Advances in numerical methods have provided useful tools to investigate 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 of 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 insights 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.
Simulating landslides with the material point method: Best practices, potentialities, and challenges
Francesca Ceccato
;
2024
Abstract
Advances in numerical methods have provided useful tools to investigate 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 of 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 insights 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.File | Dimensione | Formato | |
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