the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Shallow landslides modeling using a particle finite element model with emphasis on landslide evolution
Abstract. Numerical modelling is a powerful tool to study the mechanism of landslides and constructs the foundation of many physically-based assessment methods applied to natural hazards. Usually, numerical analyses of landslides are carried out on the failure mechanism and on the propagation process separately. With the advantage of dealing with large deformation problems, the particle finite element method (PFEM), that is the particle extension of the traditional FEM, has the capability of simulating the entire evolution of the landslide from the generation to the deposition phase. To figure out the difference between a unified PFEM simulation and the usually adopted approaches that separate failure mechanism (static analysis) and run-out analysis (dynamic analysis), we implement a PFEM code that is applied first to a simple homogeneous slope model. Numerical results reveal that under the so-called critical condition the landslide comes to a stop with a slight modification of the original profile, while its profile is drastically changed if strength reduction is further applied. To test the capability of our model, we choose the 2013 Cà Mengoni landslide, northern Apennines, Italy, as a case study, since it behaved as if it were formed by homogeneous material. In virtue of the back-analysis of the run-out distance that we perform by using different material strength parameters, we show that the PFEM model is able to capture the variation of the observed landslide profile, and contributes to the understanding of the dynamics of the whole sliding process.
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Interactive discussion
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RC1: 'Review of 'Shallow landslides modeling using a particle finite element model with emphasis on landslide evolution'', Anonymous Referee #1, 28 May 2019
- AC1: 'Reply to Referee #1', Liang Wang, 13 Jun 2019
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RC2: 'Review 2', Anonymous Referee #2, 31 May 2019
- AC2: 'Reply to Referee #2', Liang Wang, 13 Jun 2019
- EC1: 'Associate editor's recommendation', Xuanmei Fan, 23 Jun 2019
Interactive discussion
-
RC1: 'Review of 'Shallow landslides modeling using a particle finite element model with emphasis on landslide evolution'', Anonymous Referee #1, 28 May 2019
- AC1: 'Reply to Referee #1', Liang Wang, 13 Jun 2019
-
RC2: 'Review 2', Anonymous Referee #2, 31 May 2019
- AC2: 'Reply to Referee #2', Liang Wang, 13 Jun 2019
- EC1: 'Associate editor's recommendation', Xuanmei Fan, 23 Jun 2019
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5 citations as recorded by crossref.
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- Probabilistic Tsunami Hazard and Risk Analysis: A Review of Research Gaps J. Behrens et al. 10.3389/feart.2021.628772
- Landslide susceptibility mapping using artificial neural network tuned by metaheuristic algorithms M. Mehrabi & H. Moayedi 10.1007/s12665-021-10098-7
- Recognition of landslide triggers in southeast Tibetan (China) using a novel lightweight network D. Liu et al. 10.1007/s12665-022-10356-2
- A review on the application of particle finite element methods (PFEM) to cases of landslides F. Sengani & F. Mulenga 10.1080/19386362.2020.1814027