Macroscopic Approach Research Articles

Theoretical background for simulation of the interfacial layer “liquid-gas”

The study shows that macroscopic approach to the description of surface phenomena used to simulate the interfacial layer as a membrane using Laplace equation allows to calculate the shape of liquid meniscus regardless of the determination of height of liquid elevation in a capillary. The use of van der Waals statements to describe the state of the medium in the interfacial layer makes it possible to estimate the distribution of molecular pressure along the layer thickness. The tensor of interfacial stresses, represented by a set of ball and deviator parts, is determined based on continuous medium equilibrium conditions. The stresses that form the surface tension of the fluid are deviator components of the tensor. As a result, the study provides the expression linking the parameters of interfacial layer thickness and surface tension of liquid.

Prediction of forming effects in UD-NCF by macroscopic forming simulation – Capabilities and limitations

Unidirectional non-crimp fabrics (UD-NCF) provide the highest lightweight potential among dry textile materials. Compared to multiaxial NCF, the fabric layers in UD-NCF enable a more targeted tailoring. Compared to woven fabrics, the fibres of UD-NCF are straight without weakening undulations. However, the formability of UD-NCF is more challenging compared to woven fabrics. The yarns are bonded by a stitching and the deformation behaviour highly depends on this stitching and on the slippage between the stitching and the fibre yarns. Moreover, distinct local draping effects occur, like gapping and fibre waviness, which can have a considerable impact on the mechanical performance. Such local effects are particularly challenging or even impossible to be predicted by macroscopic forming simulation. The present work applies a previously published macroscopic UD-NCF modelling approach to perform numerical forming analyses and evaluate the prediction accuracy of forming effects. In addition to fibre orientations and shear angles, as investigated in previous work, the present work also provides indication for fibre area ratios, gapping, transverse compaction and fibre waviness. Moreover, the prediction accuracy is validated by comparison with experimental tests, where full-field strains of inner plies are captured by prior application of dots onto the fibre yarns, by measuring them via radiography and applying a photogrammetry software. The modelling approach provides good prediction accuracy for fibre orientations, shear strains and fibre area ratio. Conversely, normal fibre strains, indicating fibre waviness, and transverse strains, indicating gapping, show some deviations due to the multiscale nature of UD-NCF that cannot be captured entirely on macroscopic scale.

Improvement of switched structure semi‐active battery/supercapacitor hybrid energy storage system for electric vehicles

Among new configurations of battery/supercapacitor (SC) hybrid energy storage systems (HESSs) for electric vehicles (EVs), several can be united under the common name of ‘switched structure’. Their features are the ability to switch their structure during operation to direct power of a DC-bus from the battery or from the SC bank, as well as the use of a low-power DC–DC converter that connects both ESSs. Here, such a switched structure between battery/SC HESS was improved, which made it possible to obtain new operating modes. They expand the operating range of the SC bank, while the DC-bus voltage range remains relatively small. As a result, the installed capacity of the SC bank can be reduced by 50% without decreasing the available energy of the SC bank. An algorithm for the energy management system was developed according to the rule-based strategy that allows to choose one from the eight operating modes. The simulation of investigated EV operation with the proposed HESS was carried out during the transport cycle on a model developed through the energetic macroscopic representation approach. The simulation results are confirmed by experiments on a scaled-down experimental setup.

Macroscopic quantum electrodynamics approach to nonlinear optics and application to polaritonic quantum-vacuum detection

We provide an in-depth discussion of a theoretical framework recently introduced [Lindel et al., Phys. Rev. A 102, 041701(R) (2020)] which is capable of predicting the electromagnetic field emerging from a nonlinear crystal through which a coherent laser pulse is shone. This framework is based on macroscopic quantum electrodynamics and includes dispersion and absorption effects inside the crystal and allows for arbitrary optical environments through the classical Green's tensor. We introduce a diagrammatic approach with which the nonlinear processes contributing to the electric field operator up to certain orders in the perturbation series can be represented in a convenient way. Applying this framework to the setup of electro-optic sampling experiments of the polaritonic quantum vacuum, we derive analytical results for the electro-optic sampling between distinct spatiotemporal regions. Also, we discuss different approximations and the parameter ranges in which they apply including angled or diverging beams, thermal fluctuations, as well as (linear) absorption effects upon the polaritonic quantum vacuum. Finally, we compare these theoretical results to experimental data.

A macroecological perspective on the fluctuations of exploited fish populations

The natural variability of fish populations is increased by exploitation, but the specific mechanisms driving this variability are still debated. We propose a macroscopic approach combining the size-density relationship and Taylor’s law to predict the temporal variance of exploited and unexploited fish populations. Using information from 11 years of fishery-independent abundance surveys, we showed that the body-size dependence of the variance of exploited (targeted) and unexploited (non-targeted or bycatch) fish populations can be accurately predicted. Targeted fish populations showed a variability that was 2 orders of magnitude greater than that of non-targeted fish populations. Such variability was explained solely by the higher relative abundance of the former, regardless of their specific trophic position, while aggregated community fluctuation was lower in a high trophic position group. This study showed the usefulness of the macroscopic approach to predict fish variability and fishing effect in the whole community. This approach is complementary to other modeling strategies and seems to be useful in tackling the problem of variability in population fluctuations of exploited fish, particularly in cases where specific details of the interacting species are lacking.

Enhanced lignite flotation using interfacial nanobubbles based on temperature difference method

Froth flotation is the primary method for the separation and upgrading of fine coal particles. However, this method is ineffective for lignite which is more hydrophilic than other types of coal due to the abundant oxygenated functional groups, cracks, and micropores on its surface. This study develops a new method that introduces interfacial nanobubbles (INBs) based on the temperature difference method for enhancing lignite flotation. The mechanism of lignite flotation enhanced by INBs is systematically explained through the induction time and bubble-particle collision-attachment behavior. The experimental results show that the lignite flotation efficiency is evidently improved using the temperature difference method. AFM imaging of the changes on a highly oriented pyrolytic graphite surface due to temperature difference demonstrate the production of INBs. In the presence of INBs, the induction time of lignite can be reduced from 400 ms to 27.21 ms, the number of bubble-particle collisions from 4 to 3, and the attachment time from 208 ms to 128 ms. When a macroscopic air bubble approaches to a lignite surface with INBs, the air bubble first merges with the INBs, not only decreasing the induction time but also increasing the apparent contact angle and length of three-phase contact line.

Comparison of travel time for particles with different route-choice methods in two-route traffic models

We explore the route-choice problem in two-route traffic systems when real-time particle densities are provided. Four scenarios are considered, which have three types of informed particle and two types of uninformed particle. They adopt different route-choice rules. The system is mimicked by a lattice model and each vehicle is supposed as a hard-core “particle”. With a macroscopic approach, the stability conditions of systems are theoretically analyzed, which separate long, intermediate and short travel time phases. The Monte Carlo simulation results certify theoretical predictions. The relative benefits of route-choice rules are compared by average travel times of different types of particles, which depend on system’s phases. These results are useful for traffic flow optimization on traffic networks.

Operational efficiency analysis of Beijing multi-airport terminal airspace

Multi-airport systems are growing in number and size globally, despite being afflicted by known inefficiencies due to the interferences between the flows of neighbouring airports. A macroscopic empirical approach is proposed in this paper to estimate the capacity penalties and demonstrated by a numerical case study for Beijing, which is projected to become one of the busiest metroplexes in Asia. The Pareto envelopes of the theoretical and observed peak hour capacities are statistically analysed to quantify the penalties in a comparable metroplex and are subsequently modulated by a sigmoid correlation function. The analysis predicts the practical capacity of Daxing, the penalty incurred by the pre-existing Capital airport and by the total multi-airport system. Various findings are drawn and discussed, highlighting the needs for further research.

Universality in microdroplet nucleation during solvent exchange in Hele-Shaw-like channels

Abstract

The dynamics of droplet detachment in reversed electrowetting (REW)

Droplet actuation by electrowetting (EW) has drawn significant interest due to the potential applications in micro- and nano-fluidics, and the droplet departure is crucial for separation of the drop phase from the solid surface. However, the operating condition for droplet detachment, induced by the traditional electrowetting is quite strict, making it inconvenient for practical application. Recently, we considered the reversed electrowetting (REW) phenomenon, where a non-conductive droplet, settled on an adhesive surface, is dewetted continuously by applying the potential different between the substrate and surrounding fluid (Wang et al. 2020). Detachment of the oil drop is induced naturally and the detaching process is controllable. We have investigated the physical process of REW in the previous experiments. However, the dynamics of droplet detachment and the underlying mechanism are not well explained by the macroscopic experimental approach. For complementation, we build a numerical scheme in this study and examine the transient dynamics of droplet motion in the REW. The interface of the liquid-liquid system is captured by a phase-field method, and a correlation for the dynamic contact angle is incorporated in the numerical model. The simulated results are validated with the experimental cases. The process of droplet detachment and the critical condition are investigated by analyzing the energy transition during the droplet motion.

Comparison of variance-reduction techniques for gamma dose rate determination

Three-dimensional computer simulation and virtual reality technology enable the visualization of dose encountered by workers during dismantling operations by using simplified real-time dose computation tools. Such tools generally use a macroscopic approach for gamma dose rate calculation, namely the point kernel integration method with build-up factors. This simplified physical model enhances calculation performance but presents also some restrictions. In contrast, stochastic Monte Carlo methods enable a precise estimation of gamma dose rate, but computing time is prohibitive for real-time dose applications. To speed up the simulation, Monte Carlo codes can be used in combination with variance-reduction techniques, which have to be used very cautiously to stay within their limits of validity. This paper presents a comparison between two variance-reduction techniques implemented in the Monte Carlo code TRIPOLI-4 $$\circledR $$ , the exponential transform and the adaptive multilevel splitting, testing their efficiency in dismantling-like configurations.Both methods behave better in deep penetration problems but require a good amount of user experience in the creation of the importance map. This study shows the need to develop a new type of algorithm capable to tackle configurations where the lack of collisions can limit the efficiency of the current VRT.

A Macroscopic Approach for Simulating Horizontal Convection in a Vegetated Pond

A macroscopic approach for simulating horizontal convection in a vegetated pond is presented. The generated convective currents are due to the differential radiation absorption between the two regions of the pond, one with emergent vegetation up to the free surface and one without vegetation. The Volume-Averaged Navier-Stokes (VANS) equations are used for the simulation of the laminar, unsteady, two-dimensional horizontal convection. The vegetation effects on the motion of the currents are taken into account through additional resistance terms based on the vegetation porosity and permeability. The Volume-Averaged Energy (VAE) equation is also solved with an additional source term accounting for the absorption of radiation which is based on a one-waveband and a three-waveband radiation model. The model setup is based on Beer’s law whereas the incoming radiation is absorbed from the water column. Three types of vegetation porosities φ varying from 0.75 to 0.97 are examined in investigating the motion of the convective currents within the vegetated area. The case without vegetation (φ = 1.0) is also examined for assessing the effectiveness of the radiation model. The numerical current velocity and the water temperature increase are presented and compared against available experimental data. • Absorption of radiation based on one- and three-waveband attenuation models • Vegetation effects on the characteristics of horizontal convection • Effect of Grashof number on the motion of horizontal convective currents

CHAOTIC EVOLUTION OF DIFFERENCE EQUATIONS IN MANN ORBIT

Because of the tremendous characteristics of discrete chaos and sensitivity to their initial parameters, discrete one-dimensional maps are extensively used in every branch of science and engineering such as a security system, cryptography and traffic control models. In this article, it is proposed to examine the chaotic characteristics of a logistic-type difference equation using Mann orbit. Due to the presence of an added parameter <i>α</i> the resulting orbit provides superior chaotic characteristics from those of the existing characteristics in chaotic maps. As compared to existing chaotic maps it provides more efficient and effective chaotic characteristics like better sensitivity, suitable maximum Lyapunov exponent value and superior stability behavior. The results are carried out mathematically as well as experimentally followed by theorems, a few counterexamples and some concluding remarks. Moreover, a superior discrete traffic flow model using macroscopic approach and Greenshield's model is also described.

Advancements in multi‐phase unsaturated porous media fracture

AbstractThe focus in this research is on introducing an accurate and stable numerical modeling framework and to compare the numerical results with experimental data from the literature for desiccation‐induced fracturing of unsaturated porous materials. The macroscopic modeling approach is based on combined continuum porous media mechanics and a diffusive phase‐field method (PFM). In the case of unsaturated porous media, one has to deal with more than one pore fluid (e.g. water and air). In this, the mechanical behavior can be expressed via using the Bishop's effective stress principle, which considers the total stress, the capillary pressure (air pressure minus water pressure), and saturation degree. The onset of desiccation‐induced fracturing is driven by the capillary pressure, which leads to degradation not only in the effective stresses but also in the capillary pressure itself. In this contribution, we discuss via a numerical example the effect of considering the air pressure variation on the cracking process and numerical stability. Besides, we briefly discuss the potential inclusion of machine‐learning material laws, such as for retention curves and anisotropic permeability, using, e.g., deep recurrent neural networks (RNN) to improve the model accuracy.

Water management of frost‐resistant plant tissues as a consequence of extracellular ice formation

AbstractThe formation of extracellular ice within plant tissues is regarded as one of their crucial factors to withstand subzero temperatures without any (biologically irreversible) damage. In this regard, extracellular ice implies two important consequences, which are the dehydration of the tissue cells to prevent intracellular ice formation, which would be fatal for the plant, and the attraction of water towards the freezing site. However, the pattern of ice formation may vary significantly among various types of plants. There might be rather dispersed ice formation distributed in large parts of the plant or localised ice formation at internal surfaces. Within this contribution, the latter‐mentioned case is addressed with a macroscopic modelling approach based on the Theory of Porous Media. The appearing water management is discussed at a representative numerical example.

Containment effort reduction and regrowth patterns of the Covid-19 spreading.

In all countries the political decisions aim to achieve an almost stable configuration with a small number of new infected individuals per day due to Covid-19. When such a condition is reached, the containment effort is usually reduced in favor of a gradual reopening of the social life and of the various economical sectors. However, in this new phase, the infection spread restarts and, moreover, possible mutations of the virus give rise to a large specific growth rate of the infected people. Therefore, a quantitative analysis of the regrowth pattern is very useful. We discuss a macroscopic approach which, on the basis of the collected data in the first lockdown, after few days from the beginning of the new phase, outlines different scenarios of the Covid-19 diffusion for longer time. The purpose of this paper is a demonstration-of-concept: one takes simple growth models, considers the available data and shows how the future trend of the spread can be obtained. The method applies a time dependent carrying capacity, analogously to many macroscopic growth laws in biology, economics and population dynamics. The illustrative cases of France, Italy and United Kingdom are analyzed.

Prediction of crack propagation kinetics through multipoint stochastic simulations of microscopic fields

Prediction of crack propagation kinetics in the components of nuclear plant primary circuits undergoing Stress Corrosion Cracking (SCC) can be improved by a refinement of the SCC models. One of the steps in the estimation of the time to rupture is the crack propagation criterion. Current models make use of macroscopic measures (e.g. stress, strain) obtained for instance using the Finite Element Method. To go down to the microscopic scale and use local measures, a two-step approach is proposed. First, synthetic microstructures representing the material under specific loadings are simulated, and their quality is validated using statistical measures. Second, the shortest path to rupture in terms of propagation time is computed, and the distribution of those synthetic times to rupture is compared with the time to rupture estimated only from macroscopic values. The first step is realized with the cross-correlation-based simulation (CCSIM), a multipoint simulation algorithm that produces synthetic stochastic fields from a training field. The Earth Mover’s Distance is the metric which allows to assess the quality of the realizations. The computation of shortest paths is realized using Dijkstra’s algorithm. This approach allows to obtain a refinement in the prediction of the kinetics of crack propagation compared to the macroscopic approach. An influence of the loading conditions on the distribution of the computed synthetic times to rupture was observed, which could be reduced through a more robust use of the CCSIM.

On the Irreversibility in Mechanical Systems Using a New Macroscopic Energy Structure Modeling

This paper presents a macroscopic applied innovate modeling to study the performance effects of the second law of thermodynamics on the mechanical systems. To investigate the irreversibility in mechanical systems, the energy structure of the system can be studied. Some energy components relate to the reversible processes and remaining relate to the irreversible process. Exiting models are based on the studying sub structures and therefore, need a large volume of the calculations. In this paper, at first, using a macroscopic quasi-statistical approach, a new energy structure equation is extracted and by examining it’s variation in the different paths, the irreversible components as well as their structures are studied. Using the kinematic theories of dissipated energy, it can be concluded that the extracted equations have the same base as the different formulations of the second law of thermodynamics. Finally, as a mechanical system example with the possibility of irreversibility in the possible performed processes, the extracted equations are developed for viscoelasticity problems. And also the matching of the results with expected results is shown.

A Study of the Entropy Production in Physical Processes from a New Perspective of the Energy Structure

When a physical process is performed, identifying the generated entropy can be used to investigate the irreversibility. But for this mean, from the perspective of the Boltzmann equation, both all microstates and macrostates must be studied. In fact, it is needed that all particles energy level to be investigated. Therefore, to investigate entropy in configurationally systems using the Boltzmann equation, a very large volume of calculations is required. In this study, we try to extract a way to investigate entropy production without the need to study all particles (or sub-structures). For this purpose, at first, a macroscopic energy structure equation “as an equation that shows the energy components of the system activated in the performed process as well as their dependence” is presented. As a study on the irreversibility (or entropy production) in physical systems, its structure and components are studied. Writing equations in the energy space of the system makes it possible to study the structure of irreversibility. Then using a new macroscopic quasi-statistical approach, the irreversibility and its structure in physical processes are investigated. Macro energy components of the system are used for this investigation and energy structure is studied base on them. Finally, a new macroscopic definition of the generated entropy is extracted using a new energy structure equation as well as dependent and independent macroscopic energy component concepts. Also, why and what entropy can be generated, from the perspective of the presented macroscopic energy structure equation are studied. In fact, this paper investigates the generated entropy structure in physical systems using macroscopic system energy components and takes a new approach to why and what irreversibility is occurred during the physical process. Therefore, presented equations can be used for investigating the irreversibility in configurationally physical systems without the need to study all its sub structures. Also, from the extracted equations, it can be concluded that entropy is generated because of the existence of the dependent energy components in the energy structure equation of the system, and this generated entropy depends on the variation of these components as well as the amount of the applied energy to the system and its conditions. Due to the kinematic theory of dissipated energy, these results are in the same line with the different formulations of the second law of thermodynamics.

Combustion in Ni–Al system with Cu additive (powder or rod) Experiment and mathematical model

Experimental studies were carried out with theoretical calculations of wave synthesis in the Ni–Al–Cu system were performed using the mathematical model developed. Approximate analytical formulas were obtained for synthesis performance evaluation. The inverse problem method was used to get kinetic constants that determine process dynamics based on the experimental data and analytical relationships. It is shown that the combustion front propagation velocity increases monotonically with an increase in the reaction sample relative density in the range of relative density values of 0.4 to 0.6. The depth of copper melt penetration from the center of the sample into the nickel-aluminum matrix depends on the relative density of the sample and copper wire diameter: higher densities and larger diameters lead to an increase in the liquid-phase impregnation area. The rate of nickel and aluminum powder frame wetting with copper melt is limited by the synthesis wave speed. Based on the experimental data and analytical ratios, we estimated the effective kinetic constants describing the high-temperature synthesis of the Ni + Al reaction mixture in the presence of copper additives. The thermal effect of the NiAl intermetallic formation reaction and the preexponential factor in the chemical transformation equation are calculated, the exponent value in the ratio for the mixture thermal conductivity is established; a constant determining the process of nickel-aluminum matrix impregnation with copper melt is found. The macroscopic approach used to analyze the NiAl intermetallic synthesis makes it possible to determine all the desired physicochemical characteristics and model parameters. The mathematical model is suitable for predictive estimates and experimental data analysis in the macroscopic approximation. Approximate analytical formulas are obtained for calculating the NiAl intermetallic synthesis characteristics. They allow for calculating the through channel characteristics and can be used in the design of NiAl products.