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A nodal-integration based particle finite element method (N-PFEM) to model cliff recession
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0003-0148-9779
Department of Civil Engineering and Industrial Design, University of Liverpool, Liverpool, United Kingdom.
School of Engineering, Newcastle University, Newcastle, United Kingdom.
International Centre for Numerical Methods in Engineering (CIMNE), Barcelona, Spain.
2021 (English)In: Geomorphology, ISSN 0169-555X, E-ISSN 1872-695X, Vol. 381, article id 107666Article in journal (Refereed) Published
Abstract [en]

Cliff recession poses a significant threat to the built environment, transportation infrastructure and land use. In this paper, a novel computational framework called the Nodal-integration based Particle Finite Element Method (N-PFEM) is developed for modelling the cliff recession resulting from weathering-induced landslides. The N-PFEM combines the nodal-integration technique with the PFEM in second-order cone programming and thus requires no variable mapping operation, which is essential in the classical PFEM for modelling history-dependent materials, for modelling large deformation problems such as landslides in cliff recession processes. To verify the developed N-PFEM, a series of benchmarks have been simulated including the cliff recession under both the weathering-limited and transport-limited conditions. Simulation results from the N-PFEM are validated in detail to these from the limit analysis method, well established geomorphologic models and the discrete element method. Additionally, measures for preventing cliff recession such as the construction of retaining wall structures are also investigated using the N-PFEM.

Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 381, article id 107666
Keywords [en]
Cliff recession, Landslide, PFEM, Nodal integration
National Category
Geotechnical Engineering
Research subject
Soil Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-83089DOI: 10.1016/j.geomorph.2021.107666ISI: 000634863000005Scopus ID: 2-s2.0-85102473349OAI: oai:DiVA.org:ltu-83089DiVA, id: diva2:1531635
Note

Validerad;2021;Nivå 2;2021-03-23 (johcin)

Available from: 2021-02-26 Created: 2021-02-26 Last updated: 2021-05-04Bibliographically approved

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Meng, Jingjing

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