Influence of Foam Morphology on Flow and Heat Transport in a Random Packed Bed with Metallic Foam Pellets-An Investigation Using CFD.

Open-cell metallic foams used as catalyst supports exhibit excellent transport properties. In this work, a unique application of metallic foam, as pelletized catalyst in a packed bed reactor, is examined. By using a wall-segment Computational Fluid Dynamics (CFD) setup, parametric analyses are carried out to investigate the influence of foam morphologies (cell size ϕ=0.45−3 mm and porosity ε=0.55−0.95) and intrinsic conductivity on flow and heat transport characteristics in a slender packed bed (N=D/dp=6.78) made of cylindrical metallic foam pellets. The transport processes have been modeled using an extended version of conventional particle-resolved CFD, i.e., flow and energy in inter-particle spaces are fully resolved, whereas the porous-media model is used for the effective transport processes inside highly-porous foam pellets. Simulation inputs include the processing parameters relevant to Steam Methane Reforming (SMR), analyzed for low (Rep~100) and high (Rep~5000) flow regimes. The effect of foam morphologies on packed beds has shown that the desired requirements contradict each other, i.e., an increase in cell size and porosity favors the reduction in pressure drop, but, it reduces the heat transfer efficiency. A design study is also conducted to find the optimum foam morphology of a cylindrical foam pellet at a higher Rep~5000, which yields ϕ = 0.45, ε = 0.8. Suitable correlations to predict the friction factor and the overall heat transfer coefficient in a foam-packed bed have been presented, which consider the effect of different foam morphologies over a range of particle Reynolds number, 100≤Rep≤5000.

Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO2 Hydrogenation on Ni(111).

Automatic mechanism generation is used to determine mechanisms for the CO2 hydrogenation on Ni(111) in a two-stage process while considering the correlated uncertainty in DFT-based energetic parameters systematically. In a coarse stage, all the possible chemistry is explored with gas-phase products down to the ppb level, while a refined stage discovers the core methanation submechanism. Five thousand unique mechanisms were generated, which contain minor perturbations in all parameters. Global uncertainty assessment, global sensitivity analysis, and degree of rate control analysis are performed to study the effect of this parametric uncertainty on the microkinetic model predictions. Comparison of the model predictions with experimental data on a Ni/SiO2 catalyst find a feasible set of microkinetic mechanisms within the correlated uncertainty space that are in quantitative agreement with the measured data, without relying on explicit parameter optimization. Global uncertainty and sensitivity analyses provide tools to determine the pathways and key factors that control the methanation activity within the parameter space. Together, these methods reveal that the degree of rate control approach can be misleading if parametric uncertainty is not considered. The procedure of considering uncertainties in the automated mechanism generation is not unique to CO2 methanation and can be easily extended to other challenging heterogeneously catalyzed reactions.

3D-printed micro bubble column reactor with integrated microsensors for biotechnological applications: From design to evaluation.

With the technological advances in 3D printing technology, which are associated with ever-increasing printing resolution, additive manufacturing is now increasingly being used for rapid manufacturing of complex devices including microsystems development for laboratory applications. Personalized experimental devices or entire bioreactors of high complexity can be manufactured within few hours from start to finish. This study presents a customized 3D-printed micro bubble column reactor (3D-µBCR), which can be used for the cultivation of microorganisms (e.g., Saccharomyces cerevisiae) and allows online-monitoring of process parameters through integrated microsensor technology. The modular 3D-µBCR achieves rapid homogenization in less than 1 s and high oxygen transfer with kLa values up to 788 h-1 and is able to monitor biomass, pH, and DOT in the fluid phase, as well as CO2 and O2 in the gas phase. By extensive comparison of different reactor designs, the influence of the geometry on the resulting hydrodynamics was investigated. In order to quantify local flow patterns in the fluid, a three-dimensional and transient multiphase Computational Fluid Dynamics model was successfully developed and applied. The presented 3D-µBCR shows enormous potential for experimental parallelization and enables a high level of flexibility in reactor design, which can support versatile process development.