Heterogeneous Flow Research Articles

Assessing U.S. County Sustainability: Accounting for Heterogeneous Human Capital Flows and Health Quality Within the Inclusive Wealth Framework

Assessing U.S. County Sustainability: Accounting for Heterogeneous Human Capital Flows and Health Quality Within the Inclusive Wealth Framework

Column flotation hydrodynamics operating in the heterogeneous regime estimated by electrical resistance tomography and multi-phase CFD model

ABSTRACT This paper investigates the two-phase flow hydrodynamics of a column flotation operated from a homogeneous to a heterogeneous flow regimes using experimental and computational fluid dynamics (CFD) techniques. Experiments were conducted in a lab scale column flotation of 0.1 m internal diameter and 2.5 m length at various superficial gas velocities using a dual plane electrical resistance tomography (ERT). The mean gas holdup increased from 2 to 18% with the increase in superficial gas velocity from 0.6 to 7.2 cm/s. The gas holdup-based bubble swarm velocity method identified four distinct flow regimes, i.e. homogeneous bubbling regime, narrow discrete bubbling regime, a sustained helical flow regime and churn turbulent flow regime in the column. Further, transient simulations were conducted using a two-fluid model coupled with a population balance model to assess the flow behavior inside the column. Virtual mass, lift and drag forces were incorporated into the model to account for the interphase forces. Numerical simulations predicted mean gas holdup was matching with the experimental data at low gas velocities (<2.4 cm/s), and a marginal deviation was noted at higher gas velocities (>2.4 cm/s). The predicted radial gas holdup profiles were found to change from flatter to parabolic with the increase in gas velocities, i.e. similar to the experiments. The effect of particle size on the rate constant and recovery was estimated with Luttrell and Yoon’s performance model using the particle floatability input data and the two-phase experimental data. The developed CFD model can be useful to optimize the operating and design parameters for efficient operation of the column flotation process.

Design and implementation of clinical care centres for spondyloarthritis. A benchmark care and disease model in chronic pathologies

IntroductionSpondyloarthritis (SpA) is a musculoskeletal disease presenting with phenotypic clinical manifestations, integrating a set of interrelated inflammatory conditions, which share immunogenetic, epidemiological, and therapeutic characteristics. ReflectionIn clinical practice, the reality of the care process in patients diagnosed with SpA represents an area of ​​opportunity in multiple aspects. The fragmentation of clinical care and the heterogeneous flow of the patient in the care pathway, are associated with suboptimal and undesired clinical outcomes. Several aspects highlight the reality of patients with SpA in the national scenario, which -to a certain extent- could reflect what is observed in other Latin American countries. SpA represents a very significant burden for society and for individuals affected by this condition. Comprehensive assessment of the burden of disease from the perspective of the clinician and the patient is important, in order to support decisions related to treatment and comprehensive management of this condition. The improvement in health outcomes and the reduction in the cost of chronic inflammatory diseases, such as SpA, are the main advantages of implementing a care model in specialized centres integrating a multidisciplinary team. ConclusionThis is an opportunity to include the perspective of individuals affected by this condition, seeking integration between an informed patient and a highly qualified multidisciplinary care team in the comprehensive management of patients with SpA.

Heterogeneous traffic flow of expressway with Level 2 autonomous vehicles considering moving bottlenecks

With the development of autonomous driving technology, autonomous vehicles (AV) will gradually replace human-driven vehicles (HDV), but it will still be a mixed traffic flow of autonomous vehicles with different levels of automation for a long time. In addition to cars, trucks regarded as moving bottleneck are also an important part of traffic flow of expressway. In this paper, the elimination rule of moving bottleneck is introduced into the traffic flow model, and the improved hybrid traffic flow cellular automata model is proposed. Next, through numerical simulation, the existence and influence of moving bottleneck caused by heavy duty trucks are hypothesized and verified. The simulation results show that with the proportion of trucks increases, the influence range of moving bottleneck expands, resulting in the decrease of capacity and traffic congestion. Then, the impact of Level 2 autonomous vehicles (hereinafter referred to as L2 AVs) on the traffic flow of moving bottlenecks is explored. The simulation results show that with the proportion of L2 AVs increases, traffic capacity increases, and traffic congestion ratio at medium and high density decreases. Under medium density, the average velocity fluctuates greatly, while under high density, the average velocity decreases due to limitation of density. In summary, L2 AVs can alleviate influence of moving bottlenecks, increase traffic capacity, improve traffic congestion, and lift road safety. The cellular automata model of traffic flow including moving bottleneck proposed in this paper is based on the actual road situation, considering the fact that most of autonomous vehicles on the expressway currently are L2 AVs, and moving bottleneck is mainly caused by heavy trucks. This research contributes to an in-depth analysis of L2 AVs on heterogeneous traffic flows under moving bottleneck environment.

Heterogeneous Mechanical Stress and Interstitial Fluid Flow Predictions Derived from DCE-MRI for Rat U251N Orthotopic Gliomas.

Mechanical stress and fluid flow influence glioma cell phenotype in vitro, but measuring these quantities in vivo continues to be challenging. The purpose of this study was to predict these quantities in vivo, thus providing insight into glioma physiology and potential mechanical biomarkers that may improve glioma detection, diagnosis, and treatment. Image-based finite element models of human U251N orthotopic glioma in athymic rats were developed to predict structural stress and interstitial flow in and around each animal's tumor. In addition to accounting for structural stress caused by tumor growth, our approach has the advantage of capturing fluid pressure-induced structural stress, which was informed by in vivo interstitial fluid pressure (IFP) measurements. Because gliomas and the brain are soft, elevated IFP contributed substantially to tumor structural stress, even inverting this stress from compressive to tensile in the most compliant cases. The combination of tumor growth and elevated IFP resulted in a concentration of structural stress near the tumor boundary where it has the greatest potential to influence cell proliferation and invasion. MRI-derived anatomical geometries and tissue property distributions resulted in heterogeneous interstitial fluid flow with local maxima near cerebrospinal fluid spaces, which may promote tumor invasion and hinder drug delivery. In addition, predicted structural stress and interstitial flow varied markedly between irradiated and radiation-naïve animals. Our modeling suggests that relative to tumors in stiffer tissues, gliomas experience unusual mechanical conditions with potentially important biological (e.g., proliferation and invasion) and clinical consequences (e.g., drug delivery and treatment monitoring).

Modeling cardiac microcirculation for the simulation of coronary flow and 3D myocardial perfusion.

Accurate modeling of blood dynamics in the coronary microcirculation is a crucial step toward the clinical application of in silico methods for the diagnosis of coronary artery disease. In this work, we present a new mathematical model of microcirculatory hemodynamics accounting for microvasculature compliance and cardiac contraction; we also present its application to a full simulation of hyperemic coronary blood flow and 3D myocardial perfusion in real clinical cases. Microvasculature hemodynamics is modeled with a compliant multi-compartment Darcy formulation, with the new compliance terms depending on the local intramyocardial pressure generated by cardiac contraction. Nonlinear analytical relationships for vessels distensibility are included based on experimental data, and all the parameters of the model are reformulated based on histologically relevant quantities, allowing a deeper model personalization. Phasic flow patterns of high arterial inflow in diastole and venous outflow in systole are obtained, with flow waveforms morphology and pressure distribution along the microcirculation reproduced in accordance with experimental and in vivo measures. Phasic diameter change for arterioles and capillaries is also obtained with relevant differences depending on the depth location. Coronary blood dynamics exhibits a disturbed flow at the systolic onset, while the obtained 3D perfusion maps reproduce the systolic impediment effect and show relevant regional and transmural heterogeneities in myocardial blood flow (MBF). The proposed model successfully reproduces microvasculature hemodynamics over the whole heartbeat and along the entire intramural vessels. Quantification of phasic flow patterns, diameter changes, regional and transmural heterogeneities in MBF represent key steps ahead in the direction of the predictive simulation of cardiac perfusion.

Evolution of pore-scale concentration PDFs and estimation of transverse dispersion from numerical porous media column experiments

Knowing local concentration distributions is important for transport and mixing, particularly in porous media, yet a comprehensive understanding of them remains a challenge. Computing advancements have enabled high-resolution pore-scale simulations, offering an unprecedented opportunity for in-depth investigation of mixing. In this study we use simulation data to examine concentration distributions at the pore scale in the context of longitudinal (pseudo-one-dimensional) solute transport through a porous column. These distributions arise in a single column from heterogeneous flow at the pore-scale, which gets averaged out when upscaled and are not with reference to statistics across multiple random realizations. To measure these distributions, we first devise a semi-analytical approach to estimate the mean effective transport velocity profile for a non-uniform Darcy-scale fluid velocity, which unavoidably occurs due to the presence of lateral boundaries. This development allows sampling micro-scale concentrations over a moving surface that possesses a well defined Darcy-scale mean concentration, enabling empirical computation of the local concentration distribution. As an added benefit we find that our approach allows for the estimation of transverse dispersion coefficients, which is not typical in traditional column experiments. The implemented approach can estimate it via inverse modeling, and it agrees closely with previously published experimental data across the range of Peclet numbers we studied. We found that the measured pore-scale concentration probability density functions are best represented by a beta distribution, thus validating this longstanding hypothesis with direct evidence. Furthermore, we propose a model to describe the temporal and spatial evolution of the local concentration pdf, as well as its Péclet number dependence.

Physics‐Informed Convolutional Decoder (PICD): A Novel Approach for Direct Inversion of Heterogeneous Subsurface Flow

AbstractWe propose a physics‐informed convolutional decoder (PICD) framework for inverse modeling of heterogenous groundwater flow. PICD stands out as a direct inversion method, eliminating the need for repeated forward model simulations. The framework combines data‐driven and physics‐driven approaches by integrating monitoring data and domain knowledge into the inversion process. PICD utilizes a convolutional decoder to effectively approximate the spatial distribution of hydraulic heads, while Karhunen–Loève expansion (KLE) is employed to parameterize hydraulic conductivities. During the training process, the stochastic vector in KLE and the parameters of the convolutional decoder are adjusted simultaneously to minimize the data‐mismatch and the physical violation. The final optimized stochastic vectors correspond to the estimation of hydraulic conductivities, and the trained convolutional decoder can predict the evolution and distribution of hydraulic heads. Various scenarios of groundwater flow are examined and results demonstrate the framework's capability to accurately estimate heterogeneous hydraulic conductivities and to deliver satisfactory predictions of hydraulic heads, even with sparse measurements.

A Heterogeneous Viscosity Flow Model for Liquid Transport through Nanopores Considering Pore Size and Wettability.

The confinement effect in micro- and nanopores gives rise to distinct flow characteristics in fluids. Clarifying the fluid migration pattern in confined space is crucial for understanding and explaining the abnormal flow phenomena in unconventional reservoirs. In this study, flow characteristics of water and oil in alumina nanochannels were investigated with diameters ranging from 21 nm to 120 nm, and a heterogeneous viscosity flow model considering boundary fluid was proposed. Compared with the prediction of the HP equation, both types of fluids exhibit significant flow suppression in nanochannels. As the channel size decreases, the deviation degree increases. The fluid viscosity of the boundary region displays an upward trend as the channel size decreases and the influence of the interaction between the liquid and solid walls intensifies. The thickness of the boundary region gradually decreases with increasing pressure and eventually reaches a stable value, which is primarily determined by the strength of the interaction between the liquid and solid surfaces. Both the pore size and wettability are essential factors that affect the fluid flow. When the space scale is extremely small, the impact of wettability becomes more pronounced. Finally, the application of the heterogeneous flow model for permeability evaluation has yielded favorable fitting results. The model is of great significance for studying the fluid flow behavior in unconventional reservoirs.

Large-eddy simulation of aerosol concentrations in a realistic urban environment: Model validation and transport mechanism

Air pollution in urban environments exhibits large spatial and temporal variations due to high heterogeneous air flow and emissions. To address the complexity of local air pollutant dynamics, a comprehensive large-eddy simulation using the PALM model system v6.0 was conducted. The distribution of flow and vehicle emitted aerosol particles in a realistic urban environment in Malmö, Sweden, was studied and evaluated against on-site measurements made using portable instrumentation on a spring morning in 2021. The canyon transport mechanisms were investigated, and the convective and turbulent mass-transport rates compared to clarify their role in aerosol transport. The horizontal distribution of aerosols showed acceptable evaluation metrics for both mass and number. Flow and pollutant concentrations were more complex than those in idealized street canyon networks. Vertical turbulent mass-transport rate was found to dominate the mass transport process compared with the convective transport rate, contributing more than 70% of the pollutant transport process. Our findings highlight the necessity of examining various aerosol metric due their distinct dispersion behaviour. This study introduces a comprehensive high-resolution modelling framework that accounts for dynamic meteorological and aerosol background boundary conditions, real-time traffic emission, and detailed building features, offering a robust toll for local urban air quality assessment.

Review article: Melt-affected ice cores for polar research in a warming world

Abstract. Melting polar and alpine ice sheets in response to global warming pose ecological and societal risks but will also hamper our ability to reconstruct past climate and atmospheric composition across the globe. Since polar ice caps are crucial environmental archives but highly sensitive to ongoing climate warming, the Arctic and Antarctic research community is increasingly faced with melt-affected ice cores, which are already common in alpine settings of the lower latitudes. Here, we review the characteristics and effects of near-surface melting on ice-core records, focusing on a polar readership and making recommendations for melt-prone study regions. This review first covers melt layer formation, identification and quantification of melt, and structural characteristics of melt features. Subsequently, it discusses effects of melting on records of chemical impurities, i.e. major ions, trace elements, black carbon, and organic species as well as stable water isotopic signatures, gas records, and applications of melt layers as environmental proxies. Melting occurs during positive surface energy balance events, which are shaped by global to local meteorological forcing, regional orography, glacier surface conditions and subsurface characteristics. Meltwater flow ranges from homogeneous wetting to spatially heterogeneous preferential flow paths and is determined by temperature, thermal conductivity and stratigraphy of the snowpack. Melt layers and lenses are the most common consequent features in ice cores and are usually recorded manually or using line scanning. Chemical ice-core proxy records of water-soluble species are generally less preserved than insoluble particles such as black carbon or mineral dust due to their strong elution behaviour during percolation. However, high solubility in ice as observed for ions like F−, Cl−, NH4+ or ultra-trace elements can counteract the high mobility of these species due to burial in the ice interior. Stable water isotope records like δ18O are often preserved but appear smoothed if significant amounts of meltwater are involved. Melt-affected ice cores are further faced with questions about the permeability of the firn column for gas movement, and gas concentrations can be increased through dissolution and in situ production. Noble gas ratios can be useful tools for identifying melt-affected profile sections in deep ice. Despite challenges for ice-core climate reconstruction based on chemical records, melt layers are a proxy of warm temperatures above freezing, which is most sensitive in the dry snow and percolation zone. Bringing together insights from snow physics, firn hydrology, and ice-core proxy research, we aim to foster a more comprehensive understanding of ice cores as climate and environmental archives, provide a reference on how to approach melt-affected records, and raise awareness of the limitations and potential of melt layers in ice cores.

Progressive virtual risk-based vehicle trajectory optimization in mixed traffic flow

Ramp-merging zones have perennially served as bottlenecks for both safety and efficiency within road traffic. Addressing the inherent uncertainties and anomalous behaviors potentially exhibited by human-driven vehicles (HDVs) in mixed traffic flow, this study introduced a distributed merging control algorithm based on virtual risk assessment. Initially, we proposed a progressive vehicle projection method based on matching degree, formulated to engender smooth longitudinal accelerations. Building upon this foundation, a virtual risk-based longitudinal planning model named V-RQM was established, furnishing longitudinal accelerations with robust stability and safety to Connected and Autonomous Vehicles (CAVs). Results from four diverse simulation experiments corroborate that V-RQM is aptly versatile, suited for conventional one-dimensional car-following environments as well as pre-merging control in heterogeneous traffic flow. The model not only mitigates oscillatory amplitudes while sustaining high traffic efficiency but also exhibits commendable resilience against uncertainties and anomalies indigenous to mixed traffic flow. This research pioneers a novel model-driven approach to ramp-merging control, setting the stage for the full exploitation of CAV capabilities.

Research on the generalization issue of the heterogeneous QC-EMMS drag model for gas-solid fluidization

In the circulating fluidized bed (CFB), the non-uniform mesoscale structure formed by the particle clustering effect causes a substantial decrease in the gas-solid drag. Since the degree of particle clustering varies with operating conditions, an accurate drag model needs to be universal in different heterogeneous flow conditions. In this study, the relationships between the Ψ factor in clusters' solid holdup model that characterizes the flow non-uniformity and the operating parameters of CFB (including slip velocity Reynolds number, Re*, bed-averaged solid volume fraction, εs,bed, and solid mass circulation rate, Gs) are established. It improves the adaptability of the QC-EMMS drag model under different working conditions. In previous research, we established two types of models that related Ψ factor to Re* and εs,bed respectively. However, there exists a problem of high dispersion of points, indicating that the selected parameters cannot fully describe the flow non-uniformity. Therefore, Gs is reintroduced to modify the two types of models. The results show that the prediction accuracy of the modified models is improved and the relative error is <10%, indicating that the non-uniform factor Ψ has a strong correlation with Gs. In addition, the quantitative relation between Re*, εs,bed, and Gs is derived from modified models, and the trend of relation is highly consistent with the fluidization diagram proposed by Yerushalmi J., which verifies the accuracy of modified models. Finally, numerical simulation of typical CFB cases proves the adaptability of the modified models in wide operating conditions of fluidization.

Three-dimensional geological modeling applied to multiscale heterogeneity of a reservoir analog: Paleocoastal deposits from the Rio Bonito formation, Paraná Basin

Coastal sandstones have high permoporosity and contain significant hydrocarbon reserves, although they present variable flow heterogeneities. The goal of this paper is to understand the distribution of potential reservoir-flow units in the Rio Bonito Formation (early Permian, Paraná Basin) and to investigate heterogeneities on multiscale. We use stratigraphic, sedimentological, 3D model, and petrological data to evaluate reservoir heterogeneities. System tracts were modeled by sectioning the entire succession into five zones. Eleven facies associations were modeled separately within each zone, using geostatistical analysis and different algorithms. The 3D model was validated by jackknife procedure, and the distribution of facies associations adequately represented both depositional and stratigraphic frameworks. The results are adequate in a curve of accommodation changes similar to previous proposal for the study area. Tidal sand bar facies association presents as elongated (parallel to depositional dip) to sheetlike geobodies according to amalgamation grade, while upper and middle shoreface one is mostly elongated (parallel to depositional strike) to sheetlike. Besides, fluvial channel facies association occurs mainly elongated parallel to depositional dip, forming multilateral and multistory geobodies. Modeled depositional geometries were distinguished along the succession, showing similarities to Rio Bonito Formation outcrops, recent environments, and other deposits around the world, such as estuarine strata from Oriente Basin and shoreface ones from Gulf of Mexico Basin. Using a detailed petrological analysis, eleven reservoir petrofacies were defined and classified into good-, medium-, and low-quality reservoirs or non-reservoirs. Tidal sand bar, upper-middle shoreface, and fluvial channel deposits were categorized as the main reservoir-flow units. This study provides predictive scenarios for heterogeneities in reservoirs and may be applied in petroleum fields.

Protein homeostasis maintained by HOOK1 levels promotes the tumorigenic and stemness properties of ovarian cancer cells through reticulum stress and autophagy

BackgroundOvarian cancer has a high mortality rate mainly due to its resistance to currently used therapies. This resistance has been associated with the presence of cancer stem cells (CSCs), interactions with the microenvironment, and intratumoral heterogeneity. Therefore, the search for new therapeutic targets, particularly those targeting CSCs, is important for improving patient prognosis. HOOK1 has been found to be transcriptionally altered in a substantial percentage of ovarian tumors, but its role in tumor initiation and development is still not fully understood.MethodsThe downregulation of HOOK1 was performed in ovarian cancer cell lines using CRISPR/Cas9 technology, followed by growth in vitro and in vivo assays. Subsequently, migration (Boyden chamber), cell death (Western-Blot and flow cytometry) and stemness properties (clonal heterogeneity analysis, tumorspheres assay and flow cytometry) of the downregulated cell lines were analysed. To gain insights into the specific mechanisms of action of HOOK1 in ovarian cancer, a proteomic analysis was performed, followed by Western-blot and cytotoxicity assays to confirm the results found within the mass spectrometry. Immunofluorescence staining, Western-blotting and flow cytometry were also employed to finish uncovering the role of HOOK1 in ovarian cancer.ResultsIn this study, we observed that reducing the levels of HOOK1 in ovarian cancer cells reduced in vitro growth and migration and prevented tumor formation in vivo. Furthermore, HOOK1 reduction led to a decrease in stem-like capabilities in these cells, which, however, did not seem related to the expression of genes traditionally associated with this phenotype. A proteome study, along with other analysis, showed that the downregulation of HOOK1 also induced an increase in endoplasmic reticulum stress levels in these cells. Finally, the decrease in stem-like properties observed in cells with downregulated HOOK1 could be explained by an increase in cell death in the CSC population within the culture due to endoplasmic reticulum stress by the unfolded protein response.ConclusionHOOK1 contributes to maintaining the tumorigenic and stemness properties of ovarian cancer cells by preserving protein homeostasis and could be considered an alternative therapeutic target, especially in combination with inducers of endoplasmic reticulum or proteotoxic stress such as proteasome inhibitors.

Shenfu injection alleviate gut ischemia/reperfusion injury after severe hemorrhagic shock through improving intestinal microcirculation in rats

BackgroundShenfu (SF) injection, a traditional Chinese medication, would improve microcirculation in cardiogenic shock and infectious shock. This study was aimed to explore the therapeutic potential of the SF injection in gut ischemia-reperfusion (I/R) injury after severe hemorrhagic shock (SHS) and resuscitation. Furthermore, we also investigated the optimal adm？ inistration timing. MethodsTwenty-four male SD rats were randomly divided into four groups: Sham group (sham, n = 6), Control group (n = 6), SF injection group (SF, n = 6), and Delayed Shenfu injection administration group (SF-delay, n = 6). In SHS and resuscitation model, rats were induced by blood draw to a mean arterial pressure (MAP) of 40 ± 5 mmHg within 1 h and then maintained for 40 min; HR, MAP ‘were recorded, microcirculation index [De Backer score, perfused small vessel density (PSVD), total vessel density (TVD), microcirculation flow index score (MFI), flow heterogeneity index (HI)] were analyzed. The blood gas index was detected, interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), diamine oxidase (DAO), malondialdehyde (MDA) were measured by ELISA; ZO-1, and claudin-1 were measured by Western blotting. In addition, hematoxylin-eosin (HE) and periodic acid schiff (PAS) staining pathological sections of the intestinal mucosal tissues were also performed. ResultsSF injection increased the MAP, relieved the metabolic acidosis degree associated with the hypoperfusion, and improved the intestinal microcirculatory density and perfusion quality after I/R injury. The expression of DAO, MDA in intestinal tissue, and plasma IL-6, TNF-α significantly decreased in the SF injection group compared to the control group. The concentration of ZO-1 and claudin-1 is also higher in the SF injection group. In addition, the HE and PAS staining results also showed that SF injection could decrease mucosal damage and maintain the structure. In the SF-delay group, the degree of intestinal tissue damage was intermediate between that of the control group and SF injection group. ConclusionsSF injection protect the intestine from I/R injury induced by SHS and resuscitation, the mechanism of which might be through improving intestinal microcirculation, reducing the excessive release of inflammatory factors and increasing intestinal mucosal permeability. Furthermore, the protection effect is more pronounced if administration during the initial resuscitation phase.

Impact of Aggressive HGV Platoons and Human-Driven Heavy Goods Vehicles on Signalized Intersections Performance

This paper presents a study on the performance and environmental impacts of aggressive heavy goods vehicle (HGV) platoons in comparison to human-driven HGVs at a random signalized intersection under varying traffic volumes between 500 and 1500 HGVs. A total of 12 scenarios have been developed, 6 for each of the vehicular behaviors, to quantify the emissions (CO, NOX, VOC) and fuel consumption, travel time, and delays. The analysis is implemented using the PTV VISSIM microscopic traffic flow model. Realization that the majority of the differences in the performance of the two vehicular controls seems to be different as the traffic volume increases was the realization. In most cases, aggressive HGV platoons were found to have lower emissions, in comparison to fuel consumption, while the flow and delay of aggressive HGV platoons were comparatively better against the case with human-driven HGVs. The results have thus provided new avenues for the incorporation of aggressive HGV platoons into urban traffic systems, more so in scenarios that involve a high level of traffic at intersections, as a potentially effective tool for augmenting the efficiency of an intersection and cutting down its environmental impacts. The present study strongly recommends the advancement of traffic management strategies that can capture the dynamics between the two heterogenous traffic flows induced by autonomous and semi-autonomous vehicle technologies.

Turbulent flow characteristics over rough permeable and impermeable gravel-bed stream- an experimental study

Abstract The study aims to presents flow heterogeneity over rough permeable and impermeable gravel-bed stream. The rough permeable stream is prepared by laying multiple layers of gravel, whereas its impermeable counterpart is presented by a resin-casted gravel-bed. In general, a common approach can be found in literature to mimic an impermeable bed by laying single layer of gravels, therefore some results are compared with single layer gravel-bed stream keeping the hydraulic conditions same. An acoustic Doppler velocimeter was used for flow measurements whereas; double averaging (DA) methodology was adopted for data analysis. The larger flow penetration depth and intense flow mixing in permeable gravel-bed infer sufficient impetus for organized flow turbulence and damping of DA Reynolds shear stresses whereas; the wall-blocking in resin-casted gravel-bed prevents fluid infiltration which leads to follow the linear stress profile away from the crest level. The damping of DA Reynolds shear stress (RSS) is compensated by enhanced DA form-induced shear stress (FISS). The results are further analysed under the light of the energy budget to characterize the mass-momentum exchange as it penetrates the subsurface layers. The energy budget indicates negative pressure energy diffusion rates corroborating gain in turbulence production in the permeable gravel-bed stream.

Computational fluid dynamics modelling of large-scale bubble columns: from the mono-dispersed to the pure heterogeneous flow regime

This study proposes a CFD model to simulate large-scale bubble columns operating in different flow regimes. Transient 3-D simulations were performed employing a commercial code (ANSYS Fluent), and the numerical results were compared with available experimental data. The superficial gas velocity ranges between 0.0037 m/s and 0.2 m/s, covering both the mono-dispersed and pure-heterogenous flow regimes, where bubbles coalescence and breakup were modelled. The results have been critically analysed, and the discrepancies between the numerical and experimental results have been deeply commented on, setting the stage for future improvements.

The diaspora model for human migration.

Migration's impact spans various social dimensions, including demography, sustainability, politics, economy, and gender disparities. Yet, the decision-making process behind migrants choosing their destination remains elusive. Existing models primarily rely on population size and travel distance to explain the spatial patterns of migration flows, overlooking significant population heterogeneities. Paradoxically, migrants often travel long distances and to smaller destinations if their diaspora is present in those locations. To address this gap, we propose the diaspora model of migration, incorporating intensity (the number of people moving to a country), and assortativity (the destination within the country). Our model considers only the existing diaspora sizes in the destination country, influencing the probability of migrants selecting a specific residence. Despite its simplicity, our model accurately reproduces the observed stable flow and distribution of migration in Austria (postal code level) and US metropolitan areas, yielding precise estimates of migrant inflow at various geographic scales. Given the increase in international migrations, this study enlightens our understanding of migration flow heterogeneities, helping design more inclusive, integrated cities.