Videos
DEM Simulations & Animations
Elongated Particle Deposition & Shearing (Linear Split-Bottom Cell) | DEM
DEM simulation of elongated particles (multisphere sticks) deposited into a linear split-bottom shear cell under gravity. After settling, the two bottom plates move in opposite directions, generating a localized shear band near the split (y = 0). Coordinates: shear direction x, lateral direction y, vertical direction z.
Shear-Induced Surface Depression (Elongated Particles, DEM)
At intermediate friction (µ = 0.3), particle alignment inside the shear band leads to local compaction and a surface depression above the split region (y = 0). Colors show the streamwise velocity Vx (m/s).
Elongated particles under shear: mixing near the shear band (MercuryDPM, DEM)
Particles are colored by their initial y-position to visualize mixing across the shear zone. Mixing is observed mainly near the shear band, while regions outside remain nearly static.
Shear-Induced Dilatancy at High Friction (Elongated Particles, DEM)
At high friction (µ = 0.8), shear-induced dilatancy becomes pronounced inside the shear band for a dense granular packing, producing a localized surface uplift near the split region (y = 0). Colors show the streamwise velocity Vx (m/s).
Wide Surface Depression at Low Friction (µ = 0.01) | Elongated Particles (DEM)
At low friction (µ = 0.01), particles reorient easily and align with the shear direction, leading to strong compaction. The shear band becomes wide and delocalized, causing a broad surface depression across the system.
Packing Density Field at Large Friction (µ = 0.8) | Elongated Particles (DEM)
Packing density field φ(y, z) (averaged along the x-direction), computed using MercuryCG, for elongated particles in a linear split-bottom shear cell. At high friction (µ = 0.8), shear localizes into a narrow shear band, and particle rearrangement is hindered, enhancing shear-induced dilatancy and surface uplift near the split (y = 0). The colorbar shows the packing density φ, and the simulation time is displayed at the top of the frame.
Packing Density Field at Low Friction (µ = 0.01) | Elongated Particles (DEM)
At low friction (µ = 0.01), particles rearrange easily, and the shear band becomes wide, leading to relatively uniform packing density across the bulk. The colorbar shows the packing density φ, and the simulation time is displayed at the top of the frame.
Particle-Scale Orientation at High Friction (µ = 0.8) | θx (DEM)
Particle-scale visualization of elongated particle orientations in a linear split-bottom shear cell. Each line shows a particle’s principal axis, colored by the orientation angle θx relative to the shear direction (x). At high friction (µ = 0.8), shear localizes, and dilatancy becomes pronounced inside the shear band, producing surface uplift near the split. Local rearrangements can create partial alignment and compaction at the surface, leading to a depression on top of the uplifted region. Colors represent θx scaled from 0 to 1: 0 = perfect alignment, 1 = perfect misalignment. The simulation time is shown at the top of the frame.
Particle-Scale Orientation at Low Friction (µ = 0.01) | θx (DEM)
Each line shows a particle’s principal axis, colored by the orientation angle θx relative to the shear direction (x). At low friction (µ = 0.01), particles align easily inside the wide shear-band region, leading to alignment-induced compaction and a broad surface depression. Colors represent θx scaled from 0 to 1: 0 = perfect alignment, 1 = perfect misalignment.
Histogram of Particle Alignment in the Shear Band | DEM
Histogram of elongated particle orientation angles inside the shear band of a linear split-bottom shear cell.
Initially, most particles are misaligned, with angles clustered around 90°. As shear progresses, the distribution shifts toward 0° and 180°, indicating increasing alignment with the shear direction.
Here, 0°/180° = parallel to shear, while 90° = perpendicular (misaligned).
Extracting the Free Surface in 3D (Granular DEM Post-Processing)
Post-processing of DEM data to extract the granular free surface.
The domain is discretized in (x, y), and for each lattice cell the free surface is defined as the maximum particle height zmax(x, y).
This extracted surface can be used to compute surface profiles and global measures such as the area under the surface (A/A0).
Dilatancy-induced heap formation in dense cohesive granular media (DEM)
Cohesion is introduced via liquid bridges between particles. In the cohesive case, dilatancy in the shear band leads to surface elevation and heap formation. Without cohesion, the surface remains nearly flat.
Robotic Arm Pattern Formation (Yin–Yang Mosaic) | Python Automation (students project)
Python-controlled robotic arm performing automated pick-and-place to generate a predefined pattern.
A vacuum end-effector is used to grasp and position colored spherical particles to form a Yin–Yang mosaic.
The same control framework was applied to irregular particles (e.g., rice grains), demonstrating stable manipulation across varying particle geometries.
The suction system generates a controlled pressure differential for particle gripping.
The outlet was sealed to prevent air leakage, ensuring consistent holding force and placement stability.
Sensor Fusion for Motion Estimation (Kalman Filter, Python)
Simulation of 2D motion with noisy accelerometer and low-rate GPS measurements.
A Kalman filter is used to estimate position and velocity by combining both sensors.
The filtered trajectory is smoother and more accurate than raw measurements, demonstrating how model-based estimation reduces noise and drift.
Battery Digital Twin (Thermal Estimation, Python)
Simulation of a battery thermal system with noisy temperature measurements.
A simple digital twin estimates the internal temperature using recursive filtering.
Blue: true temperature
Orange: noisy sensor
Green: estimated temperature
The estimator removes noise and tracks the underlying state.