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Bioethanol is mixed with gasoline according to many countries' legislation pursuing environmental sustainability by reducing the use of fossil fuels. Bioethanol is produced by fermentation of many organic waste or biomass resources in diluted aqueous media. Unfortunately, bioethanol for fuel use must have a low content of water and its recovery is an energy intensive operation. Heterogeneous azeotropic distillation (HAD) is a well-known suitable option for dehydration of alcohols, e.g. ethanol. Many entrainers for this process are studied in literature and, in this study, is checked and verified that gasoline and gasoline additives present the lowest energy consumption. For this purpose, novel processes are proposed and rigorously simulated using AspenPlus® to verify their performance with respect to conventional processes used currently. Based on the simulation results, the processes are then compared in terms of environmental impact (expressed by the Potential Environmental Impact (PEI) index) and economic cost. Ethanol dehydration is a non-spontaneous process that requires energy to be accomplished and, on the other hand, mixing ethanol with gasoline and additives is a spontaneous process. Combining both processes in synergy in a single unit, energy consumption decreases by 50% and Potential Environmental Impact by 80%. Finally, the economic study indicated the benefits of employing the novel proposed scheme of one distillation column as CAPEX is reduced by 20% and the payback time to 1.5 years. Therefore, a novel viable process is proposed that greatly reduces the environmental impact of nowadays gasoline production.

Bioethanol is mixed with gasoline according to many countries' legislation pursuing environmental sustainability by reducing the use of fossil fuels. Bioethanol is produced by fermentation of many organic waste or biomass resources in diluted aqueous media. Unfortunately, bioethanol for fuel use must have a low content of water and its recovery is an energy intensive operation. Heterogeneous azeotropic distillation (HAD) is a well-known suitable option for dehydration of alcohols, e.g. ethanol. Many entrainers for this process are studied in literature and, in this study, is checked and verified that gasoline and gasoline additives present the lowest energy consumption. For this purpose, novel processes are proposed and rigorously simulated using AspenPlus® to verify their performance with respect to conventional processes used currently. Based on the simulation results, the processes are then compared in terms of environmental impact (expressed by the Potential Environmental Impact (PEI) index) and economic cost. Ethanol dehydration is a non-spontaneous process that requires energy to be accomplished and, on the other hand, mixing ethanol with gasoline and additives is a spontaneous process. Combining both processes in synergy in a single unit, energy consumption decreases by 50% and Potential Environmental Impact by 80%. Finally, the economic study indicated the benefits of employing the novel proposed scheme of one distillation column as CAPEX is reduced by 20% and the payback time to 1.5 years. Therefore, a novel viable process is proposed that greatly reduces the environmental impact of nowadays gasoline production.

Finding a numerical method to model solute transport in porous media with high heterogeneity is crucial, especially when chemical reactions are involved. The phase space formulation termed the multi-advective water mixing approach (MAWMA) was proposed to address this issue. The water parcel method (WP) may be obtained by discretizing MAWMA in space, time, and velocity. WP needs two transition matrices of velocity to reproduce advection (Markovian in space) and mixing (Markovian in time), separately. The matrices express the transition probability of water instead of individual solute concentration. This entails a change in concept, since the entire transport phenomenon is defined by the water phase. Concentration is reduced to a chemical attribute. The water transition matrix is obtained and is demonstrated to be constant in time. Moreover, the WP method is compared with the classic random walk method (RW) in a high heterogeneous domain. Results show that the WP adequately reproduces advection and dispersion, but overestimates mixing because mixing is a sub-velocity phase process. The WP method must, therefore, be extended to take into account incomplete mixing within velocity classes. ; This research was funded by MICINN (Spanish government) through MEDISTRAES project II and III (grant numbers CGL2013-48869-C2-2-R and PID2019-110212RB-C22). J.S.-S. wishes to acknowledge the financial support from the AGAUR (Generalitat de Catalunya, Spain) through the "Grant for universities and research centers for the recruitment of new research personnel (FI-DGR 2013)". IDAEA-CSIC is a Centre of Excellence Severo Ochoa (Spanish Ministry of Science and Innovation, Project CEX2018-000794-S). ; Peer reviewed

Methods of direct and indirect assessment of the quality of mixing dispersed solid-phase components in a liquid polymer binder are considered. It is shown that a number of methods for the quantitative estimation of mixing (associated with the extraction of solid-phase components), which have been developed in other areas of the technology of materials, are not suitable for controlling an energy-saturated heterogeneous composite material (EHCM). An experimental method revealed the criteria values (a range) of the EHCM density and determined the main groups of the EHCM characteristics, ensuring their acceptable operational properties. By means of modern research equipment using proven methods, a series of studies was carried out to establish the uniformity of the distribution of particles of solid-phase components in the EHCM, the presence, the shape, sizes and distribution in the volume of defects in the structure of the material, the physicomechanical properties of the EHCM after polymerization. According to a comparison of the results of instrumental determination of the main characteristics of the EHCM (structural, physical) with the operational properties of the material, depending on the duration of the mixing process on a specific equipment under otherwise equal conditions, it was found that for the successful solution of technological tasks it is acceptable to assess indirectly the quality of mixing according to the results of density determination of the EHCM after its polymerization. This can provide operational output quality control of the final product that does not require significant material and time costs during the development of technological processes and during the production of the EHCM.

Assortative mixing in networks is the tendency for nodes with the same attributes, or metadata, to link to each other. It is a property often found in social networks, manifesting as a higher tendency of links occurring between people of the same age, race, or political belief. Quantifying the level of assortativity or disassortativity (the preference of linking to nodes with different attributes) can shed light on the organization of complex networks. It is common practice to measure the level of assortativity according to the assortativity coefficient, or modularity in the case of categorical metadata. This global value is the average level of assortativity across the network and may not be a representative statistic when mixing patterns are heterogeneous. For example, a social network spanning the globe may exhibit local differences in mixing patterns as a consequence of differences in cultural norms. Here, we introduce an approach to localize this global measure so that we can describe the assortativity, across multiple scales, at the node level. Consequently, we are able to capture and qualitatively evaluate the distribution of mixing patterns in the network. We find that, for many real-world networks, the distribution of assortativity is skewed, overdispersed, and multimodal. Our method provides a clearer lens through which we can more closely examine mixing patterns in networks.

Assortative mixing in networks is the tendency for nodes with the same attributes, or metadata, to link to each other. It is a property often found in social networks manifesting as a higher tendency of links occurring between people with the same age, race, or political belief. Quantifying the level of assortativity or disassortativity (the preference of linking to nodes with different attributes) can shed light on the factors involved in the formation of links and contagion processes in complex networks. It is common practice to measure the level of assortativity according to the assortativity coefficient, or modularity in the case of discrete-valued metadata. This global value is the average level of assortativity across the network and may not be a representative statistic when mixing patterns are heterogeneous. For example, a social network spanning the globe may exhibit local differences in mixing patterns as a consequence of differences in cultural norms. Here, we introduce an approach to localise this global measure so that we can describe the assortativity, across multiple scales, at the node level. Consequently we are able to capture and qualitatively evaluate the distribution of mixing patterns in the network. We find that for many real-world networks the distribution of assortativity is skewed, overdispersed and multimodal. Our method provides a clearer lens through which we can more closely examine mixing patterns in networks.

Assortative mixing in networks is the tendency for nodes with thesame attributes, or metadata, to link to each other. It is a propertyoften found in social networks, manifesting as a higher tendencyof links occurring between people of the same age, race, or politi-cal belief. Quantifying the level of assortativity or disassortativity(the preference of linking to nodes with different attributes) canshed light on the organization of complex networks. It is com-mon practice to measure the level of assortativity according tothe assortativity coefficient, or modularity in the case of categori-cal metadata. This global value is the average level of assortativityacross the network and may not be a representative statistic whenmixing patterns are heterogeneous. For example, a social networkspanning the globe may exhibit local differences in mixing pat-terns as a consequence of differences in cultural norms. Here, weintroduce an approach to localize this global measure so that wecan describe the assortativity, across multiple scales, at the nodelevel. Consequently, we are able to capture and qualitatively eval-uate the distribution of mixing patterns in the network. We findthat, for many real-world networks, the distribution of assorta-tivity is skewed, overdispersed, and multimodal. Our method pro-vides a clearer lens through which we can more closely examinemixing patterns in networks.

Assortative mixing in networks is the tendency for nodes with thesame attributes, or metadata, to link to each other. It is a propertyoften found in social networks, manifesting as a higher tendencyof links occurring between people of the same age, race, or politi-cal belief. Quantifying the level of assortativity or disassortativity(the preference of linking to nodes with different attributes) canshed light on the organization of complex networks. It is com-mon practice to measure the level of assortativity according tothe assortativity coefficient, or modularity in the case of categori-cal metadata. This global value is the average level of assortativityacross the network and may not be a representative statistic whenmixing patterns are heterogeneous. For example, a social networkspanning the globe may exhibit local differences in mixing pat-terns as a consequence of differences in cultural norms. Here, weintroduce an approach to localize this global measure so that wecan describe the assortativity, across multiple scales, at the nodelevel. Consequently, we are able to capture and qualitatively eval-uate the distribution of mixing patterns in the network. We findthat, for many real-world networks, the distribution of assorta-tivity is skewed, overdispersed, and multimodal. Our method pro-vides a clearer lens through which we can more closely examinemixing patterns in networks.

The article considers one of the approaches to modeling the process of mixing of polydisperse powders, which includes three main fractions of different sizes, the shape of which is close to spherical. The work is aimed at reducing material costs at the stage of development of mixing processes by reducing the number of experiments. Aiming to obtain the most uniform mixing with the minimum time of the technological process, the model is based on the target function for a certain number of iterations of mixing of the composition to obtain the required (maximum possible) density of the package of mixed solid particles.To develop a model of the mixing process, one of the heuristic algorithms – the "metal annealing method" – was used. As a representative element of the model, an elementary cell in the form of several hexagonal densely. Packed particles around one introduced into the composition of the composite material (in a small amount, from 5 to 15 %) as a modifier was adopted. The mo del is formalized with the condition of averaging the particle sizes within each fraction, as well as the morphology of their surface. The number of particle repackaging iterations is calculated by the probability of obtaining the minimum amount of voids in the representative element and the uniformity of distribution of the modifying element.Comparison of the values obtained during the simulation with the measured values of the mixing results on a specific mixer will form a scale of compliance of the simulation results with the operating modes of the process equipment. This will make it possible to predict the appropriate mixing modes at the stage of development of the technological process with the possible system of fluctuations in the characteristics of the supplied raw materials and, thereby, to create a methodological basis for the formation of quality management of manufacturing heterogeneous composite material. The model can be adapted for polydisperse powders with the content of the main fractions of more than three.

Geological heterogeneity enhances spreading of solutes and causes transport to be anomalous (i.e., non-Fickian), with much less mixing than suggested by dispersion. This implies that modeling transport requires adopting either stochastic approaches that model heterogeneity explicitly or effective transport formulations that acknowledge the effects of heterogeneity. A number of such formulations have been developed and tested as upscaled representations of enhanced spreading. However, their ability to represent mixing has not been formally tested, which is required for proper reproduction of chemical reactions and which motivates our work. We propose that, for an effective transport formulation to be considered a valid representation of transport through heterogeneous porous media (HPM), it should honor mean advection, mixing and spreading. It should also be flexible enough to be applicable to real problems. We test the capacity of the multi-rate mass transfer (MRMT) model to reproduce mixing observed in HPM, as represented by the classical multi-Gaussian log-permeability field with a Gaussian correlation pattern. Non-dispersive mixing comes from heterogeneity structures in the concentration fields that are not captured by macrodispersion. These fine structures limit mixing initially, but eventually enhance it. Numerical results show that, relative to HPM, MRMT models display a much stronger memory of initial conditions on mixing than on dispersion because of the sensitivity of the mixing state to the actual values of concentration. Because MRMT does not restitute the local concentration structures, it induces smaller non-dispersive mixing than HPM. However long-lived trapping in the immobile zones may sustain the deviation from dispersive mixing over much longer times. While spreading can be well captured by MRMT models, in general non-dispersive mixing cannot. © Author(s) 2016. ; The European Union is acknowledged for its funding through the Marie-Curie Fellowship PIEF-GA-2009-251710 and through the project FP7-ENERGY-2012-1-2STAGE TRUST (High-resolution monitoring, real time visualization and reliable modeling of highly controlled, intermediate and upscalable size pilot injection tests of underground storage of CO2). The ANR is acknowledged for its funding through its Project H2MNO4 under the No. ANR-12-MONU-0012-01. ; Peer reviewed

Many disadvantaged neighbourhoods increasingly face pressures from globalization, modernization and individualization, which have arguably helped to accelerate a decline in local-level social cohesion and social maintenance mechanisms. Many governmental officials, politicians and community development workers consider community development a tool for improving mutual solidarity and social maintenance, leading to improved social cohesion, liveability and safety in these neighbourhoods. Today, 'mixing' strategies are popular tools for linking residents with a different ethnic and/or class background. The assumption is that once people are enabled to mingle, bridging social capital will develop easily. However, in practice, contact between heterogeneous groups and individual residents does not develop spontaneously. Once positive encounters take place, this may lead to the development of mutual trust, which is crucial for the development of successful citizens' initiatives in the Netherlands and elsewhere, a process worthy of more attention from professionals and researchers. © Oxford University Press and Community Development Journal. 2011. All rights reserved.