Description Of Flow Research Articles

The Analysis of the National Health Accounts in the Republic of Moldova

This article contains the data of the national health accounts in the Republic of Moldova in the period 2010-2021. The system of the national health accounts is a tool for evaluating and monitoring the health system, as well as, in the analysis phase, of the importance of the health expenditures from the perspective of the economy consumption. The national health accounts provide a systematic description of the financial flows related to the health goods and services consumption. The purpose of this paper is to improve the performance of the health system from the perspective of the author’s analysis of the recent data of the national health accounts in the Republic of Moldova, namely, the indicators of their level, dynamics and structure, in order to highlight the health expenditure evolution trends.

Approximate Inference of Traffic Flow State at Signalized Intersections Using a Bayesian Learning Framework

Model-based traffic state estimation is used to reproduce traffic flow states from available observation data to assist traffic control and management. Owing to temporal and spatial observation limitations, numerous unknown traffic states and parameters exist in a nonlinear traffic flow model. These cannot be accurately estimated using filter methods with unavoidable parametric assumptions. In addition, the difficulty of estimation increases owing to an increased number of diverse traffic flow states and more unfavorable observation conditions at signalized intersections compared with those on the freeway. To overcome these problems, in this study, we developed switching state–space models to approximate the description of dynamic traffic flows at signalized intersections. By setting the traffic flow rate at the upstream and downstream boundaries of the road as observation data, we constructed a Bayesian learning framework in which all unknown variables in the models can be learned from the observed data. Finally, the utility of our method is demonstrated with the synthetic and the real NGSIM data. The result demonstrated that the proposed method could perform reasonably well in estimating the traffic flow dynamic process and states at signalized intersections, and could constitute an efficient scheme that avoids critical dependence on parametric calibrations and assumptions.

A Comprehensive Review of the Oil Flow Mechanism and Numerical Simulations in Shale Oil Reservoirs

The pore structure of shale oil reservoirs is complex, and the microscale and nanoscale effect is obvious in the development of shale oil reservoirs. Understanding the oil flow mechanism in shale reservoirs is essential for optimizing the development plan and enhancing the recovery rate of shale oil reservoirs. In this review, we briefly introduce the occurrence status of shale oil and shale oil flow in the inorganic matrix and the organic matrix (including the shrinkage of kerogen, oil diffusion in kerogen, oil transport in the organic pore channels, coupling of diffusion, and fluid transport in the organic matrix). Then, the shale oil microflow simulation and a coupling model of double-porous media for microflow and macroflow in the production process of shale oil are discussed. Finally, we summarize the main conclusions and perspectives on the oil flow mechanism and numerical simulations in shale oil reservoirs. An accurate description of shale oil occurrence status and shale oil flow in the inorganic and organic matrices is crucial for the numerical simulation of shale oil reservoirs. It can provide a basis and reference for the future directions of shale oil flow and numerical simulations during the development of shale oil reservoirs.

A process model representation of the end-of-life phase of a product in a circular economy to identify standards needs

The development of secondary sources as industrial feedstocks is important to creating resilient supply chains that contribute towards diverting resources away from landfills, mitigating deleterious environmental impacts, and minimizing market volatility. A major challenge to develop secondary feedstocks is the coordination and digitalization of the large quantities of generated information at each phase of a product’s life cycle. This paper builds upon earlier work that illustrates a top-level model of the activities and information needs to integrate product manufacturing with circular practices. This paper extends the initial work to explore the cyclical nature of Circular Economy (CE) information flows specifically related to product End-of-life. Using the Integrated Definition 0, IDEF0, modeling technique this paper examines the End-of-life function envisioned under a CE manufacturing model [ISO, 2012]. This function is decomposed into subsequent child functions and is analyzed relative to other product life cycle phases. The paper reviews the current global product EoL practices and in the context of the developed IDEF0 model. The proposed framework contributes a detailed description and presentation of information flows and the drivers of change (i.e., feedback loops) that are essential for creating secondary material streams based on the critically analyzing the reviewed literature. The novelty of this study includes the identification of standards and metrics gaps to facilitate quantitative assessment and evaluation in a CE. The study further elucidates the discussion around CE in terms of resource regeneration by ‘designing out waste’ and decoupling economic growth from resource depletion.

Establishing the Range of Applicability of Hydrodynamics in High-Energy Collisions.

We simulate the space-time dynamics of high-energy collisions based on a microscopic kinetic description in the conformal relaxation time approximation, in order to determine the range of applicability of an effective description in relativistic viscous hydrodynamics. We find that hydrodynamics provides a quantitatively accurate description of collective flow when the average inverse Reynolds number Re^{-1} is sufficiently small and the early preequilibrium stage is properly accounted for. We further discuss the implications of our findings for the (in)applicability of hydrodynamics in proton-proton, proton-nucleus, and light nucleus collisions.

Pore-scale modeling of pore structure properties and wettability effect on permeability of low-rank coal

Permeability is a key parameter for coalbed methane development. Although the absolute permeability of coal has been extensively studied, wettability and pore structure properties continue to challenge the microscopic description of water-gas flow in coal. For this purpose, we reconstructed the microstructures of low-rank coal using micro-computed tomography (micro-CT) images. Pore geometry and pore-throat parameters are introduced to establish a relationship with absolute permeability. A dual-porosity pore network model is developed to study water-gas displacement under different wetting and pore structure properties. Results show that absolute permeability is significantly affected by pore geometry and can be described using a binary quadratic function of porosity and fractal dimension. Water-gas relative permeability varies significantly and the residual gas saturation is lower; the crossover saturation first decreased and then increased with increasing porosity under hydrophobic conditions. While the water relative permeability is lower and a certain amount of gas is trapped in complex pore-throat networks; the crossover saturation is higher under hydrophilic conditions. Models with large percolating porosity and well-developed pore networks have high displacement efficiency due to low capillary resistance and avoidance of trapping. This work provides a systematic description of absolute permeability and water-gas relative permeability in coal microstructure for enhanced gas recovery.

Investigations of correlation and coherence in turbulence from a large-eddy simulation

Abstract. Microscale flow descriptions are often given in terms of mean quantities, turbulent kinetic energy, and/or stresses. Those metrics, while valuable, give limited information about turbulent eddies and coherent turbulent structures. This work investigates the structure of an atmospheric boundary layer using coherence and correlation in space and time with a range of separation distances. We calculate spatial correlations over entire planes of velocity fluctuations, from which we can evaluate the correlation along different directions at different spacings. Similarly, coherence of the three velocity components over separations in the three directions is also investigated. We apply these analyses to a mesoscale–microscale coupled scenario with time-varying conditions and examine nuances in spatial correlations that are often overlooked. Through these analyses and results, this work highlights important differences observed in terms of coherence when comparing large-eddy simulation data to simpler models and suggests ways to improve these simpler models. We note that such differences are important for disciplines like wind energy structural dynamic analysis, in which blade loading and fatigue depend strongly on the structure of the turbulence. We emphasize the additional wealth of data that can be provided by typical atmospheric boundary layer large-eddy simulation when correlation and coherence analysis is included, and we also state the limitations of large-eddy simulation data, which inherently truncate the smaller scales of turbulence.

Lagrangian description of the atmospheric flow from Eulerian tracer advection with relaxation

AbstractThe Lagrangian representation of fluid flows offers a natural perspective to study many kinds of physical mechanisms. By contrast, the Eulerian representation is more convenient from a diagnostic point of view. This article attempts to combine elements of both worlds by proposing an Eulerian method that allows one to extract Lagrangian information about the atmospheric flow. The method is based on the offline advection of passive tracer fields and includes a relaxation term. The latter device allows one to run the integration in a continuous fashion without the need for reinitialization. As a result one obtains accumulated Lagrangian information, for example, about the recent parcel displacement or the recent parcel‐based diabatic heating, at each point of an Eulerian grid at any time step. The method is implemented with a pseudospectral algorithm suitable for gridded global atmospheric data and compared with the more traditional trajectory method. The method's utility is demonstrated on the basis of a few examples, which relate to cloud formation and the development of temperature anomalies. The examples highlight that the method provides a convenient diagnostic of parcel‐based changes, paving an intuitive way to explore the physical processes involved. Due to its gridpoint‐based nature, the proposed method can be applied to large data sets in a straightforward and computationally efficient manner, suggesting that the method is particularly useful for climatological analyses.

Structure function tensor equations with triple decomposition

Exact budget equations are derived for the coherent and stochastic contributions to the second-order structure function tensor. They extend the anisotropic generalised Kolmogorov equations (AGKE) by considering the coherent and stochastic parts of the Reynolds stress tensor, and are useful for the statistical description of turbulent flows with periodic or quasi-periodic features, like, for example, the alternate shedding after a bluff body. While the original AGKE describe production, transport, inter-component redistribution and dissipation of the Reynolds stresses in the combined space of scales and positions, the new equations, called $\varphi$ AGKE, contain the phase $\varphi$ as an additional independent variable, and describe the interplay among the mean, coherent and stochastic fields at the various phases. The newly derived $\varphi$ AGKE are then applied to a case where an exactly periodic external forcing drives the flow: a turbulent plane channel flow modified by harmonic spanwise oscillations of the wall to reduce drag. The phase-by-phase action of the oscillating transversal Stokes layer generated by the forcing on the near-wall turbulent structures is observed, and a detailed description of the scale-space interaction among mean, coherent and stochastic fields is provided thanks to the $\varphi$ AGKE.

Atomistic-Continuum Constitutive Modeling Connection for Gold Foams under Compression at High Strain Rates: The Dislocation Density Effect

Constitutive description of the plastic flow in metallic foams has been rarely explored in the literature. Even though the material is of great interest to researchers, its plasticity remains a topic that has a much room for exploration. With the help of the rich literature that explored the material deformation mechanism, it is possible to introduce a connection between the results of the atomistic simulations and the well-established continuum constitutive models that were developed for various loading scenarios. In this work, we perform large-scale atomistic simulations of metallic gold foams of two different sizes at a wide range of strain rates (107−109 s−1) under uniaxial compression. By utilizing the results of those simulations, as well as the results we reported in our previous works, a physical atomistic-continuum dislocations-based constitutive modeling connection is proposed to capture the compressive plastic flow in gold foams for a wide range of sizes, strain rates, temperatures, and porosities. The results reported in this work present curated datasets that can be of extreme usefulness for the data-driven AI design of metallic foams with tunable nanoscale properties. Eventually, we aim to produce an optimal physical description to improve integrated physics-based and AI-enabled design, manufacture, and validation of hierarchical architected metallic foams that deliver tailored mechanical responses and precision failure patterns at different scales.

Oscillating viscous flow past a streamwise linear array of circular cylinders.

This paper addresses the viscous flow developing about an array of equally spaced identical circular cylinders aligned with an incompressible fluid stream whose velocity oscillates periodically in time. The focus of the analysis is on harmonically oscillating flows with stroke lengths that are comparable to or smaller than the cylinder radius, such that the flow remains two-dimensional, time-periodic and symmetric with respect to the centreline. Specific consideration is given to the limit of asymptotically small stroke lengths, in which the flow is harmonic at leading order, with the first-order corrections exhibiting a steady-streaming component, which is computed here along with the accompanying Stokes drift. As in the familiar case of oscillating flow over a single cylinder, for small stroke lengths, the associated time-averaged Lagrangian velocity field, given by the sum of the steady-streaming and Stokes-drift components, displays recirculating vortices, which are quantified for different values of the two relevant controlling parameters, namely, the Womersley number and the ratio of the inter-cylinder distance to the cylinder radius. Comparisons with results of direct numerical simulations indicate that the description of the Lagrangian mean flow for infinitesimally small values of the stroke length remains reasonably accurate even when the stroke length is comparable to the cylinder radius. The numerical integrations are also used to quantify the streamwise flow rate induced by the presence of the cylinder array in cases where the periodic surrounding motion is driven by an anharmonic pressure gradient, a problem of interest in connection with the oscillating flow of cerebrospinal fluid around the nerve roots located along the spinal canal.

On the dynamics of the near-surface currents in the Arctic Ocean

Starting from the Navier–Stokes equation (in rotating, spherical coordinates), and the equation of state coupled with the first law of thermodynamics for the atmosphere, a general description of the near-surface flow in the Arctic Ocean, and the atmosphere above it, is developed. This includes a suitable stress boundary condition at the air–ice–water interface. Invoking only the thin-shell approximation, for both the atmosphere and the ocean, an appropriate asymptotic reduction is developed; this approach ensures that all the physical attributes are retained at leading order. The wind is described via the properties of the Prandtl layer and the atmospheric boundary layer, with some observations about the geostrophic flow higher in the troposphere. The corresponding equations for the ocean, with a suitable surface wind, are used to model the two dominant features of the arctic surface-current field: the rotating Beaufort Gyre and, using a transformation of the spherical coordinates that removes the polar singularities in geographical coordinates, the Transpolar Drift. In addition, we show that the stress conditions at the ice–water interface ensure that the sea-ice necessarily moves faster than the ocean on which it floats, and in a direction between that of the surface wind and that of the ocean surface current.

Study and modeling of the thrombosis of small cerebral aneurysms, with and without flow diverter, by the lattice Boltzmann method

Background and objectiveSmall cerebral aneurysms are currently commonly treated non-invasively by flow diverter device. These stents lead to thrombotic occlusion of the aneurysm soon after their placement. The purpose of this work is to model clotting into intracranial aneurysms with and without stents, using a non-Newtonian of blood behavior, and to investigate the importance of stent to generate desired thrombus in intracranial aneurysms. MethodThe description of blood flow is made by the Boltzmann lattice equations, while thrombosis is modeled by the "fluid age" model. The lattice Boltzmann method is a computational technique for simulating fluid dynamics. The method is based on a mesoscopic approach, where the fluid is represented by a set of particles that move and interact on a grid. The model for blood coagulation is described by lattice Boltzmann Method, and it doesn't take into account the complicated coagulation pathway, this main idea is developed using the model of residence time of blood: all fluid in the domain is assumed to be capable of clotting, given enough time. The fluid age is measured by a passive scalar using a transport equation, and the node coagulates if the fluid age increases enough. Three small aneurysms of different sizes and shapes with three stents of various porosities were used to test the ability of the model to predict thrombosis. The "occlusion rate" parameter is used to assess the effectiveness of the flow diverter device. ResultsFor the large aspect ratio factor, the occlusion is: 91% for flow diverter devise with seven struts. For medium aspect ratio, a rate of 80% is achieved. An occlusion rate of slightly more than 30% is obtained for very small aneurysms with low aspect ratio. The Newtonian model underestimates the volume of thrombosis generated. The difference in the prediction of the thrombosis volume between the Newtonian and no-Newtonian Carreau-Yasuda models is approximately 10%. ConclusionThe occlusion rate is proportional to the aspect ratio form factor. For the large and medium aspect ratio factors, the occlusion is satisfactory. Concerning very small aneurysms with low aspect ratio, aneurysm occlusion is low. This rate can be improved to almost complete occlusion if the flow diverter device is doubled. The generality of the model suggests its extensibility toward any other type of thrombosis (stenosis, thrombosis in aortic aneurysms).

Intelligent management of industrial building energy saving based on artificial intelligence

In order to improve the efficiency of energy-saving management of industrial buildings, this paper combines artificial intelligence technology to analyze the intelligent energy-saving of industrial buildings, and reduces the energy consumption of industrial buildings through intelligent energy-saving management. Moreover, this paper analyzes the circuit structure design, work flow, and functional description of industrial energy-saving buildings to realize the control interface of electrical equipment, and explains the specific hardware design of energy consumption acquisition module and intelligent gateway. In addition, this paper uses the data collected by the hardware as the input to establish the impulse prediction model. Finally, this paper constructs an intelligent management system for industrial building energy conservation based on constraints and optimization conditions. The data analysis results show that the intelligent energy-saving management system of industrial buildings based on artificial intelligence constructed in this paper has good effects and can play an important role in the energy-saving management of industrial buildings.

Modeling large‐scale landform evolution with a stream power law for glacial erosion (OpenLEM v37): benchmarking experiments against a more process-based description of ice flow (iSOSIA v3.4.3)

Abstract. Following the tradition of modeling fluvial landscape evolution, a novel approach describing glacial erosion based on an empirical stream power law was proposed. This approach differs substantially from well-established process-based models applied to describe glacial erosion in mountain landscapes. Outstanding computational performance but a number of potential limitations compared to process-based models requires extensive testing to evaluate the applicability of this novel approach. In this study, we test the validity of the glacial stream power law and its implementation into a 2-D landform evolution model (OpenLEM) by benchmarking it against a state of the art surface process model based on the integrated second-order shallow-ice approximation (iSOSIA). Despite completely different approaches, OpenLEM and iSOSIA predict similar ice flow patterns and erosion rates for a wide range of climatic conditions without re-adjusting a set of calibrated parameters. This parameter set is valid for full glacial conditions where the entire precipitation is converted to ice but also for an altitude-dependent glacier mass balance as characteristic for most glaciated mountain ranges on Earth. In both models characteristic glacial features, such as overdeepenings, hanging valleys and steps at confluences emerge roughly at the same locations, resulting in a consistent altitude-dependent adjustment of channel slope and relief. Compared to iSOSIA, however, distinctly higher erosion rates occur in OpenLEM at valley flanks during the initial phase of the fluvial to glacial transition. This is mainly due to the simplified description of glacier width and ice surface in OpenLEM. In this respect, we found that the glacial stream power approach cannot replace process-based models such as iSOSIA but is complementary to them by addressing research questions that could not previously be answered due to a lack of computational efficiency. The implementation of the glacial stream power law is primarily suitable for large-scale simulations investigating the evolution of mountain topography in the interplay of tectonics and climate. As coupling glacial and fluvial erosion with sediment transport shows nearly the same computational efficiency as its purely fluvial counterpart, mountain-range-scale simulations at high spatial resolution are not exclusively restricted to the fluvial domain anymore, and a series of exciting research questions can be addressed by this novel approach.

Stationary expansion of gas mixture from a spherical source into vacuum

Sublimation under solar illumination of diverse ices composing the cometary nucleus forms multispecies gas coma. Depending on the heliocentric distance, the gas production of the nucleus varies in a broad range that results in circumnucleus flow regimes ranging from free-molecular to fluid. Therefore it is important to consider kinetic effects occurring in the gas and their influence on the flow and boundary conditions.We consider stationary flows of pure gases (H2O, CO2, CO) and their mixtures from a spherical surface. It is assumed that gas production of the surface is a consequence of sublimation within the surface layer. The detailed study of the structure and parameters of the gas outflow is based on the kinetic approach. The study considers flow conditions from fluid to free molecular.The results are numerically computed quantities which make the link between production rate, gas composition and surface temperature and: (1) velocities and abundances of gas species beyond the acceleration region; (2) mass, momentum and energy fluxes from the gas environment towards the surface; (3) parameters of the gas flow at the sonic surface circumscribing the source. Also, we define regions and conditions where the fluid approximation of the flow can be correctly applied. These data are necessary for definitions of parameters in: (1) simplified “Haser-type” models; and (2) advanced models of cometary activity which take into consideration the influence of gas environment on nucleus surface; and (3) coma models based on the fluid description of the gas flow.

Geospatial Network Analysis and Origin-Destination Clustering of Bike-Sharing Activities during the COVID-19 Pandemic

Bike-sharing data are an important data source to study urban mobility in the context of the coronavirus disease 2019 (COVID-19). However, studies that focus on different bike-sharing activities including both riding and rebalancing are sparse. This limits the comprehensiveness of the analysis of the impact of the pandemic on bike-sharing. In this study, we combine geospatial network analysis and origin-destination (OD) clustering methods to explore the spatiotemporal change patterns hidden in the bike-sharing data during the pandemic. Different from previous research that mostly focuses on the analysis of riding behaviors, we also extract and analyze the rebalancing data of a bike-sharing system. In this study, we propose a framework including three components: (1) a geospatial network analysis component for a statistical and spatiotemporal description of the overall riding flows and behaviors, (2) an origin-destination clustering component that compensates the network analysis by identifying large flow groups in which individual edges start from and end at nearby stations, and (3) a rebalancing data analysis component for the understanding of the rebalancing patterns during the pandemic. We test our framework using bike-sharing data collected in New York City. The results show that the spatial distribution of the main riding flows changed significantly in the pandemic compared to pre-pandemic time. For example, many riding trips seemed to expand the purposes of riding for work–home commuting to more leisure activities. Furthermore, we found that the changes in the riding flow patterns led to changes in the spatiotemporal distributions of bike rebalancing, such as the shifting of the rebalancing peak time and the increased ratio between the number of rebalancing and the total number of rides. Policy implications are also discussed based on our findings.

Lagrangian modelling of nonlinear viscous waves generated by moving seabed deformation

A Lagrangian flow model is used to investigate highly nonlinear, dispersive waves generated by moving seabed deformation (MSD) of an otherwise horizontal seabed. Applications include free surface wave responses to horizontal co-seismic displacements and to novel bed-driven wave making systems used in surfing competitions. This paper considers gravity waves in viscous liquid, without restrictions on wave steepness, dispersion coefficient, and flow regime. Numerical computations are carried out using a Moving Particle Explicit method, which provides a Lagrangian flow description with far fewer particles than existing meshless methods. We show that the MSD speed has different effects in shallow and intermediate water depths. In shallow water, raising the MSD speed to a transcritical value promotes generation of leading solitary waves as expected. In supercritical flow, the highly nonlinear dynamics promotes breaking of the precursor soliton. In intermediate depth, wave dynamics is dominated by nonlinearity and dispersion, which act concurrently to generate a large leading wave that travels faster than predicted by linear theory, followed by a train of dispersive, short, steep waves. These waves break, even at subcritical values of MSD speed. We show that strongly nonlinear viscous dynamics occurs in the presence of a steep seabed deformation. This triggers flow separation, linked to strong amplification of wave steepness. Finally, we show that an oscillating MSD is capable of generating higher harmonics by means of nonlinear wave–wave interactions. The model is validated and verified by comparison to previously published experimental data and approximate analytical solutions.

Experimental evaluation of fluid connectivity in two-phase flow in porous media

In this work, we provide a physically-consistent modeling approach for two-phase porous media flow, by including percolating interfacial area and saturation as state variables. For this purpose, we combine two continuum theories for two-phase flow which have been individually proven to be conditionally valid. This means the potential use of the connected-to-the-flow interfacial area as a state variable is tested utilizing time-resolved microfluidic experiments, for various flux boundary conditions. Moreover, we observe and study a linear relation between the percolating saturation and interfacial area, which is persistent for the tested boundary conditions. In our microfluidic experiments, we employ optical microscopy to perform cyclic immiscible displacement experiments. Our results show that a continuum model, where capillary pressure, saturation , and specific interfacial area of the clusters connected to the flow are considered, is closer to a universal description of two-phase flow than the common approaches, where the only state variable is saturation.

A MODEL OF MICROSTRUCTURE EVOLUTIONUNDER HIGH- STRAIN RATE DEFORMATION OF COPPER

A physical model of high-strain rate deformation of metallic materials has been developed to describe the evolution of microstructure during the process. The model is based on representations of the mechanisms of grain boundary sliding, strain-induced grain growth and dynamic fragmentation of coarse grains developed in the framework of the theory of nonequilibrium grain boundaries. These representations are modified for the description of high-speed flow and supplemented by a model of dynamic recrystallization. It is shown that during high-strain rate deformation of metallic materials, grain boundary sliding dominates in the material regions with a fine-grained submicron structure and the material deforms in the superplasticity mode. In regions of material with larger grain size, grain volume deformation dominates, accompanied by fragmentation and formation of fine-grained structure with submicron grain size. The transformation of the structure from fine-grained to coarse-grained occurs due to strain-induced grain growth. Transformation of structure from coarse grain to fine grain occurs due to dynamic fragmentation. The transition from grain boundary sliding to grain volume deformation occurs at grain size corresponding to the optimum value for the course of dynamic recrystallization. The cyclic change of deformation mechanisms (from grain boundary strain-induced to grain volume deformation) is caused by alternation of the processes of deformation-stimulated grain growth and dynamic fragmentation. The alternation of the above cycles of grain boundary and intragranular deformation in different regions of the material makes it possible to maintain a high strain rate and suppress the processes of both local hardening and local softening. The high strain rate is achieved at the expense of a high strain of the regions in which grain sliding dominates. In the regions dominated by intragranular deformation, the structure is “prepared” for superplastic flow.