Predictive Model for Particle Residence Time Distributions in Riser Reactors. Part 1: Model Development and Validation

Foust, Thomas D.; Ziegler, Jack L.; Pannala, Sreekanth; Ciesielski, Peter; Nimlos, Mark R.; Robichaud, David J.

doi:10.1021/acssuschemeng.6b02384

Title: Predictive Model for Particle Residence Time Distributions in Riser Reactors. Part 1: Model Development and Validation

Journal Article · Tue Feb 28 00:00:00 EST 2017 · ACS Sustainable Chemistry & Engineering

DOI:https://doi.org/10.1021/acssuschemeng.6b02384· OSTI ID:1351161

^[1]; Ziegler, Jack L. ^[1]; Pannala, Sreekanth ^[2];

^[1]; Nimlos, Mark R. ^[1]; Robichaud, David J. ^[1]

National Renewable Energy Lab. (NREL), Golden, CO (United States). National Bioenergy Center
SABIC Americas, Sugar Land, TX (United States). Corporate Research and Development

Here in this computational study, we model the mixing of biomass pyrolysis vapor with solid catalyst in circulating riser reactors with a focus on the determination of solid catalyst residence time distributions (RTDs). A comprehensive set of 2D and 3D simulations were conducted for a pilot-scale riser using the Eulerian-Eulerian two-fluid modeling framework with and without sub-grid-scale models for the gas-solids interaction. A validation test case was also simulated and compared to experiments, showing agreement in the pressure gradient and RTD mean and spread. For simulation cases, it was found that for accurate RTD prediction, the Johnson and Jackson partial slip solids boundary condition was required for all models and a sub-grid model is useful so that ultra high resolutions grids that are very computationally intensive are not required. Finally, we discovered a 2/3 scaling relation for the RTD mean and spread when comparing resolved 2D simulations to validated unresolved 3D sub-grid-scale model simulations.

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Research Organization:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Sustainable Transportation Office. Bioenergy Technologies Office

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1351161

Report Number(s):: NREL/JA-5100-67640

Journal Information:: ACS Sustainable Chemistry & Engineering, Vol. 5, Issue 4; ISSN 2168-0485

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 6 works

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Title: Predictive Model for Particle Residence Time Distributions in Riser Reactors. Part 1: Model Development and Validation

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