Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/116683
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.contributorResearch Institute for Land and Spaceen_US
dc.creatorLiu, Yen_US
dc.creatorWu, Pen_US
dc.creatorLi, Aen_US
dc.creatorFeng, Wen_US
dc.creatorChen, Zen_US
dc.creatorZhao, Xen_US
dc.creatorZheng, JJen_US
dc.creatorYin, JHen_US
dc.date.accessioned2026-01-12T05:59:50Z-
dc.date.available2026-01-12T05:59:50Z-
dc.identifier.issn1861-1125en_US
dc.identifier.urihttp://hdl.handle.net/10397/116683-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© The Author(s) 2025.en_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Liu, Y., Wu, P., Li, A. et al. A finite strain thermal elastic visco-plastic consolidation model enhanced by particle swarm optimization of model parameters. Acta Geotech. (2025) is available at https://doi.org/10.1007/s11440-025-02773-x.en_US
dc.subjectFinite strain consolidationen_US
dc.subjectParameter calibrationen_US
dc.subjectPhysical model testen_US
dc.subjectPSO-assisted methoden_US
dc.subjectThermal elastic visco-plasticityen_US
dc.titleA finite strain thermal elastic visco-plastic consolidation model enhanced by particle swarm optimization of model parametersen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1007/s11440-025-02773-xen_US
dcterms.abstractIn this paper, a radial finite strain thermal consolidation model is extended to further consider the viscous behavior of soft soils. A newly developed thermal elastic visco-plastic (TEVP) constitutive model for the temperature and time-dependent stress–strain behavior of soft soils is implemented in a radial finite strain thermal consolidation model, which is solved through a numerical solver. This solving method is verified by comparing the calculated results by the numerical solver with two existing studies. After this, a particle swarm optimization (PSO) algorithm is employed to enhance the prediction performance of the proposed consolidation model by automatically calibrating the model parameters during the consolidation process. Two physical model tests were conducted to examine the validity of the proposed model and PSO-assisted method. The results indicate that the proposed radial consolidation model captures the viscous characteristics (including creep) of the time-dependent settlements of soft soils, which could not be simulated by the former reported models. The PSO-assisted method has demonstrated practical applicability when compared with physical model tests. The longer the observation time, the better the predictive performance of our radial finite strain thermal consolidation model. It is recommended that the observation time should not be shorter than the time required for primary consolidation.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationActa geotechnica, Published: 18 November 2025, Online first articles, https://doi.org/10.1007/s11440-025-02773-xen_US
dcterms.isPartOfActa geotechnicaen_US
dcterms.issued2025-
dc.identifier.scopus2-s2.0-105022456050-
dc.identifier.eissn1861-1133en_US
dc.description.validate202601 bcjzen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TA-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextFunding text 1: Open access funding provided by The Hong Kong Polytechnic University.; Funding text 2: The work presented in this paper is supported by the Research Grants Council (RGC) of Hong Kong Special Administrative Region Government (HKSARG) of China (GRF: 15210020, 15221721, and 15226722). The work is also supported by the Natural Science Foundation of Wuhan (No.2024040801020271) and Fundamental Research Funds for Central Public Welfare Research Institutes of China (No. CKSF20241004/YT). The authors also acknowledge the financial support from three grants (CD7A and CD7J) from Research Institute for Land and Space, a postdoctoral matching fund scheme (W314), and a start-up fund (BD30) of The Hong Kong Polytechnic University.en_US
dc.description.pubStatusEarly releaseen_US
dc.description.TASpringer Nature (2025)en_US
dc.description.oaCategoryTAen_US
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