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Idaho National Laboratory relies on complex-shape models to analyze milled biomass flow

Biomass DEM modeling is an emerging area. Idaho National Laboratory (INL) conducted a literature study on this theme, demonstrating that DEM is a robust model to resolve the flow behavior of complex-shaped granular material.

Following this research, INL will next develop better modeling techniques using Rocky DEM realistic polyhedral/fiber models, then conduct pre-processing simulation studies that determine key parameters, aiming to help the industry design more efficient material-handling equipment for the milling/biorefinery process.

Our interest is understanding particle-flow behavior in biomass materials used to create bioenergy. We are one of the first laboratory teams to use the advanced shape models in Rocky DEM, exploring their suitability for modeling biomass particles and flow variability, within biomass handling equipment. We have already determined that Rocky DEM’s flexible fiber model is suitable for corn stover tissue, and we will use it to perform complicated simulation scenarios for flow and shear tests to identify particulate behavior.

Yidong Xia, PhD

Computational R&D Scientist, U.S. DOE Idaho National Laboratory

Researchers at Idaho National Laboratory have been tasked by the DOE’s Bioenergy Technology Office to expand fundamental understanding of biomass materials and work on identifying/developing DEM simulation models and processes to advance best practices. Biomass materials have irregular particle shapes that can cause unpredictive flow patterns, which can jam and clog biorefinery equipment.

The research team at INL conducted a literature review to determine existing advanced material models and their suitability to particle flow behavior within biorefinery equipment and processes. Based on this first step, the project will next develop better modeling techniques using Rocky DEM realistic polyhedral/fiber models, then conduct pre-processing simulation studies that determine key parameters.

Project results will be used to help industry players make decisions about optimizing biorefinery equipment/process design. The study has the potential to make equipment more efficient by eliminating downtime and, ultimately, reducing operational costs.


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