476543 Steam-Blown Biomass Gasification in Fluidized Beds:Gas-Flow Distribution for Advanced Reactor Network Models

Tuesday, November 15, 2016
Grand Ballroom B (Hilton San Francisco Union Square)
Akhilesh Bakshi1, Christos Altantzis1, Addison K. Stark2, Richard B. Bates1 and Ahmed F. Ghoniem1, (1)Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, (2)Advanced Research Projects Agency - Energy, US Department of Energy, Washington, DC

Bubbling fluidized beds are used extensively in the energy and chemical industries because of their excellent heat and mass transfer characteristics. Computational Fluid Dynamics (CFD) is an extermely useful tool for reactor design, analysis and optimal operation. Application to large scale gasifiers continues to be challenging because of limitations on computational resources. Given that the hydrodynamics can largely be characterized by bubbles rising through the bed, a more feasible approach for investigating large-scale reactors is to quantify bubble dynamics and specifically, reactive gas distribution in different phases- visible bubble flow, bubblethrough flow and dense-phase flow.

In this study, reactive 3D CFD simulations are conducted for steam-blown biomass gasification in bubbling fluidized beds of varying diameters and pressures. The hydrodynamics are coupled with a global devolatalization mechanism for biomass conversion [1], while the steady state char concentration is predicted using a detailed char particle gasification and combustion model [2]. The physical model and numerical tool were developed and validated in previous studies [3], while 3D Bubble statistics are computed using MS3DATA (Multiphase Statistics using 3D Detection and Tracking Algorithm) [4]. Simulation data is analyzed and the distribution of both the oxidant and devolatalized gases, and their residence times, are computed. Accurate description of the gas-flow is critical for large-scale reactor design since quantifying the gas distribution can determine the fuel rich zones (in the emulsion) as well as the oxidant bypass through the bubbles (through-flow) leading to inefficient performance, and the formation of recalcitrant tar compounds. Additionally, insights from this study will be valuable for reactor network modeling of fuel conversion systems [1].

REFERENCES

[1] A.K. Stark, C. Altantzis, R.B. Bates and A.F. Ghoniem, Towards an advanced reactor network modeling framework for fluidized bed biomass gasification: Incorporating information from detailed CFD simulations. Chemical Engineering Journal. 303: 409-424, 2016.

[2] R. Bates, C. Altantzis, and A.F. Ghoniem, Modeling of Biomass Char Gasification, Combustion, and Attrition Kinetics in Fluidized Beds. Energy Fuels 30(1):360–376, 2016

[3] A. Bakshi, C. Altantzis, R.B. Bates and A.F. Ghoniem, Study of the effect of reactor scale on fluidization hydrodynamics using fine-grid CFD simulations based on the two-fluid model, Powder Technology, 299: 185-198, 2016

[4] A. Bakshi, C. Altantzis, R.B. Bates and A.F. Ghoniem, Multiphase-flow Statistics using 3D Detection and Tracking Algorithm (MS3DATA): Methodology and application to large-scale fluidized beds. Chemical Engineering Journal, 293: 355-364, 2016


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