A CAPE-OPEN Computational Framework for Modeling Conventional Fast Pyrolysis and Oxidative Process Intensification of Lignocellulosic Biomass.
Year: 2026
Type: article
Abstract: This work presents a modular computational tool for simulating allothermal and oxidative fast pyrolysis of lignocellulosic biomass within a CAPE-OPEN-compatible process-simulation environment. Implemented through AmsterCHEM Python Unit Operations in COCO Simulator, the tool couples feedstock characterization, multicomponent devolatilization kinetics, effective heat transfer, gas-phase and solid-phase oxidation, and material and energy balances. Dedicated reporting blocks provide global and component-level product yields, oxygen consumption, external heat requirements, oxidation heat release, process-intensification metrics, and five circular bioeconomy indicators. The modular architecture enables direct integration with downstream separation, combustion, and heat-recovery units within a common flowsheet. The tool was evaluated using literature cases for red oak and corn stover, reproducing the principal trends in bio-oil production and throughput intensification under autothermal operation. Predicted intensification factors were 3.20 and 2.65, respectively. Application to a BTG-based circulating-sand process demonstrated its use in a configuration without an inert carrier gas. A database comprising 40 simulations for 20 lignocellulosic feedstocks illustrates its capacity for systematic feedstock comparison. The results distinguish total bio-oil recovery from water-free organic production and reveal trade-offs among biomass utilization, product valorization, waste generation, and external heating demand. The developed tool provides an extensible platform for connecting reaction-level calculations with flowsheet simulation and process-performance assessment, supporting preliminary design and comparative studies of conventional and oxidative biomass pyrolysis.
Institution: Universidad del Norte
Language: English
Subfield: Fuel Technology
Field: Energy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225619774