spots early abnormal grain growth signs for safer designs
A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time—a development that could lead to the creation of ...
Periodic maintenance is common too, but still inefficient and often based on time, not actual machine condition. That ...
Within the prior 24 months, I have had a financial relationship with a company producing, marketing, selling, re-selling, or distributing healthcare products used by or on patients: Receive the the ...
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