Chen, Liuxin, Ghorbani, Javad, and Kodikara, Jayantha (2024) Modelling of shakedown, ratcheting and liquefaction of saturated granular soils using kinematic hardening with memory surface. Computers and Geotechnics, 165. 105830.

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Abstract

The present paper proposes a kinematic hardening model with a memory surface to more accurately reproduce cyclic hardening and the behaviour of saturated granular soils subjected to cyclic loads. The new cyclic hardening law offers improved accuracy in predicting soil ratcheting in drained conditions and failures due to liquefaction in undrained conditions. Simulating these two aspects has been challenging due to issues such as significant loss of accuracy and numerical instability, particularly under extended (or a large number of) cyclic loads. To deal with the challenge, in addition to the novel theoretical framework, we also developed a robust sub-stepping algorithm based on an explicit stress integration scheme with automatic error control. The proposed model is compared with several existing models and its performance is evaluated by conducting sensitivity analyses and performing validations against a wide range of laboratory test results.

Item ID:	85646
Item Type:	Article (Research - C1)
ISSN:	1873-7633
Copyright Information:	© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Date Deposited:	28 May 2025 03:06
FoR Codes:	40 ENGINEERING > 4005 Civil engineering > 400502 Civil geotechnical engineering @ 50% 40 ENGINEERING > 4005 Civil engineering > 400503 Complex civil systems @ 25% 40 ENGINEERING > 4005 Civil engineering > 400599 Civil engineering not elsewhere classified @ 25%
SEO Codes:	12 CONSTRUCTION > 1206 Environmentally sustainable construction activities > 120699 Environmentally sustainable construction activities not elsewhere classified @ 50% 27 TRANSPORT > 2702 Environmentally sustainable transport activities > 270299 Environmentally sustainable transport activities not elsewhere classified @ 50%
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