CFD modeling of biomass combustion and gasification in fluidized bed reactors
(2023)- Abstract
- Biomass is an environmentally friendly renewable energy source and carbon-neutral fuel alternative. Direct combustion/gasification of biomass in the dense particle-fluid system is an important pathway to biomass energy utilization. To efficiently utilize biomass for energy conversion, a full understanding of biomass thermal conversion in lab/industrial-scale equipment is essential. This thesis aims to gain a deeper understanding of the physical and chemical mechanisms of biomass combustion/gasification in fluidized bed (FB) furnaces using computational fluid dynamics (CFD) simulations. A three-dimensional reactive CFD model based on the Eulerian-Lagrangian method is developed to investigate the hydrodynamics, heat transfer, and... (More)
- Biomass is an environmentally friendly renewable energy source and carbon-neutral fuel alternative. Direct combustion/gasification of biomass in the dense particle-fluid system is an important pathway to biomass energy utilization. To efficiently utilize biomass for energy conversion, a full understanding of biomass thermal conversion in lab/industrial-scale equipment is essential. This thesis aims to gain a deeper understanding of the physical and chemical mechanisms of biomass combustion/gasification in fluidized bed (FB) furnaces using computational fluid dynamics (CFD) simulations. A three-dimensional reactive CFD model based on the Eulerian-Lagrangian method is developed to investigate the hydrodynamics, heat transfer, and gasification/combustion characteristics of biomass in multiple-scale FB furnaces. The CFD model considered here is based on the multi-phase particle-in-cell (MP-PIC) collision model and the coarse grain method (CGM). CGM is computationally efficient; however, it can cause numerical instability if the clustered parcels pass through small computational cells, resulting in the over-loading of solid particles in the cells. To address this issue, a distribution kernel method (DKM) is proposed. This method is to spread the solid volume and source terms of the parcel to the surrounding domain. The numerical stiffness problem caused by the CGM clustering can be remedied using DKM. Validation of the model is performed using experimental data from various lab-scale reactors. The validated model is employed to investigate further the heat transfer and biomass combustion/gasification process. Biomass pyrolysis produces a large variety of species in the products, which poses great challenges to the modeling of biomass gasification. A conventional single-step pyrolysis model is widely employed in FB simulations due to its low computational cost. However, the prediction of pyrolysis products of this model under varying operating temperatures needs to be improved. To address this issue, an empirical pyrolysis model based on element conservation law is developed. The empirical parameters are based on a number of experiments from the literature. The simulation results agree well with the experimental data under different
operating conditions. The pyrolysis model improves the sensitivity of gasification product yields to operating temperature. Furthermore, the mixture characteristics of the biomass and sand particles and the effect of the operating conditions on the yields of gasification products are analyzed. The validated CFD model is employed to investigate the fluidization, combustion, and emission processes in industrial-scale FB furnaces. A major challenge in the CFD simulation of industrial-scale FB furnaces is the enormous computational time and memory required to track quadrillions of particles in the systems. The CFD model coupling MP-PIC and CGM greatly reduces the computational cost, and the DKM overcomes the unavoidable particle overloading issue due to the refined mesh in complex geometry. The CFD predictions agree well with onsite temperature experiments in the furnace. The CFD results are used to understand the granular flow and the impact of operating conditions on the physical and chemical processes in biomass FB-fired furnaces. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/f3e29ee0-c669-406a-bf84-94e609f955ae
- author
- Yang, Miao LU
- supervisor
-
- Xue-Song Bai LU
- Hesameddin Fatehi LU
- Leilei Xu LU
- opponent
-
- Prof. Halter, Fabien, University of Orleans, France.
- organization
- publishing date
- 2023-03
- type
- Thesis
- publication status
- published
- subject
- keywords
- Biomass combustion and gasification, CFD simulation, Fluidized bed furnace, Distribution kernel method, Empirical pyrolysis model
- pages
- 165 pages
- publisher
- Department of Energy Sciences, Lund University
- defense location
- Lecture hall KC:A, Kemicentrum, Naturvetarvägen 14, Faculty of Engineering LTH, Lund University, Lund
- defense date
- 2023-03-31 10:00:00
- ISBN
- 978-91-8039-512-0
- 978-91-8039-513-7
- language
- English
- LU publication?
- yes
- id
- f3e29ee0-c669-406a-bf84-94e609f955ae
- date added to LUP
- 2023-03-06 08:38:33
- date last changed
- 2023-03-08 08:22:39
@phdthesis{f3e29ee0-c669-406a-bf84-94e609f955ae,
abstract = {{Biomass is an environmentally friendly renewable energy source and carbon-neutral fuel alternative. Direct combustion/gasification of biomass in the dense particle-fluid system is an important pathway to biomass energy utilization. To efficiently utilize biomass for energy conversion, a full understanding of biomass thermal conversion in lab/industrial-scale equipment is essential. This thesis aims to gain a deeper understanding of the physical and chemical mechanisms of biomass combustion/gasification in fluidized bed (FB) furnaces using computational fluid dynamics (CFD) simulations. A three-dimensional reactive CFD model based on the Eulerian-Lagrangian method is developed to investigate the hydrodynamics, heat transfer, and gasification/combustion characteristics of biomass in multiple-scale FB furnaces. The CFD model considered here is based on the multi-phase particle-in-cell (MP-PIC) collision model and the coarse grain method (CGM). CGM is computationally efficient; however, it can cause numerical instability if the clustered parcels pass through small computational cells, resulting in the over-loading of solid particles in the cells. To address this issue, a distribution kernel method (DKM) is proposed. This method is to spread the solid volume and source terms of the parcel to the surrounding domain. The numerical stiffness problem caused by the CGM clustering can be remedied using DKM. Validation of the model is performed using experimental data from various lab-scale reactors. The validated model is employed to investigate further the heat transfer and biomass combustion/gasification process. Biomass pyrolysis produces a large variety of species in the products, which poses great challenges to the modeling of biomass gasification. A conventional single-step pyrolysis model is widely employed in FB simulations due to its low computational cost. However, the prediction of pyrolysis products of this model under varying operating temperatures needs to be improved. To address this issue, an empirical pyrolysis model based on element conservation law is developed. The empirical parameters are based on a number of experiments from the literature. The simulation results agree well with the experimental data under different<br/>operating conditions. The pyrolysis model improves the sensitivity of gasification product yields to operating temperature. Furthermore, the mixture characteristics of the biomass and sand particles and the effect of the operating conditions on the yields of gasification products are analyzed. The validated CFD model is employed to investigate the fluidization, combustion, and emission processes in industrial-scale FB furnaces. A major challenge in the CFD simulation of industrial-scale FB furnaces is the enormous computational time and memory required to track quadrillions of particles in the systems. The CFD model coupling MP-PIC and CGM greatly reduces the computational cost, and the DKM overcomes the unavoidable particle overloading issue due to the refined mesh in complex geometry. The CFD predictions agree well with onsite temperature experiments in the furnace. The CFD results are used to understand the granular flow and the impact of operating conditions on the physical and chemical processes in biomass FB-fired furnaces.}},
author = {{Yang, Miao}},
isbn = {{978-91-8039-512-0}},
keywords = {{Biomass combustion and gasification; CFD simulation; Fluidized bed furnace; Distribution kernel method; Empirical pyrolysis model}},
language = {{eng}},
publisher = {{Department of Energy Sciences, Lund University}},
school = {{Lund University}},
title = {{CFD modeling of biomass combustion and gasification in fluidized bed reactors}},
url = {{https://lup.lub.lu.se/search/files/139660453/MiaoYang_PhD_thesis.pdf}},
year = {{2023}},
}