ERI: Morphology-Governed Transport Phenomena in Biomass Gasification: A Pore-Resolved CFD Study

Biomass gasification is a promising way to produce clean fuels from plants. Engineers rely on simulation tools to design gasification processes. These tools assume that solid particles of biomass have simple shapes. Real biomass particles are uneven and full of tiny holes. Their true shapes affect how fast heat and reacting gases reach their surfaces, which, in turn, affects process efficiency. This project will identify the shape features that matter most in gasification and analyze why, so that the tools used to design and operate biomass conversion systems can be improved. The results will support more efficient and reliable reactor designs. The project will train undergraduate and graduate students in advanced imaging, simulation, and data reading. Project results will be included in coursework and broadly shared through publications and presentations. The project will reconstruct three-dimensional biomass char particle geometries using high-resolution micro computed tomography imaging, and then quantify measurable shape and pore descriptors (for example, roughness, elongation, and internal void fraction) for a representative particle set. It will then perform pore-resolved computational fluid dynamics simulations for (i) individual particles and (ii) small groups of particles to resolve how geometry and relative arrangement control local flow patterns, heat exchange, and inter-particle effects such as shielding and wake interference. It will benchmark these results against idealized shapes to define the limits of simplified assumptions. To build confidence in the simulation framework, selected particle shapes will be reproduced with high-resolution three-dimensional printing and tested in a small wind tunnel to compare measured drag and wake behavior with simulation predictions under non-reacting conditions. The resulting image-to-simulation dataset and physics-based relationships linking shape to transport will provide benchmark resources for improved reduced-order modeling in multiphase systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2536221 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Dongyu Liang | Institution: Lawrence Technological University, SOUTHFIELD, MI | Award Amount: $196,850 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2536221 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2536221.html