Simulating landslides with the material point method: Best practices, potentialities, and challenges
Engineering Geology, ISSN: 0013-7952, Vol: 338, Page: 107614
2024
- 2Citations
- 31Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Review Description
Advances in numerical methods have provided useful tools for investigating the complex behaviour of landslides, which can be a valuable support for landslide hazard assessment, planning, and design of mitigation measures. Among different methodologies, the Material Point Method (MPM) has recently grown in popularity, thanks to its ability to simulate large displacements and has been applied to simulate an increasing number of real cases. Despite the success, there are still several challenges to be addressed. This paper aims to present the current state of the art in the modelling of real landslide case histories with MPM. The key numerical features used to capture the evolution of different types of landslides are discussed, such as constitutive models, soil-water interaction, and triggering mechanisms, thus providing insight into the computational aspects of using MPM to serve as guidelines for future applications. Limitations and future perspectives are also mentioned to encourage the development of new solutions for current numerical challenges and further extend the applicability of the methodology in this field.
Bibliographic Details
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know