Multiphase CFD-DEM model for gasification and melting applications
Due to the increase in urban population and consumption, there is an increasing need for evolving waste management technologies to deal with the excessive solid waste produced. Gasification is one proposed technology that achieves greater waste volume reduction compared to other thermal processes. H...
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2023
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Engineering::Environmental engineering::Waste management Soon, Genevieve Qian Yi Multiphase CFD-DEM model for gasification and melting applications |
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Due to the increase in urban population and consumption, there is an increasing need for evolving waste management technologies to deal with the excessive solid waste produced. Gasification is one proposed technology that achieves greater waste volume reduction compared to other thermal processes. Hence, the optimization, stability and reliability of commercial gasifiers is important, especially when diverse feedstock and waste streams are present. Other than conducting pilot trials and experiments, numerical simulations have been adopted as useful tools for modelling the chemical and physical processes to modify operating conditions and predict the resultant effects.
The study is targeted to develop a numerical modelling approach to model the melting and phase-change process in multiphase flows for gasification and other applications. A melting model that could be used for isothermal and non-isothermal melting in packed beds was established with the combination of computational fluid dynamics and the discrete element method. At present, the state-of-the-art numerical models are not found to be suitable for melting for independent, three-phase flows within packed beds, especially for complex processes such as gasification with chemical reactions. Throughout the study, some methods of reducing computational costs in particle-fluid simulations were also investigated and adapted to the model. The limitations of the approach and comparison with other approaches were also reviewed.
Application examples were used to demonstrate the capability of the melting modelling approach developed in this study. The isothermal melting of a single ice particle and a packed bed of ice flowing under warm water convection were examined as a first step. The simulations were validated against experimental results and found to be satisfactory. Insights were also obtained with regards to the modification of the mesh-particle size ratio and determination of the values of the spring constant and restitution coefficient in the linear spring-dashpot particle collision model. Subsequently, the non-isothermal melting of a wax layer in an inert packed bed under air convection was simulated. In the utilization of the approach for three-phase flows, the governing principle of particle energy balance was established together with a novel concept of particle “enthalpy” being introduced for non-isothermal melting. Due to the nature of the three-phase flow, this approach allowed for the tracking of the liquid phase and permeation through the packed bed, as well as the viewing of the formation of gas channels. The approach was also deemed to be compatible with coarse-graining, and useful in certain applications over other multiphase modelling approaches.
Lastly, attempts were made for further extension of the modelling approach for application in a prototype gasifier, including the full-scale gasification chemical and physical processes (vaporization, devolatilization, combustion and melting). However, various challenges were encountered during this process, particularly with numerical instabilities and uncertainties stemming from the approach being coupled with the commercial software. Nevertheless, the lifetime and process of a sample MSW particle was able to be predicted, and a comparison was carried to determine the effectiveness and need for slag recycling in the prototype gasifier.
In conclusion, a novel modelling approach was developed in this study for melting which can be used to improve and predict conditions in reactors. By tracking each particle individually, the model is well-equipped to simulate the packed bed in a discrete manner, allowing for unique particle temperatures, composition, and melting rates. The model has the potential to improve gasification performance as it is able to assess the performance of changing operating parameters at the design and operational stages. The use of various methods to reduce the high computational costs of modelling phase-change in large-scale facilities was also investigated, and the simultaneous melting and tracking of liquid phase within the solid packed bed was able to be predicted. |
author2 |
Law Wing-Keung, Adrian |
author_facet |
Law Wing-Keung, Adrian Soon, Genevieve Qian Yi |
format |
Thesis-Doctor of Philosophy |
author |
Soon, Genevieve Qian Yi |
author_sort |
Soon, Genevieve Qian Yi |
title |
Multiphase CFD-DEM model for gasification and melting applications |
title_short |
Multiphase CFD-DEM model for gasification and melting applications |
title_full |
Multiphase CFD-DEM model for gasification and melting applications |
title_fullStr |
Multiphase CFD-DEM model for gasification and melting applications |
title_full_unstemmed |
Multiphase CFD-DEM model for gasification and melting applications |
title_sort |
multiphase cfd-dem model for gasification and melting applications |
publisher |
Nanyang Technological University |
publishDate |
2023 |
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https://hdl.handle.net/10356/166302 |
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sg-ntu-dr.10356-1663022023-05-03T00:05:53Z Multiphase CFD-DEM model for gasification and melting applications Soon, Genevieve Qian Yi Law Wing-Keung, Adrian Interdisciplinary Graduate School (IGS) Nanyang Environment and Water Research Institute CWKLAW@ntu.edu.sg Engineering::Environmental engineering::Waste management Due to the increase in urban population and consumption, there is an increasing need for evolving waste management technologies to deal with the excessive solid waste produced. Gasification is one proposed technology that achieves greater waste volume reduction compared to other thermal processes. Hence, the optimization, stability and reliability of commercial gasifiers is important, especially when diverse feedstock and waste streams are present. Other than conducting pilot trials and experiments, numerical simulations have been adopted as useful tools for modelling the chemical and physical processes to modify operating conditions and predict the resultant effects. The study is targeted to develop a numerical modelling approach to model the melting and phase-change process in multiphase flows for gasification and other applications. A melting model that could be used for isothermal and non-isothermal melting in packed beds was established with the combination of computational fluid dynamics and the discrete element method. At present, the state-of-the-art numerical models are not found to be suitable for melting for independent, three-phase flows within packed beds, especially for complex processes such as gasification with chemical reactions. Throughout the study, some methods of reducing computational costs in particle-fluid simulations were also investigated and adapted to the model. The limitations of the approach and comparison with other approaches were also reviewed. Application examples were used to demonstrate the capability of the melting modelling approach developed in this study. The isothermal melting of a single ice particle and a packed bed of ice flowing under warm water convection were examined as a first step. The simulations were validated against experimental results and found to be satisfactory. Insights were also obtained with regards to the modification of the mesh-particle size ratio and determination of the values of the spring constant and restitution coefficient in the linear spring-dashpot particle collision model. Subsequently, the non-isothermal melting of a wax layer in an inert packed bed under air convection was simulated. In the utilization of the approach for three-phase flows, the governing principle of particle energy balance was established together with a novel concept of particle “enthalpy” being introduced for non-isothermal melting. Due to the nature of the three-phase flow, this approach allowed for the tracking of the liquid phase and permeation through the packed bed, as well as the viewing of the formation of gas channels. The approach was also deemed to be compatible with coarse-graining, and useful in certain applications over other multiphase modelling approaches. Lastly, attempts were made for further extension of the modelling approach for application in a prototype gasifier, including the full-scale gasification chemical and physical processes (vaporization, devolatilization, combustion and melting). However, various challenges were encountered during this process, particularly with numerical instabilities and uncertainties stemming from the approach being coupled with the commercial software. Nevertheless, the lifetime and process of a sample MSW particle was able to be predicted, and a comparison was carried to determine the effectiveness and need for slag recycling in the prototype gasifier. In conclusion, a novel modelling approach was developed in this study for melting which can be used to improve and predict conditions in reactors. By tracking each particle individually, the model is well-equipped to simulate the packed bed in a discrete manner, allowing for unique particle temperatures, composition, and melting rates. The model has the potential to improve gasification performance as it is able to assess the performance of changing operating parameters at the design and operational stages. The use of various methods to reduce the high computational costs of modelling phase-change in large-scale facilities was also investigated, and the simultaneous melting and tracking of liquid phase within the solid packed bed was able to be predicted. Doctor of Philosophy 2023-04-27T06:22:39Z 2023-04-27T06:22:39Z 2022 Thesis-Doctor of Philosophy Soon, G. Q. Y. (2022). Multiphase CFD-DEM model for gasification and melting applications. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166302 https://hdl.handle.net/10356/166302 10.32657/10356/166302 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University |