Supervisor:
Chungen Yin

Co-Supervisor:
Matthias Mandø

Assessment Committee:
Saqib Toor (Chair)
Peter Glarborg, DTU, Dept. Chemical and Biochemical Engineering
Xue-Song Bai, Lund University, Dept. Energy Sciences

Moderator:
Saqib Toor

Abstract:

Large-scale biomass piles in open environments are prone to self-heating, which can lead to spontaneous combustion under certain conditions. This presents significant safety risks for storing and using biomass fuels. Developing a prediction tool for self-heating in stored biomass is an economical way to reduce these risks. This project introduces a robust and reliable modeling tool to forecast self-heating in biomass storage piles. A computational fluid dynamics (CFD) model has been created using Ansys Fluent, integrating the three main mechanisms of biomass self-heating: chemical, physical, and microbial activities. The project scheme is divided into three parts. The first part involves developing a simple model to simulate and verify the self-heating and spontaneous combustion process of coal piles, focusing only on low-temperature oxidation and physical processes without microbial activity. The second part successfully models and verifies the microbial-driven self-heating process of biomass piles using a well-established mathematical approach from existing literature. These two parts include local parameter studies and initial exploration of external factors affecting self-heating activity. The third part provides an in-depth analysis and validation of how environmental relative humidity influences biomass self-heating. It emphasizes refining the mathematical model of water evaporation and condensation based on laboratory tests of biomass moisture migration from literature, aiming to match real-world evaporation and condensation rates in open-air conditions. This part addresses the current lack of literature on simulations of water migration in large-scale biomass piles. Building on these simulations, a comprehensive parameter study was conducted to better understand the self-heating process, offering practical guidance for preventing fires in biomass piles. Overall, this project demonstrates specific strategies for safe biomass storage in open-air environments and offers a practical, reproducible simulation method.