Investigation of flow through a computationally generated packed column using CFD and additive layer manufacturing

Preprint submitted to Computers and Chemical Engineering 18 March 2014. © The AuthorsThe version of record is available from the publisher via doi:10.1016/j.compchemeng.2014.04.005.When analysing packed beds using CFD approaches, producing an accurate geometry is often challenging. Often a computational model is produced from non-invasive imaging of the packed bed using 3d MRI or μ-CT. This work pioneers the exact reverse of this, by creating a physical bed from the computational model using Additive Layer Manufacturing (ALM). The paper focuses on both experimental analysis and computational analysis of packed columns of spheres. A STL file is generated of a packed column formed using a Monte-Carlo packing algorithm, and this is meshed and analysed using Computational Fluid Dynamics. In addition to this, a physical model is created using ALM on a 3d printer. This allows us to analyse the identical bed geometry both computationally and experimentally and compare the two. Pressure drop and flow patterns are analysed within the bed in detail. © 2014 Elsevier Ltd

Computational analysis of transitional airflow through packed columns of spheres using the finite volume technique

Copyright © 2010 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Computers and Chemical Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Chemical Engineering, Volume 34 Issue 6 (2010), DOI: 10.1016/j.compchemeng.2009.10.013We compare computational simulations of the flow of air through a packed column containing spherical particles with experimental and theoretical results for equivalent beds. The column contained 160 spherical particles at an aspect ratio N=7.14N=7.14, and the experiments and simulations were carried out at particle Reynolds numbers of (RedP=700−5000)(RedP=700−5000). Experimental measurements were taken of the pressure drop across the column and compared with the correlation of Reichelt (1972) using the fitted coefficients of Eisfeld and Schnitzlein (2001). An equivalent computational domain was prepared using Monte Carlo packing, from which computational meshes were generated and analysed in detail. Computational fluid dynamics calculations of the air flow through the simulated bed was then performed using the finite volume technique. Results for pressure drop across the column were found to correlate strongly with the experimental data and the literature correlation. The flow structure through the bed was also analysed in detail

A systematic procedure for the virtual reconstruction of open-cell foams

Open-cell foams are considered a potential candidate as an innovative catalyst support in many processes of the chemical industry. In this respect, a deeper understanding of the transport phenomena in such structures can promote their extensive application. In this contribution, we propose a general procedure to recover a representative open-cell structure starting from some easily obtained information. In particular, we adopt a realistic description of the foam geometry by considering clusters of solid material at nodes and different strut-cross sectional shapes depending on the void fraction. The methodology avoids time-consuming and expensive measuring techniques, such as micro-computed tomography (μCT) or magnetic resonance imaging (MRI). Computational Fluid Dynamics (CFD) could be a powerful instrument to enable accurate analyses of the complex flow field and of the gas-to-solid heat and mass transport. The reconstructed geometry can be easily exploited to generate a suitable computational domain allowing for the detailed investigation of the transport properties on a realistic foam structure by means of CFD simulations. Moreover, the proposed methodology easily allows for parametric sensitivity analysis of the foam performances, thus being an instrument for the advanced design of these structures. The geometrical properties of the reconstructed foams are in good agreement with experimental measurements. The flow field established in complex tridimensional geometries reproduces the real foam behavior as proved by the comparison between numerical simulations and experiments

Multi-scale modeling of inertial flows through propped fractures

Non-Darcy flows are expected to be ubiquitous in near wellbore regions, completions, and in hydraulic fractures of high productivity gas wells. Further, the prevailing dynamic effective stress in the near wellbore region is expected to be an influencing factor for the completion conductivity and non-Darcy flow behavior in it. In other words, the properties (fracture permeability and β-factor) can vary with the time and location in the reservoir (especially in regions close to the wellbore). Using constant values based on empirical correlations for reservoirs/completions properties can lead to erroneous cumulative productivity predictions. With the recent advances in the imaging technology, it is now possible to reconstruct pore geometries of the proppant packs under different stress conditions. With further advances in powerful computing platforms, it is possible to handle large amount of computations such as Lattice Boltzmann (LB) simulations faster and more efficiently. Calculated properties of the proppant pack at different confining stresses show reasonable agreement with the reported values for both permeability and β-factor. These predicted stress-dependent permeability and β-factors corresponding to the effective stress fields around the hydraulic fractured completions is included in a 2D gas reservoir simulator to calculate the productivity index. In image-based flow simulations, spatial resolution of the digital images used for modeling is critical not only because it dictates the scale of features that can be resolved, but also because for most techniques there is at least some relationship between voxel size in the image data and numerical resolution applied to the computational simulations. In this work we investigate this relationship using a computer-generated consolidated porous medium, which was digitized at voxel resolutions in the range 2-10 microns. These images are then used to compute permeability and tortuosity using lattice Boltzmann (LB) and compared against finite elements methods (FEM)simulation results. Results show how changes in computed permeability are affected by image resolution (which dictates how well the pore geometry is approximated) versus grid or mesh resolution (which changes numerical accuracy). For LB, the image and grid resolution are usually taken to be the same; we show at least one case where effects of grid and image resolution appear to counteract one another, giving the mistaken appearance of resolution-independent results. For FEM, meshing can provide certain attributes (such as better conformance to surfaces), but it also adds an extra step for error or approximation to be introduced in the workflow