Case Study: Discrete Element Method (DEM) Simulation of Hopper for plastic particles

Project Overview

MechSourcing conducted a Discrete Element Method (DEM) Simulation to evaluate the particle velocity and distribution at various angles and find an optimum angle to achieve desired particle flow for further processing.

Objectives of the Study

The primary objective of this case study is to demonstrate the application of Discrete Element Method (DEM) for analysing the flow behaviour, interaction, and segregation of granular materials under realistic operating conditions.

Specifically, the study aims to:

• Predict particle trajectories, velocities, and contact forces

• Evaluate segregation tendencies

• Identify zones of stagnation, arching, or excessive wear

• Support equipment design, scale-up, and optimisation

• Reduce trial-and-error experimentation and physical prototyping

Geometry and Computational Domain

The reference system modelled in this case study represents a generic industrial granular handling unit, such as:

• Hopper System

Key geometric features:

• Rigid walls

• Defined in CAD and imported into DEM simulation software

• Motion can be applied via prescribed angular or linear velocities but for the current simulation gravity based particle flow is considered.

Particle Properties

Each particle is assigned physical and mechanical properties:

Contact Models

• Hertz–Mindlin (Nonlinear elastic contact)

• Linear spring-dashpot model

• Optional cohesive force models (van der Waals / capillary)

Governing Equations:

Translational Motion (Newton’s Second Law)

Rotational Motion

Normal Contact Force (Hertz Model)

Tangential Contact Force (Mindlin–Deresiewicz)

Simulation Methodology

Step 1: Geometry Import

• CAD geometry imported into DEM software

• Mesh-free DEM boundaries defined

Step 2: Particle Generation

• Particle cloud generated with defined size distribution

• Initial packing via gravity settling

Step 3: Contact Model Assignment

• Particle–particle and particle–wall models defined

• Friction, restitution, and cohesion enabled as required

Step 4: Boundary Conditions

• Gravity applied

• Rotational speed or translational motion imposed

• Time step selected based on Rayleigh criterion

Step 5: Solver Execution

• Explicit time integration

• Monitoring of kinetic energy and contact stability

Post-Processing and Key Results

Key outputs analyzed:

• Particle velocity and acceleration fields

• Contact force networks (force chains)

• Residence time distribution

• Mixing index (Lacey or relative variance)

• Wear-prone wall regions

• Mass flow rate and discharge uniformity

Engineering Insights Gained

• Identification of dead zones and segregation layers

• Optimization of rotational speed or feed rate

• Prediction of abrasive wear and liner requirements

• Validation of scale-up from lab to industrial size

• Reduced physical testing costs

Industrial Applications

Food Processing Industry

• Powder mixing and blending

• Grain handling and milling

• Sugar, flour, spice processing

• Avoiding segregation and product inconsistency

Plastic and Polymer Processing

• Plastic pellet conveying

• Hopper and extruder feed optimization

• Minimizing pellet breakage and dust formation

Chemical & Pharmaceutical

• Tablet coating drums

• Catalyst pellet handling

• Uniform mixing of active ingredients

Mining & Bulk Solids

• Ore flow in chutes and crushers

• Stockpile reclaim systems

• Wear prediction in transfer points

Benefits to Industry

• Design validation before manufacturing

• Reduced downtime due to blockages

• Improved product quality

• Energy-efficient equipment operation

• Shorter development cycles