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Controlled Synthesis and Fluorescence Tracking of Highly Uniform PolyN-isopropylacrylamide Microgels

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Development of a Non-Spherical Polymeric Particles Calibration Procedure for Numerical Simulations Based on the

Joshua García-Montagut¹, Rubén Paz¹, Mario Monzón¹

¹Mechanical Engineering Department, Edificio de Ingenierías, Campus de Tafira Baja, Universidad de Las Palmas de Gran Canaria, 35017 Las Palmas, Spain.

|October 28, 2025

Summary

This study presents an efficient calibration method for Low-Density Polyethylene particles using numerical simulations and genetic algorithms. The optimized model accurately predicts material properties and particle interactions, reducing computational costs.

Keywords:

discrete element method genetic algorithms material calibration polymeric powder calibration

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Assembly and Characterization of Polyelectrolyte Complex Micelles

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Assembly and Characterization of Polyelectrolyte Complex Micelles

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Published on: March 2, 2020

Area of Science:

Materials Science
Chemical Engineering
Computational Mechanics

Background:

The plastic industry requires optimized manufacturing processes for new materials.
Numerical methods, particularly the Discrete Elements Method (DEM), are crucial for simulating particulate materials.
Calibration of DEM parameters is essential but computationally expensive.

Purpose of the Study:

To develop and present a general, cost-effective calibration method for Low-Density Polyethylene (LDPE) particles.
To accurately determine material properties and particle interaction parameters for DEM simulations.
To integrate speed-up procedures for efficient calibration.

Main Methods:

Utilized the Discrete Elements Method (DEM) for particulate material simulation.
Integrated speed-up procedures to reduce computational cost.
Employed genetic algorithms for parameter calibration based on experimental data.
Conducted four experimental tests and corresponding simulations.

Main Results:

Calibrated solid density, Poisson's ratio, friction factors (static, rolling, restitution), and contact model variables (damping, stiffness, energy density).
Achieved a Mean Absolute Percentage Error (MAPE) below 2% between simulated and experimental results.
Successfully calibrated input parameters after 85 iterations.

Conclusions:

The developed calibration method is effective for LDPE particles, significantly reducing computational and experimental costs.
Accurate calibration of DEM parameters is vital for reliable simulation of plastic manufacturing processes.
The study demonstrates the potential of integrating numerical methods with optimization algorithms for material process optimization.