Multiscale modeling of natural hazards

MPM, LBM-DEM and ML


Krishna Kumar, krishnak@utexas.edu
Rei Hosseini, Qiuyu (Amber) Wang, and Chihun Sung
University of Texas at Austin



Boase Seminar Series

CU Boulder, 29th Oct 2021

Geoelements Extremescale Computational Geomechanics

  • Material Point Method
  • Lattice-Boltzmann + Discrete Element Method
  • Finite Element Method - Thermo-Hydro Mechanical Coupling
  • Lattice Element Method
View the Geoelements website for more information and software tools

Scales of modeling

Oso landslide (2014)

8 million cubic meters of glacial deposits and water-filled debris material transported to a distance of 1 km (Haugerud., 2014).

Oso landslide (2014)

Mesh-based vs Mesh-free techniques

Material Point Method

Oso Landslide Topography

MPM model setup

MPM simulation of Oso landslide

Yerro et al., 2017

Simulation of Oso with X-MPM

Yong Liang, Kenichi Soga, and Krishna Kumar

MPM Towards exascale simulations

What is Ray Tracing?

What is Ray Tracing?

Two-phase MPM rendering

In-situ visualization

MPM Oso landslide rendering

In-situ visualization of Oso with MPM and Galaxy

Submarine run-out

Credit: Amanda Murphy (2016)

Mechanism of submarine runout

Mechanism of submarine landslides

Modeling Test at 1g Condition

  • Material type influences the mode of the flow.
  • Target: Clay‐rich flow (Less diffusive, Hydroplaning).

LBM - DEM simulation of granular collapse in a fluid




aspect ratio 'a' of 6

Discrete Element Method

  • Particle level interaction based on Newton's equation of motion

  • The contact force is computed as:

    • $F_n=\left\{ \begin{matrix} \text{ }0\text{ },\text{ }{{\delta }_{n}}>0 \\ -{{k}_{n}}{{\delta }_{n}}-{{\gamma }_{n}}\frac{d{{\delta }_{n}}}{dt},\text{ }{{\delta }_{n}}<0 \\ \end{matrix} \right.$

  • The Newton's equation of motion

    • $F_n =m \times a $

Fluid-grain systems


Lattice Boltzmann - MRT

Real Fluid vs LBM Idealisation
LBM D2Q9 Model

\[f_{i}(x + dx, t +\Delta t) - f_{i}(x, t) = -S_{\alpha i}( f_{i}(x, t) - f_{i} ^ {eq}(x, t))\]
  • $S_{\alpha i}$ is the collisional matrix.
  • Probability density of finding a particle : $f(x,\varepsilon, t) $, where, x is position, $\varepsilon$ is velocity, and t is time.
Streaming
Collision

LBM-DEM fluid-solid coupling

$$\Delta t_{s}=\frac{\Delta t}{\mathit{n}_{s}} \qquad (\mathit{n}_{s}=[\Delta t/ \Delta t_{D}]+1) $$
  • At every fluid iteration, $\mathit{n}_{s}$ sub-steps of DEM iterations are performed using the time step $\Delta t_{s}$.
  • The hydrodynamic force is unchanged during the sub-cycling.

LBM - DEM a = 0.8 & 10,000 particles



  • LBM Nodes = 50 Million : DEM grains = 10000 discs
  • Run-time = 4 hours
  • Speedup = 125x on a Pascal P100

Collapse in a fluid

Collapse in a fluid ('a'=0.8)

Loose v dense: Runout distance

Loose
Dense

Collapse on slopes: loose v dense

runout evolution ('a' of 0.8)

Loose v dense: Initiation phase

initial runout evolution ('a' of 0.8)

Loose v dense: Initiation phase

Loose
Dense

Pore-pressure distribution along the failure plane during initiation.

Loose v dense: Runout phase

Attack angle ('a' of 0.8) $t = 3 \tau_c $

Loose v dense: Runout phase

Loose
Dense
Water entrainment front (~15d length) at a slope of 5*

Two-phase MPM Submarine landslide

Multiphase LBM

Shan-Chen Multiphase LBM

Coexistance densities

Multiphase LBM: Effect of varying the contact angle

Fully hydrophilic surface
(θ = 0°)
Fully hydrophobic surface
(θ = 180°)
Neutral surface
(θ = 90°)

Multiphase LBM: Hysteresis in Hamburg sand

Multiphase LBM: Hysteresis

Microscale features

Multiphase system
Solids
Fluids

Multiphase LBM: Origin of Hysteresis

Micromechanics of unsaturated behavior

Multiphase LBM: Capillary structures

Neutral surface
(θ = 90°)

Two-phase MPM Rainfall induced landslide

Deep learning

Physics-informed Graph Attention Networks

GAT simulator








Krishna Kumar

krishnak@utexas.edu






View the Geoelements website for more information and software tools