首页|New Findings Reported from PSL University Describe Advances in Machine Learning (A Plastic Correction Algorithm for Full-field Elasto-plastic Finite Element Sim ulations: Critical Assessment of Predictive Capabilities and Improvement By Mach ine ...)
New Findings Reported from PSL University Describe Advances in Machine Learning (A Plastic Correction Algorithm for Full-field Elasto-plastic Finite Element Sim ulations: Critical Assessment of Predictive Capabilities and Improvement By Mach ine ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Machine Learning have be en published. According to news reporting out of Evry, France, by NewsRx editors , research stated, “This paper introduces a new local plastic correction algorit hm that is aimed at accelerating elasto-plastic finite element (FE) simulations for structural problems exhibiting localised plasticity (around e.g. notches, ge ometrical defects). The proposed method belongs to the category of generalised m ulti-axial Neuber-type methods, which process the results of an elastic predicti on point-wise in order to calculate an approximation of the full elasto-plastic solution.”
EvryFranceEuropeAlgorithmsCyborg sEmerging TechnologiesMachine LearningPSL University
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