For the development of a new porous material such as catalytic carrier, the control of the textural properties is of fundamental importance. In order to move towards rational synthesis, it is ...necessary to better understand the physical phenomena that generate a defined solid structure. A contribute to this purpose can be achieved by studying the aggregation process inside colloidal suspensions, leading to porosity generation: this phenomenon can be described with a Brownian dynamics model that, for any set of chemical parameters, gives access to the mass distribution and the fractal dimension of colloidal aggregates. However, this model cannot be used for the simulation of large colloidal systems, due to its high computational time, limiting comparison with analytical methods, which probe the whole multi-scale system. This problem is solved by developing a new aggregation morphological model, wherein the fractal dimension is tuned with two compactness parameters. An efficient simulation algorithm is proposed in case of spheres, for which the fractal dimension of the generated aggregates varies between 1.2 and 3. Brownian dynamics results are used to parametrize this purely geometric model, in order to constrain the size and the morphology of the aggregates created. The large numerical solid will be representative of the textural properties of a real solid and will give more information on the porous network. It could be used, for example, to simulate diffusive transport coupled with chemical reaction and to study the impact of the geometry of the porous system on the catalytic performance.
This paper addresses the numerical characterization of microstructures by the concept of tortuosity. After a brief review of geometric tortuosities, some definitions are considered for a benchmarking ...analysis. The focus is on the M-tortuosity definition, which is revised by expliciting the link to percolation theory, among other things. This operator fits with the analysis of real samples of materials whatever their complexity. A contribution of this paper is a new formulation of the M-tortuosity , making it generic to many situations. Additionally, the comparison of the various tortuosimetric descriptors, state-of-the-art definitions and M-tortuosity , is proposed by considering several scenarios thanks to stochastic multi-scale models of complex materials. The relationships with porosity, morphological heterogeneity and structural anisotropy are investigated. The results highlight the similarities and differences between the descriptors while attesting that the M-tortuosity is equivalent to the state-of-the-art definitions, for a potential use in diffusion and conductivity analyses. Moreover, the M-tortuosity handles correctly situations where state-of the-art algorithms fail. The anisotropic case highlights some limitations of the state-of-the-art definitions behaving differently according to the given propagation direction. In the case of unknown propagation and irregular piece of materials, the M-tortuosity provides a unique tortuosity value representative of the whole microstructure while detecting the anisotropy. These operators are freely available within the plug im! platform.
•The morphology of boehmite agglomerates depends on the pH of the colloidal suspension.•The boehmite agglomerate growth is simulated using population balance and morphological models.•Light ...scattering and Brownian dynamics enable the population balance adjustment.
The agglomeration dynamics within colloidal boehmite suspensions is crucial to understand the formation of a porous boehmite network during the manufacturing of γ-alumina catalyst carriers. Such carriers are frequently used in petroleum hydrotreating processes and must have specific textural characteristics. The method described in this work enables to model the three-dimensional morphology of colloidal agglomerates of boehmite for different conditions of pH in the colloidal mixture. These agglomerates are then used to generate a boehmite grain, whose textural properties can be numerically estimated. The coagulation kinetics has been studied with experimental Dynamic Light Scattering and Lagrangian model including Brownian dynamics and DLVO interaction potential. The adjustment of the Brownian aggregation kernel of a population-balance model enables to estimate the agglomerates size distribution and fractal dimension.
In this work we focus on further understanding reactive transport in carbonate rocks, in particular limestones characterized by a bimodal pore size distribution. To this end, we performed injection ...experiments with CO 2 -saturated water on a sample of Euville limestone and monitored the experiments with a medical CT scanner. Microscanner imaging was performed before and after alteration. Experiments showed that permeability increased by nearly two decades due to the alteration process. This increase could be attributed to the formation of a preferential dissolution path visualized on the CT images. Microscanner images show that preferential dissolution areas are characterized by the presence of numerous enlarged macropores. The preferential dissolution path created therefore retains a porous structure and does not correspond to a wormhole-type channel. To provide further knowledge of the small-scale physics of reactive transport, we performed Lattice-Boltzmann simulations of flow in a numerically generated model 2D porous medium having geometrical and topological features designed to approach Euville limestone. We showed that the fluid velocity increased in nearly percolating paths of macropores. Considering the experiments, this means that the CO 2 -saturated water starts to enter high-velocity zones earlier than low-velocity zones, inducing an earlier onset of the alteration process and a more pronounced local dissolution. However, numerical results showed that the alteration of non-connected macropores leads to an increase of permeability much smaller than the experimentally observed one. To explain this fact we used effective medium modelling that permits predicting the variation in permeability as a function of the fraction of macropores and consequently as a function of alteration. It proved that as long as there is no alteration-induced percolating path consisting of macropores, the increase in permeability is relatively low as shown by the Lattice-Boltzmann simulations. An increase in permeability of several orders of magnitude is only observed when the macroporosity is close to the percolation threshold. This fact is in accordance with the experimentally observed results.
Ancient geographical maps are our window into the past for understanding the spatial dynamics of last centuries. This paper proposes a novel approach to address this problem using deep learning. ...Convolutional neural networks (CNNs) are today the state-of-the-art methods in handling a variety of problems in the fields of image processing. The Cassini map, created in the eighteenth century, is used to illustrate our methodology. This approach enables us to extract the surfaces of classes of lands in the Cassini map: forests, heaths, arboricultural, and hydrological. The evolution of land use between the end of the eighteenth century andtoday was quantified by comparison with Corine Land Cover (CLC) database. For the Rhone watershed, the results show that forests, arboriculture, and heaths are more extensive on the CLC map, in contrast to the hydrological network. These unprecedented results are new findings that reveal the major anthropo-climatic changes.
Semantic segmentation allows us to identify several land use patterns from a cartographic support item such as the Cassini map.
Semantic segmentation reduces the analysis time of the map by a factor of approximately 10 compared with an entirely manual segmentation, while maintaining an average accuracy equivalent to 90%.
Our results illustrate a climatic and anthropic forcing on the Rhône watershed that significantly modified the landscape compared with today.
By employing multi-scale random models of c-alumina, we have studied the influence of porosity, grain aspect ratio and aggregation state on the effective diffusion coefficient. Multi-scale Boolean ...models of platelets were used to produce digital volumes reproducing the alumina porous space. Iterative fast Fourier transform numerical simulation of Fick's diffusion were performed on the volume to obtain the effective diffusion coefficient. The tortuosity factors of the various simulated models show a simple dependence with pore volume fraction with an exponent guided by the platelet aspect ratio and the aggregation state. Comparisons with proton pulsed-field gradient nuclear magnetic resonance spectrometry show a satisfactory agreement.
The bilateral filter plays a key role in image processing applications due to its intuitive parameterization and its high quality filter result, smoothing homogeneous regions while preserving the ...edges of the objects. Considering the image as a topological relief, seeing pixel intensities as peaks and valleys, we introduce a way to control the tonal weighting coefficients, the flowing bilateral filter, reducing "halo" artifacts typically produced by the regular bilateral filter around a large peak surrounded by two valleys of lower values. In this paper we propose to investigate exact and approximated versions of CPU and parallel GPU (Graphical Processing Unit) based implementations of the regular and flowing bilateral filter using the NVidia CUDA API. Fast implementations of these filters are important for the processing of large 3D volumes up to several GB acquired by x-ray or electron tomography.
Geometric tortuosity is one of the foremost topological characteristics of porous media. Despite the various definitions in the literature, to our knowledge, they are all linked to an arbitrary ...propagation direction. This article proposes a novel topological descriptor, named M-tortuosity, by giving a more straightforward definition, describing the data regardless of physicochemical processes. M-tortuosity, based on the concept of geometric tortuosity, is a scalable descriptor, meaning that information of several dimensions (scalar, histograms, 3D maps) is available. It is applicable on complex disconnected structures without any arbitrary definition of entry and exit. Topological information can be represented by aggregation into a unique scalar descriptor for classification purposes. It is extended by iterative erosions to take into account porous structure narrowness, especially bottleneck effects. This new descriptor, called M-tortuosity-by-iterative-erosions, describes tortuosity of the porous part as seen by a spherical particle of given size walking along the network. Boolean models are used to simulate different porous media structures in order to test the proposed characterization.
This paper addresses the characterization of spatial arrangements of fringes in catalysts imaged by High Resolution Transmission Electron Microscopy (HRTEM). It presents a statistical model-based ...approach for analyzing these fringes. The proposed approach involves Fractional Brownian Field (FBF) and 2-D AutoRegressive (AR) modeling, as well as morphological analysis. The originality of the approach consists in identifying the image background as an FBF, subtracting this background, modeling the residual by 2-D AR so as to capture fringe information and, finally, discriminating catalysts from fringe characterizations obtained by morphological analysis. The overall analysis is called ARFBF (Auto-Regressive Fractional Brownian Field) based morphology characterization.
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