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Researchers employ artificial intelligence to unlock the secrets of magnesium alloy anisotropy
Magnesium (Mg) alloys have been popularly used for designing aerospace and automotive parts owing to their high strength-to-weight ratio. Their biocompatibility and low density also make these alloys ideal for use in biomedical and electronic equipment. However, Mg alloys are known to exhibit plastic anisotropic behavior. In other words, their mechanical properties vary depending on the direction of the applied load.
To ensure that the performance of these Mg alloys is unaffected by this anisotropic behavior, a better understanding of the anisotropic deformations and the development of models for their analysis is needed.
According to Metal Design & Manufacturing (MEDEM) Lab led by Associate Professor Taekyung Lee from Pusan National University, Republic of Korea, machine learning (ML) might hold answers to this prediction problem. In their recent breakthrough, the team proposed a novel approach called "Generative adversarial networks (GAN)-aided gated recurrent unit (GRU)."
What appears to be a picture made from assorted grains and seeds glued to canvas. Stamp on the back said it was from Pusan, South Korea. Found in a Myrorna secondhand store in Sweden.
M4 Sherman, 89th Tank Battalion. Pusan Perimeter, South Korea.
An M4 Sherman of 89th Tank Battalion somewhere on the southern side of the Pusan Perimeter on August 12, 1950. This was likely taken near Chinju, South Korea during Task Force Kean’s counterattack in that area