# Research Advances in Large Deformation Analysis and Applications of the Material Point Method
## 7 Application in Fluid-Structure Interaction
discretization (see Figure 25), where Lagrangian marker points act as a bridge between multiphase flows and solids. The coupling of the LBM and MPM can effectively capture the interactions between fluids and solids and even perform multiphase flow analysis at the pore scale. However, this coupled algorithm has low computational efficiency, especially in 3D cases. Debris flows, such as landslides and mudslides, often involve large deformations and interactions between fluids, solids, and particles. Analyzing these mixed flows using only continuous medium methods or discontinuous methods is inappropriate. To address this, many scholars have developed MPM-DEM coupling methods for continuous-discontinuous mechanics problems involving fluid-solid coupling. The MPM is used to handle the large deformations of solid and liquid phases, while the DEM captures the motion of particles. [PERSON] et al. [120] simulated landslides involving fluids, soil, and rocks by converting the MPM points into DEM particles and calculating the contact forces between material points and the DEM particles within a unified DEM framework, thereby determining the contact between the MPM objects and DEM particles, as shown in Figure 26. To improve computational efficiency, [PERSON] et al. [121] proposed a scheme to convert material points in contact with DEM particles into virtual DEM particles, modeling soil with fewer particles and larger particle diameters. [PERSON] et al. [122] used a two-phase \(u\)-\(v\)-\(p\) MPM to solve the fluid-solid coupling problems in saturated porous media and proposed a semi-implicit integration scheme based on a splitting algorithm. [PERSON] et al. [123] developed a three-phase MPM-DEM coupling method to simulate multiphase, multi-physical field, and multi-scale problems in frozen and thawed granular media, where the MPM solver uses a semi-implicit staggered integration scheme, allowing for larger time steps and providing better computational efficiency for the DEM. [PERSON] et al. [124] proposed a CPU-GPU parallel solution scheme. Despite the development of various MPM models and their coupling schemes, which have achieved certain application results in FSI analysis, there are still some difficulties in practical applications: (1) The interpenetration and entanglement between solid and fluid regions make the boundary between the two vague, which poses a challenge in determining precise boundary conditions, especially when dealing with fluid-solid coupling seepage problems in porous media at the microscale. (2) In the process of fluid-solid coupling analysis, it is necessary to transfer key data, such as displacement, velocity, and pressure, between different grid systems. However, different interpolation techniques may lead to discontinuities in data at the coupling interface, thereby affecting the accuracy of the  
Figure 18:0 Schematic diagram of four groups of spatial discretization [119]. simulation results. (3) When dealing with large-scale FSI problems, the MPM requires tracking and updating the positions and velocities of a large number of material points at each time step, which inevitably increases the computational cost. (4) It is challenging to embed the constitutive equations of shear-thinning/shear-thickening fluids, such as blood and lava. The coupling simulation of these non-Newtonian fluids with solids is prone to large errors.