Gasification of mixed plastic-biomass pellets in an updraft fixed bed reactor: A simplified dynamic model

In the context of materials recycling, updraft gasifiers are promising small and middle-scale reactors to obtain building blocks and/or energy from waste plastic and biomasses. To this aim, these kinds of materials can also be mixed and reduced into pellets, while the needed heat enters the process with a heated carrier gas. In order to preliminarily design a gasifier to check its feasibility with an available feedstock, currently available models are inadequate. Thermodynamic ones are useless for the purposes of sizing, while too detailed rate-based models (e.g. based on fluid-dynamic modelling) are too substrate specific, need detailed input data and are extremely time consuming. A dynamic model of a fixed-bed reactor for biomass gasification is presented here. The gasifier is loaded continuously from the top with solid pellets and fed with counter-current air flow. The model considers: i) a one-step gasification kinetics, yielding a product spectrum which matches experimental data from the literature; ii) dynamic gas and solid energy balances and iii) steady-state energy balance for the furnace. The model has been applied to describe a tubular furnace (Ø 40 cm) which gasifies 500–1000 kg day −1 of mixed wastes using air heated up to 1200 °C: on the basis of the produced chemicals, the energy consumption was estimated as ca. 2 MJ per kg of solid feedstock. This simplified approach proved robust in describing the overall yields and start-up dynamics, showing higher reliability than equilibrium models in addressing the temperature profiles, at the cost of a simplified reaction kinetic and pellet description with respect to more complex simulation models. The model validation was done by comparison between the calculations results and available pilot-plant data. An overall good fit of the data can be concluded. The solid-gas heat transfer and the bed packing are the main computational criticalities to achieve a reliable process description. • Simplified model for preliminary analysis and economics of biomass gasifier. • The model proved stable and robust also in dynamic mode. • Examples are provided to estimate missing parameters for complex mixed substrates. • Gap is filled between barely thermodynamic models and more complex kinetic/CFD ones.

Authors

Institutions

Publication Details

Journal
Biomass and Bioenergy
Published
2024-09-23
DOI
https://doi.org/10.1016/j.biombioe.2024.107390
Citations
7
Primary Topic
Thermochemical Biomass Conversion Processes
Type
article
Field-Weighted Citation Impact
1.29

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gasification of mixed plastic-biomass pellets in an updraft fixed bed reactor: A simplified dynamic model

Ilenia Rossetti, Matteo Tommasi, Antonio Tripodi, Ilaria Prada
7 citations
Biomass and Bioenergy
Thermochemical Biomass Conversion Processes
1.29
article

Gasification of mixed plastic-biomass pellets in an updraft fixed bed reactor: A simplified dynamic model

Ilenia Rossetti, Matteo Tommasi, Antonio Tripodi, Ilaria Prada
article en
7 citations

Abstract

In the context of materials recycling, updraft gasifiers are promising small and middle-scale reactors to obtain building blocks and/or energy from waste plastic and biomasses. To this aim, these kinds of materials can also be mixed and reduced into pellets, while the needed heat enters the process with a heated carrier gas. In order to preliminarily design a gasifier to check its feasibility with an available feedstock, currently available models are inadequate. Thermodynamic ones are useless for the purposes of sizing, while too detailed rate-based models (e.g. based on fluid-dynamic modelling) are too substrate specific, need detailed input data and are extremely time consuming. A dynamic model of a fixed-bed reactor for biomass gasification is presented here. The gasifier is loaded continuously from the top with solid pellets and fed with counter-current air flow. The model considers: i) a one-step gasification kinetics, yielding a product spectrum which matches experimental data from the literature; ii) dynamic gas and solid energy balances and iii) steady-state energy balance for the furnace. The model has been applied to describe a tubular furnace (Ø 40 cm) which gasifies 500–1000 kg day −1 of mixed wastes using air heated up to 1200 °C: on the basis of the produced chemicals, the energy consumption was estimated as ca. 2 MJ per kg of solid feedstock. This simplified approach proved robust in describing the overall yields and start-up dynamics, showing higher reliability than equilibrium models in addressing the temperature profiles, at the cost of a simplified reaction kinetic and pellet description with respect to more complex simulation models. The model validation was done by comparison between the calculations results and available pilot-plant data. An overall good fit of the data can be concluded. The solid-gas heat transfer and the bed packing are the main computational criticalities to achieve a reliable process description. • Simplified model for preliminary analysis and economics of biomass gasifier. • The model proved stable and robust also in dynamic mode. • Examples are provided to estimate missing parameters for complex mixed substrates. • Gap is filled between barely thermodynamic models and more complex kinetic/CFD ones.

Biomass and BioenergyVol. 190
University of Milan (IT)
Ministero dell’Istruzione, dell’Università e della Ricerca, Ministero dell'Università e della Ricerca
Openalex Percentile: Top 22%
Thermochemical Biomass Conversion Processes
1.29
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.