431392 Incorporating Intra-Particle Temperature Gradient in Dpm Modeling of Biomass Fast Pyrolysis

Tuesday, November 10, 2015: 3:57 PM
257B (Salt Palace Convention Center)
Qingang Xiong, Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, Sreekanth Pannala, Computer Science and Mathematics Division, Oak Ridge National Laboratories, Oak Ridge, TN and Stuart C. Daw, Feerc, Oak Ridge National Laboratory, Knoxville, TN

Incorporating intra-particle temperature gradient in DPM modeling of biomass fast pyrolysis

Qingang Xiong, Sreekanth Pannala, Stuart C. Daw

Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA

Emails: xiongq@ornl.gov (Q. Xiong), pannalas@gmail.com (S. Pannala), dawcs@ornl.gov (S. C. Daw)

Abstract Numerical simulation plays a vital role in the development of advanced technologies for biomass fast pyrolysis. Because of its relatively low thermal conductivity, biomass particles are always thermally thick and the effects of intra-particle temperature gradient on the overall reactor performance need to be considered. In this study, intra-particle temperature distribution was modeled and incorporated into the discrete particle simulation (DPM) for modeling biomass fast pyrolysis in fluidized-bed reactor. Each biomass particle was tracked individually and the inter-particle interactions were resolved directly via the soft-sphere collision model. A global multi-component multi-step kinetics was employed to model the biomass fast pyrolysis reactions. To consider the temperature gradient inside biomass, a mathematical distribution of intra-particle temperature which was developed from single-particle models was assigned to each biomass particle depending on its conversion history. With the assigned intra-particle temperature information, the pyrolysis reaction rates were obtained semi-analytically. The incorporation of the intra-particle temperature distribution into DPM was carried out in the open-source MFIX-DEM code. A small fluidized bed reactor consisting of several thousand biomass particles was simulated. The results were compared with those from the DPM simulation without consideration of the intra-particle temperature gradient. In the future work, sand particles will be included and parallel computing will be launched to simulate a laboratory-scale bubbling fluidized-bed reactor for experimental validation.

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