(328c) X-Ray Computed Tomography-Based Micro-Porosity Analysis and Discrete Element Modeling: Algorithm Development and Application for Woody Biomass
AIChE Annual Meeting
2021 Annual Meeting
Particle Technology Forum
Fluidization: Modeling Approaches and Applications in Fluidization Fundamentals
Tuesday, November 16, 2021 - 2:15pm to 2:30pm
The properties of lignocellulosic biomass, such as bulk physical, thermal, and mechanical properties, as well as the mobility of enzymes or catalysts, are largely affected by porosity, pore structures, and pore size distribution. While X-ray computed tomography (CT) has been introduced to effectively produce 3D volumetric images of material microstructure, a quantitative porosity analysis from the 3D images has never been done. This work presents a first-of-its-kind X-ray CT-based quantitative micro-porosity analysis method and applies the developed toolkit to characterize the microstructure and internal porosity distribution of biomass particles. Building on the microstructure data, a high-fidelity micromechanical discrete element model is developed to simulate the mechanical behavior of the particle. In the application for woody biomass, sample loblolly pine chips are scanned by a nano-resolution X-ray CT system and digitally reconstructed after a sequence of image processing operations. A comprehensive porosity analysis is then performed to quantify the envelope porosity, the spatial distribution of local porosity, and the directional porosity. Then, micromechanical simulations are performed using the developed discrete element model to predict the mechanical and fracturing behavior of loblolly pine particles. Solutions to various challenges in image processing, porosity calculation, large data handling, and microstructure-based mechanical model development are provided.