Abstract
We developed an CFD aided ML-based tool for rapid assessment and optimization of different compositions of biomass in a fluidized bed reactor. First, we use CFD to simulate fluidized bed reactors with known inlet biomass mixtures and obtain corresponding syngas yields. A lumped kinetic mechanisms represents the conversion of cellulose, hemicellulose, and lignin, as well as subsequent cracking of tars into non-condensable gases (H2, CO, CO2, CH4). We use Bayesian analysis/optimization to obtain the ideal operational and mass flow conditions for hydrogen production.
Original language | American English |
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Publisher | National Renewable Energy Laboratory (NREL) |
DOIs | |
State | Published - 2023 |
NREL Publication Number
- NREL/PO-2C00-86731
Keywords
- biomass pyrolysis
- computational fluid dynamics
- machine learning
- optimization
- syngas production