Direct numerical simulation (DNS) of alkali metals released during char combustion

Qu, Sibo; You, Changfu

doi:10.1016/j.fuel.2019.115763

Cited by 6 publications

(4 citation statements)

References 32 publications

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“…Lattice models of coke-ash structure evolution were proposed in [253,254]. The evaporation of alkali metals was introduced in the fuel particle combustion model in [255]. Models of the slag deposits formation on heat exchange surfaces considering the solid and molten ash particles interaction, make it possible to describe the decrease in heat transfer efficiency in boilers [256][257][258][259][260][261].…”

Section: Interfacial Interactionsmentioning

confidence: 99%

Particle Agglomeration of Biomass and Plastic Waste during Their Thermochemical Fixed-Bed Conversion

Donskoy

2023

Energies

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The article provides state-of-the-art research on agglomeration processes during fixed-bed combustion and gasification of low-grade fuels such as biomass and waste (primarily plastic-containing waste). Such fuels demonstrate complex thermal behaviour: their decomposition and combustion are multistage, accompanied by phase transitions, and may lead to fixed-bed mechanical instability and the non-uniformity of air distribution over the cross-section. To clarify the role of physicochemical factors (fuel composition and properties, reactor conditions), data from different sources are compared. The review shows that the fixed-bed agglomeration regimes can, in a rough approximation, be classified by the sintering mechanism (due to the melting of the mineral part or the organic part), with the following search for each mechanism realisation conditions by comparing the fuel properties and characteristic temperatures. Attempts to theoretically describe and numerically simulate the agglomeration phenomenon as a change in the structure of a reacting dispersed medium are also considered: the main directions in which such approaches can be developed are indicated.

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Section: Interfacial Interactionsmentioning

confidence: 99%

Particle Agglomeration of Biomass and Plastic Waste during Their Thermochemical Fixed-Bed Conversion

Donskoy

2023

Energies

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“…For multiphase flows with mass transfer, the boundary conditions for two typical types of mass transfer problems are discussed. The first type is the mass transfer among a membrane without heterogeneous surface reaction or permeation problem (De Jong et al 2012a;De Jong et al 2012b;Miyauchi et al 2017;Takeuchi et al 2019;Yao and Mori 2017), and the second type is the mass transfer associated with heterogeneous surface reaction (Lu et al 2019a;Qu and You 2019;Yousefzadeh and Battiato 2019;Zhu et al 2019).…”

Section: Mass Transfer Boundary Conditionsmentioning

confidence: 99%

Immersed boundary method for multiphase transport phenomena

Wei

Zhang

Luo

et al. 2020

Reviews in Chemical Engineering

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Multiphase flows with momentum, heat, and mass transfer exist widely in a variety of industrial applications. With the rapid development of numerical algorithms and computer capacity, advanced numerical simulation has become a promising tool in investigating multiphase transport problems. Immersed boundary (IB) method has recently emerged as such a popular interface capturing method for efficient simulations of multiphase flows, and significant achievements have been obtained. In this review, we attempt to give an overview of recent progresses on IB method for multiphase transport phenomena. Firstly, the governing equations, the basic ideas, and different boundary conditions for the IB methods are introduced. This is followed by numerical strategies, from which the IB methods are classified into two types, namely the artificial boundary method and the authentic boundary method. Discussions on the implementation of various boundary conditions at the interphase surface with momentum, heat, and mass transfer for different IB methods are then presented, together with a summary. Then, the state-of-the-art applications of IB methods to multiphase flows, including the isothermal flows, the heat transfer flows, and the mass transfer problems are outlined, with particular emphasis on the latter two topics. Finally, the conclusions and future challenges are identified.

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“…Lui et al simulated a uniformly fixed distributed particle group combustion. We simulated moving particle combustion using a fictitious domain method (FDM), which adopts a set of unified mesh and governing equations describing both the gas and solid phases. , In addition, research on the drag force of particles in a combustion environment has progressed steadily …”

Section: Introductionmentioning

confidence: 99%

“…We simulated moving particle combustion using a fictitious domain method (FDM), which adopts a set of unified mesh and governing equations describing both the gas and solid phases. 22,23 In addition, research on the drag force of particles in a combustion environment has progressed steadily. In recent years, machine-learning (ML) approaches have also gained extensive application in solving the classification and regression problems in particle systems.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Combustion Characteristics of Particles in Transient Gas–Solid Reacting Flow via a Machine Learning Approach

Zhang

You

2022

Ind. Eng. Chem. Res.

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Particle group combustion presents a strong temporal and spatial inhomogeneity owing to the complicated interphase interactions. Based on the data set from the fictitious domain method, the recurrent fully connected and convolutional parallel neural network (R-FC&CNN) architecture and its two comparable simplified models, that is, the recurrent fully connected neural network (R-FCNN) and the recurrent convolutional neural network (R-CNN) architectures, were constructed for predicting the gas−solid momentum exchange coefficient, β (kg•s −1 • m −3 ), average combustion rate per unit surface area of particles, r A / c (kg• s −1 •m −2 ), and comprehensive NaCl release parameter, γ, selectively. A time sequence of average particle temperature, T̅ (K), and particle volume fraction, ε, which can be extended in the matrix form, were constructed as the features selectively according to their correlation with the target physical quantity. The average relative error, δ̅ , and coefficient of determination, R 2 , were used as the evaluators. Through final testing, in the mild combustion domain, the R-CNN and R-FCNN models with simple structures showed good performance for β(δ̅ = 0.13, R 2 = 0.8) and r A / c (δ̅ = 0.04, R 2 = 0.84), respectively, while in the severe combustion domain, the R-FC&CNN model, with more complete features and functional structure, performed the best (for β, δ̅ = 0.12, R 2 = 0.85; for r A / c , δ̅ = 0.05, R 2 = 0.92; and for γ, = = R 0.05, 0.96 2). A fine-tuning and interpolated prediction method was developed to investigate further the model's expansibility. Both ensured acceptable performance on a new similar problem. In summary, the feasibility of physical meaningoriented machine learning--based model(s) for predicting the combustion characteristics of nonuniformly distributed particles was confirmed.

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Direct numerical simulation (DNS) of alkali metals released during char combustion

Cited by 6 publications

References 32 publications

Particle Agglomeration of Biomass and Plastic Waste during Their Thermochemical Fixed-Bed Conversion

Particle Agglomeration of Biomass and Plastic Waste during Their Thermochemical Fixed-Bed Conversion

Immersed boundary method for multiphase transport phenomena

Modeling of Combustion Characteristics of Particles in Transient Gas–Solid Reacting Flow via a Machine Learning Approach

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