Identification of Channeling in Pore‐Scale Flows

We quantify flow channeling at the microscale in three-dimensional porous media. The study is motivated by the recognition that heterogeneity and connectivity of porous media are key drivers of channeling. While efforts in the characterization of this phenomenon mostly address processes at the continuum scale, it is recognized that pore-scale preferential flow may affect the behavior at larger scales. We consider synthetically generated pore structures and rely on geometrical/topological features of subregions of the pore space where clusters of velocity outliers are found. We relate quantitatively the size of such fast channels, formed by pore bodies and pore throats, to key indicators of preferential flow and anomalous transport. Pore-space spatial correlation provides information beyond just pore size distribution and drives the occurrence of these velocity structures. The latter occupy a larger fraction of the pore-space volume in pore throats than in pore bodies and shrink with increasing flow Reynolds number. Plain Language Summary The movement of fluids and dissolved chemicals through porous media is massively affected by the heterogeneous nature of these systems. The presence of "fast channels," that is, preferential flow paths characterized by large velocities persisting over long distances, gives rise to very short solute travel times, with key implications in, for example, environmental risk assessment. While efforts in the characterization of this phenomenon mostly address processes at the continuum (laboratory or field) scale, it is recognized that pore-scale channeling of flow may affect the system behavior at larger scales. Here we provide criteria for the identification of fast channels at the pore scale, addressing feedback between channeling and geometrical/topological features of the investigated porous structures. Our results clearly evidence the major role of well-defined regions in the pore space, termed pore throats, in driving flow channeling. We also find that the strength of channeling is controlled by the characteristic Reynolds number of the flow field.Fraunhofer Award for Young Researchers; EU; MIUR6 month embargo; published online: 13 March 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

3D-CFD analysis of the effect of cooling via minitubes on the performance of a three-fluid combined membrane contactor

Abstract A 3D computational fluid dynamics model was adopted to study the effects of internal cooling on the performance of a three-fluid combined membrane contactor (3F-CMC), in the presence of minitubes in solution and a spacer in the air channel. This compact 3F-CMC is part of a hybrid climate-control system, recently developed for serving in electric vehicles. For the studied operating conditions, results show that the absorption and sensible effectiveness parameters increase up to 77% and 124% by internal cooling, respectively. This study also reports 3D flow effects on the heat and mass transfer enhancement inside the contactor, with implications for further design improvements

Simulation of Thermochemical Heat Storage in the CaO/Ca(OH)2- System on the Micro-Scale

Thermochemical Energy Storge (TCES) has long been under investigation for prospective applications including the capture of excess heat from industrial processes or storing energy in concentrated solar power plants. Furthermore, TCES in the CaO/Ca(OH)2-System is investigated because of the low price and environmentally friendliness of the reactants. In the project THEMSE, DLR is developing models and simulations for TCES in the CaO/Ca(OH)2-System on the microscopic level. A geometrical microscale characterization of the material is done using a combination of micro computed tomography (µCT) and scanning electron microscopy (SEM). Where SEM can be used to resolve fine scale details, up to crystallites, µCT can resolve particles as well as agglomerates of numerous particles. This is complemented by kinetics, measured by thermogravimetric analysis. The first goal in the project is to explain the measured kinetics using a spatially resolved model, which takes the three-dimensional morphology of the storage material into account. In general, this involves, thermal, hydrodynamic, mechanical, and chemical modeling. However, the first investigations involve a single particle model, where the thermal and hydrodynamic effects can be neglected, and which is solved using finite element simulations. In this talk, we give an overview over the project and the materials involved and we will show first results from kinetic simulations and experiments

Modeling of Powder Bed Dynamics in Thermochemical Heat Storage

Storing energy in the form of heat has been under long-standing investigation for prospective applications, such as the capturing of excess heat from industrial processes as well as storing energy in concentrated solar power plants. Investigated mechanisms for the heat storage include the adsorption in porous media, materials undergoing phase changes and thermochemical reactions. Among these, thermochemical heat storage provides a large energy capacity and next to perfect reversibility. More specifically, storage in the CaO/Ca(OH)2-System is investigated because of the low price and environmental friendliness of the reactants. In the project THEMSE, DLR is developing models and simulations as well as experimental characterization methods for thermochemical heat storage in the CaO/Ca(OH)2-System. In this talk, we shall give an overview over the project with a focus on the modeling activities. Special attention is given to the investigation of how the cycling of the material influences the heat and mass transport in the powder bed inside the reactor. This happens through mechanical and physical alteration of the powder bed, mainly through three mechanisms. First, the gas flow through the reactor exerts a force on the powder particles, compacting the powder bed. The resulting densification of the bed increases its flow resistance, while improving the heat transport. Second, the agglomeration of powder particles, where bonds between the particles form, turning the bed into a solid. The exact mechanism of the agglomeration is yet unknown, but it can be characterized by mechanical measurements. Third, the expansion of the powder particles through water uptake during the hydration stage, and the corresponding contraction during dehydration. To model the compaction and solidification of the powder bed during cycling, we present a mechanical model based on Drucker-Prager-Cap plasticity, which has been used previously for powder compaction, see e.g. [1]. The parameterization of the model, i.e., the plastic yield surface, is done via flow tester experiments. The changes in the powder bed during cycling are modeled by hardening mechanisms, i.e., a changing yield surface, corresponding to powder compaction and agglomeration, respectively. Then, the plastic model is coupled to a reactor scale model, simulating the heat and mass transport, as well as the thermochemical reaction using a model, similar to [2]. This enables the study of the powder bed dynamics under different boundary conditions during cycling, such as pressure drop, water vapor fraction and reactor geometry. Finally, an outlook will be given on the multi-scale modeling of the reactor. The geometrical micro-scale characterization of the material is done using micro computed tomography (µCT). From the µCT-Images, effective transport parameters, such as diffusivity and permeability are computed for different stages of agglomeration. These are then used in the reactor-scale model to produce predictions, which can be verified on the reactor-scale. [1] Wu, C.-Y & Ruddy, O.M. & Bentham, A.C. & Hancock, B.C. & Best, Serena & Elliott, James. (2005). Modelling the mechanical behaviour of pharmaceutical powders during compaction. Powder Technology. 152. 107-117. 10.1016/j.powtec.2005.01.010. [2] Nagel, Thomas & Shao, Haibing & Singh, Ashok & Watanabe, Norihiro & Roßkopf, Christian & Linder, Marc & Wörner, A & Kolditz, Olaf. (2013). Non-equilibrium thermochemical heat storage in porous media: Part 1 – Conceptual model. Energy. -. 10.1016/j.energy.2013.06.025

Caractérisation et modélisation de structures carbonées nanoporeuses

The aim of the work presented here is to optimize nanoporous carbon materials by means of 'virtual material design'. On this length scale (~ 10nm) Focused Ion Beam – Scanning Electron Microscopy Nanotomography (FIB-SEM) is the only imaging technique providing three dimensional geometric information. Yet, for the optimization, the pore space of the materials must be reconstructed from the resulting image data, which was a generally unsolved problem so far.To overcome this problem, a simulation method for FIB-SEM images was developed. The resulting synthetic FIB-SEM images could then be used to test and validate segmentation algorithms. Using simulated image data, a new algorithm for the morphological segmentation of the highly porous structures from FIB-SEM data was developed, enabling the reconstruction of the three dimensional pore space from FIB-SEM images.Two case studies with nanoporous carbons used for energy storage are presented, using the new techniques for the characterization and optimization of electrodes of Li-ion batteries and electric double layer capacitors (EDLC's), respectively. The reconstructed pore space is modeled geometrically by means of stochastic geometry. Finally, the electrical properties of the materials were simulated using both imaged real and modeled structures.L'objectif de la thèse présentée ici est l'optimisation de matériaux carbonésnanoporeux au moyen de la “conception de matériaux virtuels”. En ce qui concerne cette échelle de travail (~ 10nm), la Nanotomographie FIB-SEM est la seule technique d'imagerie donnant accès à une information sur la géométrie tridimensionnelle. Cependant, pour l'optimisation du comportement, l'espace des pores doit être reconstruit à partir des données tirées des images obtenues. Jusqu'à présent ce problème n'était pas résolu. Pour pouvoir le maîtriser, on a développé une simulation d'images FIB-SEM. Les images FIB-SEM simulées peuvent être utilisées pour la vérification et la validation des algorithmes de segmentation. En utilisant les données d'image simulées, un nouvel algorithme pour la reconstruction de l'espace des pores à partir des données FIB-SEM a été développé.Deux études de cas avec des carbones nanoporeux utilisés pour le stockage d'énergie sont présentées, en utilisant les nouvelles techniques pour la caractérisation et l'optimisation des électrodes Li-ion de type EDLC'S (« electric double-layer capacitors », soit supercondensateurs). L'espace des pores reconstruit est modélisé géométriquement à l'aide de la géométrie stochastique. Enfin, on a simulé les propriétés électriques des matériaux enutilisant des structures modélisées et simulées

Charakterisierung und Modellierung nanoporöser Kohlenstoffstrukturen

The aim of the work presented here is to optimize nanoporous carbon materials by means of 'virtual material design'. On this length scale (~ 10nm) Focused Ion Beam – Scanning Electron Microscopy Nanotomography (FIB-SEM) is the only imaging technique providing three dimensional geometric information. Yet, for the optimization, the pore space of the materials must be reconstructed from the resulting image data, which was a generally unsolved problem so far. To overcome this problem, a simulation method for FIB-SEM images was developed. The resulting synthetic FIB-SEM images could then be used to test and validate segmentation algorithms. Using simulated image data, a new algorithm for the morphological segmentation of the highly porous structures from FIB-SEM data was developed, enabling the reconstruction of the three dimensional pore space from FIB-SEM images. Two case studies with nanoporous carbons used for energy storage are presented, using the new techniques for the characterization and optimization of electrodes of Li-ion batteries and electric double layer capacitors (EDLC's), respectively. The reconstructed pore space is modeled geometrically by means of stochastic geometry. Finally, the electrical properties of the materials were simulated using both imaged real and modeled structures.Das Ziel dieser Arbeit ist die Optimierung von nanoporösen Kohlenstoffmaterialien durch virtuelles Materialdesign. Auf dieser Längenskala (~ 10 nm) kann nur die Focused Ion Beam - Scanning Electron Microscopy Nanotomography (FIB-SEM) die Geometrie einer Probe dreidimensional abbilden. Jedoch muss für eine Optimierung des Materials der Porenraum aus den Bilddaten rekonstruiert werden. Dies war ein bisher im Allgemeinen ungelöstes Problem. Um das Rekonstruktionsproblem zu lösen, wurde eine Simulationsmethode für FIB-SEM-Bilder entwickelt. Die sich daraus ergebenden synthetischen Bilder konnten dann benutzt werden, um Segmentierungsalgorithmen zu testen und zu validieren. Mit den simulierten Daten wurde ein neuer, auf mathematischer Morphologie basierender Segmentierungsalgorithmus entwickelt, welcher es erlaubt den dreidimensionalen Porenraum hochporöser Materialien zu rekonstruieren. In dieser Arbeit werden zwei Fallstudien mit nanoporösen Kohlenstoffen für Energiespeicherung vorgestellt, in denen die neuen Techniken zur Charakterisierung und Optimierung von Elektrodenmaterialien für Li-Ionen-Akkus sowie Doppelschichtkondensatoren (EDLCs) eingesetzt werden. Dann wurde der rekonstruierte Porenraum mit Hilfe der stochastischen Geometrie geometrisch modelliert. Letztendlich wurden die elektrischen Eigenschaften der Materialien simuliert, sowohl auf echten abgebildeten Strukturen, als auch auf modellierten Strukturen

Characterization and modeling of nanoporous carbon structures

L'objectif de la thèse présentée ici est l'optimisation de matériaux carbonésnanoporeux au moyen de la “conception de matériaux virtuels”. En ce qui concerne cette échelle de travail (~ 10nm), la Nanotomographie FIB-SEM est la seule technique d'imagerie donnant accès à une information sur la géométrie tridimensionnelle. Cependant, pour l'optimisation du comportement, l'espace des pores doit être reconstruit à partir des données tirées des images obtenues. Jusqu'à présent ce problème n'était pas résolu. Pour pouvoir le maîtriser, on a développé une simulation d'images FIB-SEM. Les images FIB-SEM simulées peuvent être utilisées pour la vérification et la validation des algorithmes de segmentation. En utilisant les données d'image simulées, un nouvel algorithme pour la reconstruction de l'espace des pores à partir des données FIB-SEM a été développé.Deux études de cas avec des carbones nanoporeux utilisés pour le stockage d'énergie sont présentées, en utilisant les nouvelles techniques pour la caractérisation et l'optimisation des électrodes Li-ion de type EDLC'S (« electric double-layer capacitors », soit supercondensateurs). L'espace des pores reconstruit est modélisé géométriquement à l'aide de la géométrie stochastique. Enfin, on a simulé les propriétés électriques des matériaux enutilisant des structures modélisées et simulées.The aim of the work presented here is to optimize nanoporous carbon materials by means of 'virtual material design'. On this length scale (~ 10nm) Focused Ion Beam – Scanning Electron Microscopy Nanotomography (FIB-SEM) is the only imaging technique providing three dimensional geometric information. Yet, for the optimization, the pore space of the materials must be reconstructed from the resulting image data, which was a generally unsolved problem so far.To overcome this problem, a simulation method for FIB-SEM images was developed. The resulting synthetic FIB-SEM images could then be used to test and validate segmentation algorithms. Using simulated image data, a new algorithm for the morphological segmentation of the highly porous structures from FIB-SEM data was developed, enabling the reconstruction of the three dimensional pore space from FIB-SEM images.Two case studies with nanoporous carbons used for energy storage are presented, using the new techniques for the characterization and optimization of electrodes of Li-ion batteries and electric double layer capacitors (EDLC's), respectively. The reconstructed pore space is modeled geometrically by means of stochastic geometry. Finally, the electrical properties of the materials were simulated using both imaged real and modeled structures

Characterization and modeling of nanoporous carbon structures

L'objectif de la thèse présentée ici est l'optimisation de matériaux carbonésnanoporeux au moyen de la “conception de matériaux virtuels”. En ce qui concerne cette échelle de travail (~ 10nm), la Nanotomographie FIB-SEM est la seule technique d'imagerie donnant accès à une information sur la géométrie tridimensionnelle. Cependant, pour l'optimisation du comportement, l'espace des pores doit être reconstruit à partir des données tirées des images obtenues. Jusqu'à présent ce problème n'était pas résolu. Pour pouvoir le maîtriser, on a développé une simulation d'images FIB-SEM. Les images FIB-SEM simulées peuvent être utilisées pour la vérification et la validation des algorithmes de segmentation. En utilisant les données d'image simulées, un nouvel algorithme pour la reconstruction de l'espace des pores à partir des données FIB-SEM a été développé.Deux études de cas avec des carbones nanoporeux utilisés pour le stockage d'énergie sont présentées, en utilisant les nouvelles techniques pour la caractérisation et l'optimisation des électrodes Li-ion de type EDLC'S (« electric double-layer capacitors », soit supercondensateurs). L'espace des pores reconstruit est modélisé géométriquement à l'aide de la géométrie stochastique. Enfin, on a simulé les propriétés électriques des matériaux enutilisant des structures modélisées et simulées.The aim of the work presented here is to optimize nanoporous carbon materials by means of 'virtual material design'. On this length scale (~ 10nm) Focused Ion Beam – Scanning Electron Microscopy Nanotomography (FIB-SEM) is the only imaging technique providing three dimensional geometric information. Yet, for the optimization, the pore space of the materials must be reconstructed from the resulting image data, which was a generally unsolved problem so far.To overcome this problem, a simulation method for FIB-SEM images was developed. The resulting synthetic FIB-SEM images could then be used to test and validate segmentation algorithms. Using simulated image data, a new algorithm for the morphological segmentation of the highly porous structures from FIB-SEM data was developed, enabling the reconstruction of the three dimensional pore space from FIB-SEM images.Two case studies with nanoporous carbons used for energy storage are presented, using the new techniques for the characterization and optimization of electrodes of Li-ion batteries and electric double layer capacitors (EDLC's), respectively. The reconstructed pore space is modeled geometrically by means of stochastic geometry. Finally, the electrical properties of the materials were simulated using both imaged real and modeled structures