Material Point Method (MPM) is a particle based method that represents the material as a collection of material points, and their deformations are determined by Newton’s laws of motion. The MPM is a hybrid Eulerian-Lagrangian approach, which uses moving material points and computational nodes on a background mesh. This approach is very effective particularly in the context of large deformations.

algorithm

Illustration of the MPM algorithm (1) A representation of material points overlaid on a computational grid. Arrows represent material point state vectors (mass, volume, velocity, etc.) being projected to the nodes of the computational grid. (2) The equations of motion are solved onto the nodes, resulting in updated nodal velocities and positions. (3) The updated nodal kinematics are interpolated back to the material points. (4) The state of the material points is updated, and the computational grid is reset

CB-Geo MPM code

  • The CB-Geo MPM code is available at GitHub

Documentation

Team

Krishna Kumar

Assistant Professor, UT Austin
krishnak@utexas.edu

Thiago Ordonho Araujo

PhD candidate, UT Austin
thiago.araujo@utexas.edu

Brent Sordo

PhD candidate, UT Austin
bsordo@utexas.edu

Chihun Sung

PhD candidate, UT Austin
csung@utexas.edu

Publications

In-situ visualization of natural hazards with Galaxy and Material Point Method

Abram, G., Solis, A., Liang, Y., and Kumar, K.;
IEEE Computing in Science & Engineering

Visualizing regional-scale landslides is the key to conveying the threat of natural hazards to stakeholders and policymakers. Traditional visualization techniques are restricted to post-processing a limited subset of simulation data and are not scalable to rendering exascale models with billions of particles. In-situ visualization is a technique of rendering simulation data in real-time, i.e., rendering visuals in tandem while the simulation is running. In this study, we develop a scalable N:M interface architecture to visualize regional-scale landslides. We demonstrate the scalability of the architecture by simulating the long runout of the 2014 Oso landslide using the Material Point Method coupled with the Galaxy ray tracing engine rendering 4.2 million material points as spheres. In-situ visualization has an amortized runtime increase of 2\% compared to non-visualized simulations. The developed approach can achieve in-situ visualization of regional-scale landslides with billions of particles with minimal impact on the simulation process.

Investigating the thixotropic behaviour of tremie concrete using the slump‑flow test and the Material Point Method

Wilkes, C.; Kumar, K.; Biscontin, G.;
Concrete Rheology

A new thixotropic model is developed integrating the Papanastasiou-Bingham model with thixotropy equations to simulate the flow behaviour of Tremie Concrete in the Material Point Method framework. The effect of thixotropy on the rheological behaviour of fresh concrete is investigated by comparing field measurements with numerical simulations. The comparison yields new insights into a critical and often overlooked behaviour of concrete. A parametric study is performed to understand the effect of model parameters and rest-time on the shear stress response of fresh concrete. The Material Point Method with the Papanastasiou-Bingham model reproduces slump-flow measurements observed in the field. The novel model revealed a decline in concrete workability during the Slump-flow test after a period of rest due to thixotropy, which the physical version of the test fails to capture. This reduction in workability significantly affects the flow behaviour and the effective use of fresh concrete in construction operation.