Nut Mixing and Packaging System Simulation in EDEM - Material Dosing
Altair EmployeeA significant proportion of food produced globally is never consumed, with around 14% lost between production and retail [1]. While food loss can occur at various stages of the supply chain, improving bulk material handling in food processing—through virtual testing and system optimization—can help reduce losses and improve production efficiency.
Designing an effective particle dosing and packaging system presents several challenges, including:
- Controlling Particle Movement
- Preventing Segregation
- Precise Release Mechanisms
- Optimizing Efficiency & Reducing Waste
This blog post demonstrates how Altair® EDEM™ can be used to simulate a nut packaging system (see Figure 1), offering insights into particle behavior and providing a virtual environment to evaluate and optimize the feeding process prior to packaging.
Figure 1 – Simulation of the nut packaging system
The simulation deck corresponding to the nut mixer example is provided below:
How EDEM Enables Smarter Feeding System Design
Altair® EDEM™ enables engineers to build detailed DEM simulations that replicate bulk material behavior in processes such as handling, feeding, and mixing. It provides a virtual environment to assess system design and optimize material flow.
Simulations help improve efficiency, reduce segregation, and minimize material loss—while avoiding the cost and time of physical prototyping.
For new users, a summary of key learning resources is available in the blog post linked below:
4 Steps to Accelerate your Learning
Step 1: Setting the Material Model
The first step is to define the material properties for both the nut particles—almonds, pistachios, walnuts, hazelnuts, and cashews—and the system components. These properties govern how all materials interact and move within the simulation.
While material calibration is typically recommended in EDEM to improve accuracy and reflect real-world behavior, this example uses non-calibrated models with realistic values for each nut type, which are sufficient for demonstrating system behavior and particle interactions in this context.
Users looking to explore calibration in more detail can refer to the resources below:
Calibration Blog Post - Discrete Element Method Calibration with EDEM
Calibration eLearning Videos – EDEM Calibration eLearning
Step 2: Defining Particle Shape Using Polyhedral Particles
Accurately representing particle shape is crucial, as it directly impacts how materials flow, stack, and mix. In this simulation, all nut types—almonds, pistachios, walnuts, hazelnuts, and cashews—were modelled as concave polyhedral particles, created as 3D CAD models and imported into EDEM.
Using polyhedral particles allows for a more realistic capture of each nut's unique shape and surface detail (see Figure 2), which supports more accurate modeling of mixing and segregation. However, this approach comes with increased computational cost compared to simpler shapes like multi-sphere particles.
Figure 2 – A section of walnuts on the conveyor; made using Altair® Inspire™ Studio
While the materials were not calibrated, the coefficient of static friction was adjusted to reduce excessive sliding, and the coefficient of restitution was tuned to minimize unrealistic bouncing during interactions.
Step 3: Importing CAD Geometry
EDEM supports various CAD file formats, including STL, STEP, and IGES, allowing users to import custom equipment models (see Figure 3).
Geometries can be imported via Creator > Geometries > Import Geometry and are automatically meshed unless the format already includes a predefined mesh. While mesh size generally has minimal impact on DEM results, manual mesh adjustments may be useful for wear analysis or detailed contact interactions as wear is plotted per triangular mesh element.
Figure 3 – CAD model of nut mixer in EDEM
Step 4: Introducing Material
To ensure a continuous supply of nuts, all particles are introduced using dynamic factories positioned over the central plate. Each factory geometry is shaped to match its designated 1/5th section of the decagonal plate and is defined in EDEM as a virtual geometry (see Figure 4). This allows each factory to more precisely conform to its section, enabling smoother and more even particle distribution than default EDEM shapes such as polygons or cylinders, which may not accurately reflect the section's geometry. This setup keeps the central plate consistently full, allowing nuts to accumulate before reaching the conveyors.
A small initial velocity is also applied in the vertical (Z) direction to reduce particle overlap and improve factory efficiency.
Figure 4 – Top view of system; showcasing factory geometries and generated nuts
Step 5: Assigning Kinematics
Different kinematic motions are assigned to control nut movement throughout the system (see Figure 5):
Sinusoidal Motion on the Central Plate
- A constant sinusoidal vibration is applied in the vertical (Z) direction, allowing nuts to slowly move evenly in the horizontal direction and onto the conveyor plates.
Linear Conveyor Motion on Conveyor Plates
- At the start and to get the system to reach steady-state sooner, a linear conveyor motion is used to move nuts closer to the ends of the conveyors, positioning them near the catchers.
Sinusoidal Vibrations (Bursts) on Conveyor Plates
- Periodic sinusoidal bursts applied across entire conveyors to push nuts into catchers in controlled amounts, preventing excessive material flow.
Rotating Discharge Plate in Catchers
- Each catcher is equipped with a rotating discharge plate at its base, which briefly opens when a defined torque threshold is exceeded. This allows the nuts to drop into the hopper before the plate quickly closes again, enabling controlled, mass-responsive release and helping maintain the desired proportions in the final mix.
Figure 5 – Overview of kinematic motions applied throughout the system
Step 6: Post-Processing
EDEM allows engineers to analyse and extract various pieces of key information, these include but are not limited to:
- Mass flow rate of nuts per ejection.
- Total mass of nuts in the discharge hopper.
- Mixing uniformity/ratio in the discharge hopper.
- Prediction of wear hotspots and amount of wear on the system.
- Particle trajectories/pathlines to identify and eliminate potential dead zones.
- Velocity of nuts at any point in the system (see Figure 6).
Users interested in a detailed overview of EDEM’s post-processing features can refer to the following blog post:
EDEM Post-Processing: How to analyze your EDEM simulation results
Figure 6 – Velocity coloring of nut particles
Conclusion
This blog post showcased the use of EDEM to simulate and analyze a bulk material handling process for nuts, focusing on the mixing and dosing stages—from material setup through to kinematic control and post-processing. By leveraging EDEM’s capabilities, users can gain valuable insights into particle behavior and optimize their bulk material handling systems for improved efficiency and performance.
Further Readings
Below are links grouped into two focus areas:
Enhancing Simulation Setup and Performance:
- Factors affecting simulation runtime in EDEM – EDEM Simulation Run Time
- Estimating runtime of an EDEM simulation – Estimate Simulation Runtime
- Documentation on reduction of simulation time – Reduce Simulation Time
Other Related Readings that may be of Interest:
- Optimizing pharmaceutical manufacturing using EDEM – Pharmaceutical Manufacturing
- Analysis and optimization of bulk solids mixing systems with EDEM – Optimization of Bulk Solids Mixing
- Effect of material properties on blend uniformity – Blend Uniformity
References:
[1] Food Health Organisation. The State of Food and Agriculture. (2019). https://openknowledge.fao.org/server/api/core/bitstreams/11f9288f-dc78-4171-8d02-92235b8d7dc7/content