Optimization of Hydrogen Production from Pyrolysis of Biomass Waste

Milo Parra-Alvarez, Hariswaran Sitaraman

Research output: NRELPoster

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 languageAmerican English
PublisherNational Renewable Energy Laboratory (NREL)
DOIs
StatePublished - 2023

NREL Publication Number

  • NREL/PO-2C00-86731

Keywords

  • biomass pyrolysis
  • computational fluid dynamics
  • machine learning
  • optimization
  • syngas production

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