Project institution: University of Glasgow
Project supervisor(s): Dr Zhiwei Gao (University of Glasgow), Dr Jingtao Lai (University of Glasgow), Prof Lukasz Kaczmarczyk (University of Glasgow), Dr Martin Hurst (University of Glasgow) and Hassan Al-Budairi (QTS Group)
Overview and Background
Global climate and environmental change are increasingly resulting in weather extremes that impact society and infrastructure. These extremes include stormier climates with increased wind speeds, precipitation events or drought, and temperatures (amongst other things). A team of University of Glasgow researchers are developing an Earth systems digital twin for exascale computing that works on GPU computers and uses weather forecasts to predict the cascading effect of climate change events on environmental systems. Our goal is to provide predictions, at the national or large scale, of the impacts of environmental extremes on natural and urban settings. This project is one, stand-alone, component of this larger-scale project.
In this project, you will develop and apply one component of the Earth system model. We are seeking a student interested in GPU-accelerated large deformation modelling of landslides in soil-rock mixtures (SRM) along UK coasts. SRM is a naturally occurring material composed of high-strength rock fragments embedded in a matrix of low-strength soil. It is a common geological formation found in mountainous regions, river valleys and coasts. One example is the glacial till widely seen in the UK. SRM exhibits significant heterogeneity and anisotropy due to the random distribution and varying proportions of rock blocks and soil. In this project, we will develop a GPU-accelerated multifield plasticity simulation for modelling landslides in SRM.
Your job while working on this project will involve software development for simulating the relevant physical processes, applying the model to historic data for model evaluation, working in a team/workgroup environment, attending regular research group seminars, integrating diverse environmental and satellite data into your software, and learning new techniques through ExaGEO training workshops.
Methodology and Objectives
Methods used in this project involve multiscale modelling of SRM at the element level and large deformation modelling using multifield plasticity. The result from the multiscale modelling will be used to develop a constitutive model for SRM.
Teaser Project 1: Multiscale modelling of SRM
The mechanical behaviour of SRM is governed by the interaction between its components, with rock blocks contributing to structural stability and the soil matrix often controlling deformation and failure. Its unique characteristics, such as non-uniform strength, variable permeability, a wide range of particle sizes, and complex stress distribution, make SRM challenging to test and model. For instance, measuring the stress-strain relationship of SRM requires large equipment to accommodate the rock fragments in the testing cell. Developing such equipment is time-consuming and expensive. Therefore, we will use the multiscale approach to model the element response of SRM. At the mesoscale, elements of the SRM will be modelled to capture the detailed microstructure, including the distribution and properties of rock fragments and soil. This will be done using the finite element code MoFEM which is GPU compatible. The rock fragments will be modelled as non-deformable solids and soils will be modelled using a suitable elastoplastic model. The mechanical properties obtained from the microscale models will then be upscaled to the macroscale using homogenisation techniques. The multiscale modelling results will be validated and calibrated using experimental data to ensure accuracy. This involves comparing simulation results with laboratory tests reported in the literature. These simulations provide effective material properties that can be used in developing constitutive models for the SRM that are needed in large-scale modelling.
Teaser Project 2: Large deformation modelling of landslides using multifield plasticity
The multifield plasticity developed at the Glasgow Computation Engineering Centre (GCEC) is a numerical method suitable for modelling large deformation problems, which eliminates the need for local integration of the elastoplastic model and can effectively exploit the computation power of GPUs. In the multifield framework, the balance of linear momentum, the flow rule, and the Karush–Kuhn–Tucker (KKT) constraints are formulated together within a variational framework. Beyond deformation, the plastic strain and the consistency parameter are treated as global degrees of freedom in the spatially discretised problem. To manage the increased number of global degrees of freedom, the method leverages the block sparse structure of the algebraic system and employs a customised block matrix solver designed to take advantage of modern hardware architectures. A constitutive model for the SRM will be implemented following the multifield plasticity and then used to model landslides in MoFEM. We will collaborate with research teams working on field observations and large-scale modelling in this development.
References and Further Reading
- Lewandowski, K., Barbera, D., Blackwell, P., Roohi, A. H., Athanasiadis, I., McBride, A., … & Kaczmarczyk, Ł. (2023). Multifield finite strain plasticity: Theory and numerics. Computer Methods in Applied Mechanics and Engineering, 414, 116101
- Gao, W. W., Gao, W., Hu, R. L., Xu, P. F., & Xia, J. G. (2018). Microtremor survey and stability analysis of a soil-rock mixture landslide: a case study in Baidian town, China. Landslides, 15, 1951-1961
- Gao, W., Yang, H., & Hu, R. (2022). Soil–rock mixture slope stability analysis by microtremor survey and discrete element method. Bulletin of Engineering Geology and the Environment, 81(3), 121
- Qiu, Z., Liu, Y., Tang, S., Meng, Q., Wang, J., Li, X., & Jiang, X. (2024). Effects of rock content and spatial distribution on the stability of soil rock mixture embankments. Scientific Reports, 14(1), 29088
- Li, J., Wang, B., Wang, D., Zhang, P., & Vardon, P. J. (2023). A coupled MPM-DEM method for modelling soil-rock mixtures. Computers and Geotechnics, 160, 105508
