Mixed modeling approach for mechanical sorting processes based on physical properties of municipal solid waste

Area of Science:

• Environmental Engineering
• Waste Management Science
• Process Modeling

Background:

• Material recovery facilities (MRFs) are crucial for efficient recycling but face challenges due to poor understanding of sorting equipment mechanisms.
• Current methods using transfer coefficients for predicting mechanical sorting efficiency lack flexibility and accuracy when operating conditions change.
• Improving the modeling of unit operations within MRFs is essential for mitigating these challenges and enhancing waste management systems.

Purpose of the Study:

• To develop a novel predictive tool integrating mechanistic models and transfer coefficients for enhanced MRF sorting efficiency prediction.
• To address the limitations of traditional transfer coefficient methods by incorporating physically-based models for key sorting operations.
• To provide a flexible and accurate tool for predicting mass flows and optimizing operations in material recovery facilities.

Main Methods:

• Development of mechanistic models for influential unit operations within MRFs, focusing on physical phenomena.
• Integration of these mechanistic models with transfer coefficients for less influential operations to maintain simplicity and flexibility.
• Validation of the predictive tool using a case study of a real-world material recovery facility to assess mass flow prediction accuracy.

Main Results:

• The integrated predictive tool demonstrated good accuracy in predicting mass flows for a material recovery facility.
• The study successfully validated the enhanced modeling approach against real-world operational data.
• A novel modeling technique for ballistic separators, utilizing a shape factor of waste items, was proposed and presented.

Conclusions:

• The developed predictive tool offers a significant improvement over traditional methods for predicting MRF sorting efficiency.
• Combining mechanistic models with transfer coefficients provides a flexible, accurate, and practical solution for MRF operational modeling.
• The proposed approach enhances the understanding and optimization of waste sorting processes, contributing to more effective recycling and waste management.