Computational Science and Physics-based Modeling for Biomass Processing

Idaho National Laboratory

Description

This capability encompasses INL’s advanced multi-scale computational models and predictive simulation software tools for the design and optimization of biomass processing operations, which include but are not limited to sorting, comminution, screening, and material feeding and transport. The computational models that have been developed for biomass flow and/or fragmentation include but are not limited to discrete element method (DEM), dissipative particle dynamics (DPD), finite element method (FEM), and smoothed particle hydrodynamics (SPH). Most of the simulation software tools can be run on INL’s high-performance computer systems.

Capability Bounds

From micrometer scale to pilot scale.

Unique Aspects

All the computational models developed are calibrated and validated against the physical experiments at INL.

Availability

Currently available through the development of collaborative work scopes that utilize a variety of contractual mechanisms to meet the needs of the partners and funding agencies.

Benefit

Predictive simulations for biomass processing are essential for identifying emergent issues in preprocessing and material handling, verifying design efficiency, and de-risking the scale-up operations.

Capability Expert(s)

Yidong Xia, Wencheng Jin, Ahmed Hamed

References

Xia, Y., Chen, F., Klinger, J. L., Kane, J. J., Bhattacharjee, T., Seifert, R., … & Chen, Q. (2021). Assessment of a tomography-informed polyhedral discrete element modelling approach for complex-shaped granular woody biomass in stress consolidation. Biosystems Engineering, 205, 187-211.
Chen, F., Xia, Y., Klinger, J., & Chen, Q. (2023). Hopper discharge flow dynamics of milled pine and prediction of process upsets using the discrete element method. Powder Technology, 415, 118165.
Hamed, A., Xia, Y., Saha, N., Klinger, J., Lanning, D. N., & Dooley, J. H. (2023). Particle size and shape effect of Crumbler® rotary shear-milled granular woody biomass on the performance of Acrison® screw feeder: A computational and experimental investigation. Powder Technology, 118707.
Lu, Y., Jin, W., Klinger, J., & Dai, S. (2021). Flow and arching of biomass particles in wedge-shaped hoppers. ACS Sustainable Chemistry & Engineering, 9(45), 15303-15314.
Lu, Y., Jin, W., Saha, N., Klinger, J. L., Xia, Y., & Dai, S. (2022). Wedge-shaped hopper design for milled woody biomass flow. ACS Sustainable Chemistry & Engineering, 10(50), 16803-16813.
Jin, W., Lu, Y., Chen, F., Hamed, A., Saha, N., Klinger, J., … & Xia, Y. (2022). On the fidelity of computational models for the flow of milled loblolly pine: A benchmark study on continuum-mechanics models and discrete-particle models. Frontiers in Energy Research, 10, 855848.
Zhao, Y., Jin, W., Klinger, J., Dayton, D. C., & Dai, S. (2023). SPH modeling of biomass granular flow: Theoretical implementation and experimental validation. Powder Technology, 426, 118625.