269 research outputs found
New climate-control units for more energy-efficient Electric Vehicles: The innovative Three-Fluids Combined Membrane Contactor
No full textThis paper describes the work in progress in the XERIC project, funded within the Horizon 2020 EU program, which is aimed at building and testing a new climate-control system. The latter integrates a vapour compression cycle with a liquid desiccant cycle to increase Battery Electric Vehicles autonomy thanks to its increased energy efficiency. The modeling activity carried out on the design of an innovative Three-Fluids Combined Membrane Contactor (3F-CMC) and on the development of a lumped-parameters model to predict the 3F-CMC performance is described. The physical assumptions considered in the lumped-parameters model are presented. Results of 2D and 3D numerical heat and mass transfer simulations are used to get input data for the lumped code. The effect of air spacer design on the overall component performance is presented
3D-CFD analysis of the effect of cooling via minitubes on the performance of a three-fluid combined membrane contactor
No full textA 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
Review: Doing educational research : a guide for first time researchers
No full textTitle: Doing Educational Research : a guide for first time researchers
Author/Editor: Clive Opie
Publisher: Sage Publications
Publication Date: 2004
ISBN: Paperback 0761970029
Price: £18.99
Reviewed by: Torben Steeg, Independent D&T Consultan
Visual Author-ship: Creativity and Intentionality in Media
No full textBook review of Torben Grodal (ed.): Visual Author-ship: Creativity and Intentionality in Media Northern Lights, vol. 3, 2004, Museum Tusculanum Press/University of Copenhage
Identification of Channeling in Pore‐Scale Flows
No full textWe 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]
Charakterisierung und Modellierung nanoporöser Kohlenstoffstrukturen
No full textThe 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
Caractérisation et modélisation de structures carbonées nanoporeuses
No full textThe 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
Caractérisation et modélisation de structures carbonées nanoporeuses
No full textThe 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
Characterization and modeling of nanoporous carbon structures
No full textThe aim of the work presented here is to optimize nanoporous carbon materials by means of 'virtual material design'. On this length scale (ca. 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. In the first part of the thesis, a novel simulation program for FIB-SEM nanotomography is described. The program can, for the first time, generate completely artificial FIB-SEM tomographic images of highly porous materials, described by Boolean models of spheres or cylinders. The computation of which, using standard methods, would have taken weeks, even on high-performance machines. To this end, new acceleration techniques were developed and combined with existing techniques, reducing the simulation time by several orders of magnitude, without loss of physical accuracy. Results of simulated FIB-SEM nanotomograms of highly complex structures are presented, consisting of more than one hundred 2D images. In the second part, a new segmentation algorithm for FIB-SEM data is presented, enabling the reconstruction of the three-dimensional structure of highly porous materials, imaged by FIB-SEM nanotomography. The new method uses mathematical morphology, and is shown to be the best performing documented in literature so far. For the first time, simulated FIB-SEM data has been used to verify the correctness of the new method. In two case studies, the geometric structure of a nanoporous additive for Li-ion battery electrodes and nanoporous carbon electrodes for electric double layer capacitors (EDLC's) are reconstructed. The optimization of porous materials requires virtual representations of their pore space. This is achieved by using models from stochastic geometry, as described in the third part of the thesis. Virtual models are described, representing the nanoporous additive as well as the EDLC electrodes. The additive is modeled by level sets of a Gaussian random field, while for the EDLC electrodes a modified version of the Boolean model of spheres has been used. The modified Boolean model has been fitted to the observed structure by means of simulating realizations of the model and minimizing a similarity measure using stochastic optimization. The models, fitted to the reconstructed pore spaces of both materials, show good agreement. In the final part of the thesis, electrical properties of the electrodes made from the nanoporous carbons are predicted using physical simulations. For Lithium-Ion batteries, the in influence of the nanoporous carbon on the charging behavior is investigated using simulations. A multi-scale model is employed using the segmented FIB-SEM and synchrotron radiation computed tomography data. This establishes for the first time a multi-scale process for simulations, combining both experimental techniques. The additive is homogenized on the nanoscale and inserted as an effective medium into the microscale electrode. It is found, that the additive has a non negligible in influence on the charging behavior. Multi-scale simulations are also used to investigate the electrical behavior of nanoporous carbon electrodes for EDLC's. To this end, the effective resistivities and capacitances of the electrodes are computed using the segmented FIB-SEM data sets. Then, a macro- homogeneous model is fitted to a measured electric impedance spectrum of one of the samples, using the computed effective properties. Finally, the microscale simulations are performed on model realizations with a given parameter range. This enables us to optimize the resistance and the capacitance of the electrode
Characterization and modeling of nanoporous carbon structures
No full textL'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
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