Predicting Average Void Fraction and Void Fraction Uncertainty in Fixed Beds of Poly Lobed Particles

Abstract

Random packed beds of cylindrical, trilobic and quadrilobic particles in cylindrical and bi-periodic containers are numerically studied using Grains 3D, a code based on the Discrete Element Method (DEM) that resolves all inelastic collisions and simulates dynamically the loading of packed beds. To mimic industrial or laboratory packing 1 procedures, particles initial position and orientation are random so that the same simulation repeated again yields a different packed bed structure and thus a different average void fraction. These "in silico" experiments aim at being able to optimize particle shape in heterogeneous catalysis, in particular with respect to the corresponding bed void fraction that is a critical parameter for pressure drop prediction. These "in silico" experiments are deterministic and accurate but with differences due to the loading procedure. In this paper, we first present our assessment of the uncertainty on average void fraction induced by (i) the initial random position and orientation of inserted particles and (ii) the insertion zone size. Next we investigate the effect of particle shape, namely cylindrical, trilobic and quadrilobic on the average void fraction as a function of particle length and diameter, and of the container type. Simple correlations are proposed that describe very well the simulations within the aforementioned uncertainty related to the packing procedure. While the beds made with cylindrical particles are markedly denser, the beds made of the trilobic and quadrilobic particles have statistically an identical void fraction.

Bridging Scales in Bioenergy and Catalysis: A Review of Mesoscale Modeling Applications, Methods, and Future Directions

“…However, fluid physics at the biomass particle scale are not fully understood and may play important roles in determining macroscopic performance, such as product oil yield or extent of biopolymer fractionation. , For example, gas diffusion through dry biomass cell lumen (i.e., macropores used by plants to transport water) may occur much more rapidly than bulk liquid diffusion, where capillary lumen wetting and surface tension effects may influence mass transport time scales; then, within individual cell walls, solute ions and/or molecules must navigate dense, rubbery polymeric membranes , of nanoscale porosity , in tandem with participating in the desired physical or chemical transformations that are altering the local environment. Critical physical descriptors of cell walls and lumen domains, such as porosity (i.e., void fraction), − pore size distributions, ,,,, tortuosity, , and heat transfer coefficients, , can vary substantially between biomass feedstocks as a function of treatment history and species of origin, and much remains to be understood about gas/liquid/biomass mass transfer interactions. Quantitative knowledge of key reaction–diffusion time and length scales and of associated thermal gradients is crucial for proper design of experiments and data interpretation in each laboratory, bench, and pilot setting.…”

“…Significant knowledge and refinement are still needed to better understand directional permeability and anisotropy in biomass tissues, , particularly for liquid-phase transport. At the reactor scale, recent efforts to demonstrate fixed-bed flow reactors for biomass deconstruction , and combined or tandem catalytic upgrading ,− have largely emphasized product yields at extended times-on-stream for comparison to batch processes; however, gas/liquid reactant hydrodynamics and contacting patterns must also be heeded to ensure appropriate kinetic control and upscaling, particularly for packed biomass beds, wherein incomplete particle wetting and irregular packing are expected. All the above are important feedstock-specific attributes that must be considered alongside biomass conversion kinetics in order to make meaningful performance predictions for a given biorefinery strategy.…”

“…At the molecular scale, reactants and solvents may, for example, compete for adsorption sites on the surface of catalyst particles, while solvents may ultimately affect the stability of transition states of important reactive intermediates. At the mesoscale, mass transport limitations unique to both solid phases may complicate the collection and interpretation of kinetic rate data, particularly when both are combined in the same reactor, requiring proper diagnostic assessment and control. ,, Further, many catalyst materials were historically designed for operational stability in the gas phase; thus, liquid-phase components and coproducts (especially water) arising from conversion of unconventional feedstocks such as biomass may influence unintended structural changes to catalyst surfaces, pores and their connectivities, leading to time-evolved material properties and performance. − Catalyst deactivation is an especially criticalyet frequently overlookedkinetic phenomenon in reaction media and hence must be assessed via kinetically controlled conditions. − However, upon proper evaluation, , this behavior may be readily incorporated into mesoscale and reactor-scale modeling frameworks ,− to enable reliable process science and operational de-risking.…”

Numerical determination of the volumetric heat transfer coefficient in fixed beds of wood chips

“…It uses the Gilbert-Johnson-Keerthi (GJK) algorithm (39) to detect collisions and compute contact forces and momentum. More details on Grains3D and its validation on convex particles and workflow can be found in (40,41). For the cases presented here, the spheres were introduced one by one at random locations in an insertion box located in the upper part of the cylindrical reactor.…”

Local Percolation of a Binary Particle Mixture in a Rectangular Hopper with Inclined Bottom during Discharging

“…In the past few decades, segregation of particles in hoppers has attracted great attention from scholars. , Scholars have done a lot of research work on particle size segregation in hoppers by experiments and the discrete element method (DEM). − Geometric parameters, − particle properties, − and interaction parameters have significant effects on segregation, and there is obvious percolation on the free surface . Among them, DEM, as an effective method, has been widely used in the simulation of particle motion. − Some information that cannot be directly obtained in experiment can be obtained through DEM simulations.…”