Drag force for a burning particle

Zhang, Hancong; Luo, Kun; Haugen, Nils Erland L.; Mao, Chaoli; Fan, Jianren

doi:10.1016/j.combustflame.2020.02.016

Cited by 27 publications

(10 citation statements)

References 44 publications

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“…• Gaseous combustion and detonation (Babkovskaia, Haugen, and Brandenburg 2011;Zhang et al 2020;Krüger, Haugen, and Løvås 2017), • Burning particles, resolved or unresolved (Qian et al 2020),…”

Section: Discussionmentioning

confidence: 99%

The Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained

Brandenburg,

Johansen,

Bourdin

et al. 2020

Preprint

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code can also evolve Lagrangian (inertial and noninertial) particles, their coagulation and condensation, as well as their interaction with the fluid. A related module has also been adapted to perform ray tracing and to solve the eikonal equation.The code is being used for Cartesian, cylindrical, and spherical geometries, but further extensions are possible. One can choose between different time stepping schemes and different spatial derivative operators. High-order first and second derivatives are used to deal with weakly compressible turbulent flows. There are also different diffusion operators to allow for both direct numerical simulations (DNS) and various types of large-eddy simulations (LES). High-level functionalityAn idea about the range of available modules can be obtained by inspecting the examples under pencil-code/samples/. Those are low resolution versions related to applications published in the literature. Some of the run directories of actual production runs are published through Zenodo. Below a list of method papers that describe the various applications and tests:

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Section: Discussionmentioning

confidence: 99%

The Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained

Brandenburg,

Johansen,

Bourdin

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…Non-sphericity is not the only factor that impacts the drag force. It has been proven by Zhang et al [267] that the drag force of a particle in the presence of homogeneous and heterogeneous reactions is different from a simple particle with outflow in non-reactive conditions. This is supposed to be more pronounced in the gasification process compared to pyrolysis, due to subsequent homogeneous and heterogeneous gasification reactions around the particles/droplets (Figure 5).…”

Section: Drag Forcementioning

confidence: 99%

Multi-Scale Modeling of Plastic Waste Gasification: Opportunities and Challenges

et al. 2022

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Among the different thermo-chemical recycling routes for plastic waste valorization, gasification is one of the most promising, converting plastic waste into syngas (H2+CO) and energy in the presence of an oxygen-rich gas. Plastic waste gasification is associated with many different complexities due to the multi-scale nature of the process, the feedstock complexity (mixed polyolefins with different contaminations), intricate reaction mechanisms, plastic properties (melting behavior and molecular weight distribution), and complex transport phenomena in a multi-phase flow system. Hence, creating a reliable model calls for an extensive understanding of the phenomena at all scales, and more advanced modeling approaches than those applied today are required. Indeed, modeling of plastic waste gasification (PWG) is still in its infancy today. Our review paper shows that the thermophysical properties are rarely properly defined. Challenges in this regard together with possible methodologies to decently define these properties have been elaborated. The complexities regarding the kinetic modeling of gasification are numerous, compared to, e.g., plastic waste pyrolysis, or coal and biomass gasification, which are elaborated in this work along with the possible solutions to overcome them. Moreover, transport limitations and phase transformations, which affect the apparent kinetics of the process, are not usually considered, while it is demonstrated in this review that they are crucial in the robust prediction of the outcome. Hence, possible approaches in implementing available models to consider these limitations are suggested. Finally, the reactor-scale phenomena of PWG, which are more intricate than the similar processes—due to the presence of molten plastic—are usually simplified to the gas-solid systems, which can result in unreliable modeling frameworks. In this regard, an opportunity lies in the increased computational power that helps improve the model’s precision and allows us to include those complexities within the multi-scale PWG modeling. Using the more accurate modeling methodologies in combination with multi-scale modeling approaches will, in a decade, allow us to perform a rigorous optimization of the PWG process, improve existing and develop new gasifiers, and avoid fouling issues caused by tar.

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“…• Gaseous combustion and detonation (Babkovskaia et al, 2011;Krüger et al, 2017;Zhang et al, 2020), • Burning particles, resolved or unresolved (Qian et al, 2020),…”

Section: High-level Functionalitymentioning

confidence: 99%

The Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained

Brandenburg¹,

Johansen²,

Bourdin³

et al. 2021

JOSS

116

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Drag force for a burning particle

Cited by 27 publications

References 44 publications

The Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained

The Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained

Multi-Scale Modeling of Plastic Waste Gasification: Opportunities and Challenges

The Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained

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