Prediction of elastic stresses in porous materials using fully convolutional networks
Sign Up to like & getrecommendations! Published in 2021 at "Scripta Materialia"
DOI: 10.1016/j.scriptamat.2021.113805
Abstract: Abstract Machine learning (ML) models enable exploration of vast structural space faster than the traditional methods, such as finite element method (FEM). This makes ML models suitable for stochastic fracture problems in brittle porous materials.… read more here.
Keywords: prediction elastic; fully convolutional; convolutional networks; porous materials ... See more keywords
Elastic stresses reverse Ostwald ripening.
Sign Up to like & getrecommendations! Published in 2020 at "Soft matter"
DOI: 10.1039/d0sm00628a
Abstract: When liquid droplets nucleate and grow in a polymer network, compressive stresses can significantly increase their internal pressure, reaching values that far exceed the Laplace pressure. When droplets have grown in a polymer network with… read more here.
Keywords: reverse ostwald; elastic stresses; stresses reverse; network ... See more keywords