Equivalent Reactor Network Model for Simulating the Air Gasification of Polyethylene in a Conical Spouted Bed Gasifier

Du, Yiqing; Yang, Qi; Berrouk, Abdallah S.; Yang, Chaohe; Shoaibi, Ahmed Al

doi:10.1021/ef501667n

Cited by 29 publications

(28 citation statements)

References 48 publications

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“…Number of Occurrences References k-ε 18 [90,92,203,204,206,209,211,212,[215][216][217][218][223][224][225][226][227][230][231][232],236] None or not specified 16 [25,89,91,202,203,205,207,208,210,213,214,[220][221][222]228,229] Riera and co-workers [217] simulated a multi-phase spouted column to test the validity of three turbulence models: the k-ε model, the k-ω model [240] and the SST model [241]. They observed that the k-ε and k-ω models yielded similar results for an air-water mixture, while the SST model was the most adequate for the air-water-sand mixture.…”

Section: Modelmentioning

confidence: 99%

“…Following an unusual CFD-based Equivalent Reactor Network (ERN) model, Du and colleagues [211] modelled the fluid dynamics of a spouted bed reactor employed as polyethylene gasifier to identify the separate fluid dynamics zone it features, and then considered each of them as a separate block in Aspen Plus © v7.3 (see Section 4).…”

Section: Study Of the Fluidisation Behaviourmentioning

confidence: 99%

“…In this sense, Li et al [253] outlined a 3D kinetic and computational fluid dynamic model for a pressurized spout-fluid bed and provided verification based on experimental data. Du et al [211] proposed a hydrodynamic model based on an equivalent reactor network built in Aspen Plus © with gasification of polyethylene reactions are included through an external FORTRAN module. The good agreement of the model results with experimental data permitted to obtain valuable information regarding the influence of the gasification temperature and equivalence ratio on the gasification performance.…”

Section: Plant Scale Modellingmentioning

confidence: 99%

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Modelling of Spouted and Spout-Fluid Beds: Key for Their Successful Scale Up

et al. 2017

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The development of robust mathematical models could provide the necessary tools for a more rapid, efficient, and reliable spouted bed technology development. Computer simulations can be very useful to aid this design and scale-up process: firstly, they can contribute to obtain a fundamental insight into their complex dynamic behavior by understanding the elementary physical principles such as drag, friction, dissipation etc.; secondly, the simulations can be used as a design tool where the ultimate goal is to have a numerical model with predictive capabilities for gas-particle flows at engineering scale. Clearly, one single simulation method will not be able to achieve this goal, but a hierarchy of methods modelling phenomena on different length and time scales can achieve this. The most fruitful approach will be when they are simultaneously followed, so that they can mutually benefit from each other. In this sense, this paper presents a review of the current state of the art of modelling on spouted and spout-fluid beds through an analysis of recent literature following a multiscale approach (molecular and particle, lab, plant and industrial scale). The main features of the different scales together with their current limits are discussed and specific topics are highlighted as paths that still need to be explored. In summary, the paper aims to define the theoretical setline and the basis of improvement that would lead to a robust multiscale model with solid links between micro and macroscopic phenomena. If done with the correct balance between accuracy and computational costs it will gear SB towards their reliable and successful implementation.

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Section: Modelmentioning

confidence: 99%

Section: Study Of the Fluidisation Behaviourmentioning

confidence: 99%

Section: Plant Scale Modellingmentioning

confidence: 99%

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Modelling of Spouted and Spout-Fluid Beds: Key for Their Successful Scale Up

et al. 2017

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“…where m biomass is the mass flow of the input biomass (in kg s -1 ), LHV biomass the lower heating value of the biomass (in kJ kg -1 ); and H, C, O, N are the mass fraction of hydrogen, carbon, oxygen, and nitrogen, respectively. Specific CO 2 emission indicates the mass unit flow of CO 2 emission divided by the energy generated by power and hydrogen [45,46]. This term is expressed as:…”

Section: Parameters Valuesmentioning

confidence: 99%

Biomass Gasification Integrated with Chemical Looping System for Hydrogen and Power. Coproduction Process – Thermodynamic and Techno‐Economic Assessment

2019

Self Cite

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Three biomass gasification-based hydrogen and power coproduction processes are modeled with Aspen Plus. Case 1 is the conventional biomass gasification coupled with a shift reactor, cases 2 and 3 involve integration of biomass gasification with iron-based and calcium-based chemical looping systems. The effects of important process parameters on the performance indicators such as hydrogen yield and efficiencies are evaluated by sensitivity analyses. These parameters include gasification temperature, molar ratios of steam to biomass in the gasifier, Fe 2 O 3 to syngas in the fuel reactor, Fe/FeO to steam in the steam reactor, CaO to CO, and steam to CO in the carbonator. The energy and exergy balance distributions for the above three cases are comprehensively discussed and compared. Furthermore, techno-economic assessments are performed to evaluate the three cases in terms of capital cost, operating cost, and leveled cost of energy.

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“…Each of these zones is then represented by a suitable ideal reactor in steady-state operation. 39 Originally, ERN models were applied for highly turbulent flows, which were not suitable for simulating a fixed bed with a low turbulence airflow crossing. Therefore, models have been proposed that consider the geometry and height of the fuel bed.…”

Section: ■ Introductionmentioning

confidence: 99%

Stochastic Reactor-Based Fuel Bed Model for Grate Furnaces

Netzer

Seidel

et al. 2020

Energy Fuels

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Biomass devolatilization and incineration in grate-fired plants are characterized by heterogeneous fuel mixtures, often incompletely mixed, dynamical processes in the fuel bed and on the particle scale, as well as heterogeneous and homogeneous chemistry. This makes modeling using detailed kinetics favorable but computationally expensive. Therefore, a computationally efficient model based on zero-dimensional stochastic reactors and reduced chemistry schemes, consisting of 83 gas-phase species and 18 species for surface reactions, is developed. Each reactor is enabled to account for the three phases: the solid phase, pore gas surrounding the solid, and the bulk gas. The stochastic reactors are connected to build a reactor network that represents the fuel bed in grate-fired furnaces. The use of stochastic reactors allows us to account for incompletely mixed fuel feeds, distributions of local temperature and local equivalence ratio within each reactor and the fuel bed. This allows us to predict the released gases and emission precursors more accurately than if a homogeneous reactor network approach was employed. The model approach is demonstrated by predicting pyrolysis conditions and two fuel beds of grate-fired plants from the literature. The developed approach can predict global operating parameters, such as the fuel bed length, species release to the freeboard, and species distributions within the fuel bed to a high degree of accuracy when compared to experiments.

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Equivalent Reactor Network Model for Simulating the Air Gasification of Polyethylene in a Conical Spouted Bed Gasifier

Cited by 29 publications

References 48 publications

Modelling of Spouted and Spout-Fluid Beds: Key for Their Successful Scale Up

Modelling of Spouted and Spout-Fluid Beds: Key for Their Successful Scale Up

Biomass Gasification Integrated with Chemical Looping System for Hydrogen and Power. Coproduction Process – Thermodynamic and Techno‐Economic Assessment

Stochastic Reactor-Based Fuel Bed Model for Grate Furnaces

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