An AI‐based model for describing cyclic characteristics of granular materials

Summary Modelling cyclic behaviour of granular soils under both drained and undrained conditions with a good performance is still a challenge. This study presents a new way of modelling the cyclic behaviour of granular materials using deep learning. To capture the continuous cyclic behaviour in time...

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Vydané v:	International journal for numerical and analytical methods in geomechanics Ročník 44; číslo 9; s. 1315 - 1335
Hlavní autori:	Zhang, Pin, Yin, Zhen‐Yu, Jin, Yin‐Fu, Ye, Guan‐Lin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Bognor Regis Wiley Subscription Services, Inc 25.06.2020
Predmet:	Computer simulation constitutive model Constitutive models Cyclic loading Cyclic loads deep learning Deformation Deformation effects Densification Dimensions Granular materials Learning behaviour liquefaction Machine learning Mathematical models Modelling neural network Neural networks Sand Shear strain Soil Soils
ISSN:	0363-9061, 1096-9853
On-line prístup:	Získať plný text
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