Initial Number Of Particles Research Articles

Air exchange rate as a means of ensure requirements to air purity on the basis of high-efficiency filters

In the context of a constant increase in air pollution, the question arises of creating safe air zones with quality control of the air environment in places where people stay. The constant deterioration of air quality caused by military operations and their consequences, as well as the need to reduce the consumption of available energy resources, requires studying the recommendations on the optimal air exchange rate of existing European and American air quality requirements in residential and office buildings to achieve the required air quality with minimal energy consumption. The objectives of the study were to obtain data on the efficiency of air purification in a given volume at different air exchange rates. A separate task was to check the data declared by the manufacturer on the pressure drop across the filter with an increase in the volume of air passing through it. CleanZone5300 filtration systems with F9 class filter and HEPA H12/13 class filter were considered, which can provide an air exchange rate of 2 to 10 times. In a room volume of 225.9 m3, at a temperature of 18 ˚C, a relative humidity of 57-59 % and an initial number of particles in the room air of 533,440 particles/ft3 (15105 particles/m3), the ability of filtration units to purify the air at different rates was studied. It was concluded that even with a factor of 2, the filtration system can provide air purification up to 40 % when using the F9 filter and up to 60 % when using the HEPA H12/13 filter in a short period of time. Recirculation filter units are considered as the easiest way to increase the air exchange rate in the room, in our climatic conditions. With the possibility of avoiding the processing of air for heating or cooling when using outside atmospheric air. In the installations used in the study, the electrical power consumption of the fans is 300 W per hour. The conclusions of the study need to be tested in office premises with an existing ventilation system to determine the optimal multiplicity of achieving a given air quality when using filters or portable filter units.

Distribution and Environmental Impact of Expanded Polystyrene Buoys from Korean Aquaculture Farms

Expanded polystyrene (EPS) buoys, commonly employed in South Korean aquaculture farms, are prone to fragmentation, generating substantial marine debris. The trajectories of EPS buoys dislocated from aquaculture farms were investigated using a Lagrangian particle-tracking model. Daily ocean current data from the 1/12° Hybrid Coordinate Ocean Model analysis and wind data from the 1/4° European Center for Medium-Range Weather Forecasts reanalysis were used as inputs. The particles were released daily, and the initial positions and number of particles were determined based on the usage of EPS buoys. Because EPS buoys are highly buoyant, both wind and ocean currents considerably influence their movement. To account for variations in the buoyancy of these buoys, three experiments were conducted, each considering different levels of windage. The simulation results closely aligned with the observed coastal distribution patterns of the large EPS debris. As the windage increases, the particles exhibit a swifter deviation from their original locations, highlighting the need for effective local management. Moreover, this increased windage affects the distribution patterns in regional seas, reducing the number of particles that flow into the East Sea, while increasing the number of particles that migrate into the Yellow Sea and East China Sea.

Ultrasonic aerosol agglomeration: Manipulation of particle deposition and its impact on air filter pressure drop

Acoustic agglomeration is a technique that leverages on sound waves to promote the collision of aerosol particulate matter, thus leading to the formation of larger particle agglomerates. In this study, this acoustics-driven phenomenon is demonstrated for its usefulness as an aerosol pre-conditioning method to significantly enhance the efficiency of filtration systems in particle treatment processes. Specifically, favorable changes in pressure drop across the filters are observed as a result of receiving less particle mass, for which filters are shown to be able to have their operational life extended remarkably by more than 50%. The involved ultrasonic aerosol agglomeration mechanisms are unveiled through numerical simulations, and the effects of residence time, sound pressure level, and initial particle number concentration on agglomeration performances are experimentally investigated. In addition, validations and measurements of filter pressure drop are obtained through a series of experiments. This study provides a comprehensive overview to the design and performance characterization of acoustics-agglomeration-enhanced filtration systems, which could potentially derive energy savings for fan power in ventilation systems and be scaled up for applications in industrial plants for reducing carbon emissions.

Fluctuations of Mean-Square Displacement in Presence of Traps: Non-Self-Averaging versus Ensemble Averaging

We consider nonstationary diffusion in a medium with random traps-sinks. We study the self-averaging of the mean-square displacement (MSD) of the ensemble of N particles in the fluctuational long-time limit. We demonstrate that MSD of survivors is self-averaging with respect to the number of engaged particles N and is strongly non-self-averaging with respect to time t . To measure MSD of survivors with required accuracy at the required time of observation t 0 , the initial number of particles N 0 must be exponentially large in t 0 . Any N 0 , whatever large, will be insufficient at long enough time. In the formulation, when all particles, both survivors and trapped ones, contribute to MSD, we find self-averaging in N and non-strong non-self-averaging over t .

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data, especially in the event of a noisy or unreliable satellite signal. Toward this end, we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera, an altimeter, a compass, and an open-source Vector Map (VMAP). The algorithm combines the matching and particle filter methods. Shape vector and correlation between two building contour vectors are defined, and a coarse-to-fine building vector matching (CFBVM) method is proposed in the matching stage, for which the original matching results are described by the Gaussian mixture model (GMM). Subsequently, an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles, and a credibility indicator is designed to avoid location mistakes in the particle filter stage. An experimental evaluation of the approach based on flight data is provided. On a flight at a height of 0.2 km over a flight distance of 2 km, the aircraft is geo-localized in a reference map of 11,025 km2 using 0.09 km2 aerial images without any prior information. The absolute localization error is less than 10 m.

Environmental Cost Control of Manufacturing Enterprises via Machine Learning under Data Warehouse

Environmental cost refers to the cost paid by enterprises to reduce environmental pollution and resource depletion in production and operation. To help enterprises reduce environmental costs, a manufacturing environmental cost control algorithm based on machine learning is proposed. The probabilistic neural network is used to classify the current environmental cost control level of different manufacturing enterprises. Then, the particle swarm optimization (PSO) algorithm is improved to build a multi-objective backbone PSO algorithm for multi-objective decision-making, which is used in the selection of environmental cost control methods. The experimental results show that there is a strong correlation between the original data classification and the proposed probabilistic neural network, and the correlation reaches 96.1%. PSO performance test results show that the algorithm has the best performance, the best stability, and the shortest time needed to find the optimal solution set when the initial particle number is 140 and the number of iterations is 60. Based on the comprehensive experimental results, the following conclusions are drawn. Enterprises should strengthen collaboration and cooperation with customers, suppliers, and waste-profiting enterprises, so as to well control environmental costs. To sum up, the proposed model provides some references for the adoption of machine learning in environmental cost control of manufacturing enterprises.

WIMPs without weakness: Generalized mass window with entropy injection

We study general freeze-out scenarios where an arbitrary number of initial and final dark matter particles participate in the number-changing freeze-out interaction. We consider a simple sector with two particle species undergoing such a thermal freeze-out; one of the relics is stable and gives rise to the dark matter today, while the other one decays to the Standard Model, injecting significant entropy into the thermal bath that dilutes the dark matter abundance. We show that this setup can lead to a stable relic population that reproduces the observed dark matter abundance without requiring weak scale masses or couplings. The final dark matter abundance is estimated analytically. We carry out this calculation for arbitrary temperature dependence in the freeze-out process and identify the viable dark matter mass and cross section ranges that explain the observed dark matter abundance. This setup can be used to open parameter space for both heavy (above the unitarity bound) or light (sub-GeV) dark matter candidates. We point out that the best strategy for probing most parts of our parameter space is to look for signatures of an early matter-dominant epoch.

Eulerian–Eulerian modeling of the formation and deposition of SiO2 in the outside vapor deposition process

Understanding the complex phenomena in the outside vapor deposition (OVD) process is critical to improvement of the quality and production rate of optical fibers. In the current work, an Eulerian–Eulerian multiphase model based on Computational Fluid Dynamics (CFD) is proposed to simulate the physico-chemical behavior in the OVD process. The model considers the gas–solid flow, heat and mass transfer, species transport, thermodynamics of chemical reactions, as well as growth and deposition of SiO2 comprehensively. The predicted flame structure and flow characteristics are validated against experimental measurements taken from literature. Typical transport phenomena of the OVD process are captured successfully for deeper insights into the mechanisms of the SiO2 growth and deposition. The sensitivity of the key model constants for the solid phase is analyzed. The model predictions are insensitive to the initial particle number density of the seeds introduced. The initial particle size of the seeds critically affects the growth and deposition of SiO2 in the OVD process. The model provides a profound understanding of the mechanism of SiO2 growth and deposition, which plays an important role in process optimization and product attributes control.

The Matrix Effect in the RT-PCR Detection of SARS-CoV-2 Using Saliva without RNA Extraction.

The present work focuses on the detection of SARS-CoV-2 in saliva, contributing to understanding the inhibition effect of the matrix and its influence on the results. Detection of viral genes ORF1ab, N, and E was performed by RT-PCR using saliva directly in the reaction without RNA extraction. Different amounts of saliva were spiked with increasing amounts of viral RNA from COVID-19 patients and subjected to RT-PCR detection. In parallel, 64 saliva samples from confirmed COVID-19 patients were used in two different amounts directly in the RT-PCR reaction and their results compared. The presence of saliva in the RT-PCR always causes a positive shift of the Ct values, but a very high between-person variability of its magnitude was obtained, with increases ranging from 0.93 to 11.36. Viral targets are also affected differently depending on the initial number of viral particles. Due to inhibitors present in saliva, the duplication of sample volume causes only 48 to 61% of the expected Ct value decrease depending on the viral target gene. The use of saliva has advantages, but also limitations, due to potential inhibitors present in the matrix. However, the choice of the target and the right amount of sample may significantly influence the results.

Branching Random Walks with Two Types of Particles on Multidimensional Lattices

We consider a continuous-time branching random walk on a multidimensional lattice with two types of particles and an infinite number of initial particles. The main results are devoted to the study of the generating function and the limiting behavior of the moments of subpopulations generated by a single particle of each type. We assume that particle types differ from each other not only by the laws of branching, as in multi-type branching processes, but also by the laws of walking. For a critical branching process at each lattice point and recurrent random walk of particles, the effect of limit spatial clustering of particles over the lattice is studied. A model illustrating epidemic propagation is also considered. In this model, we consider two types of particles: infected and immunity generated. Initially, there is an infected particle that can infect others. Here, for the local number of particles of each type at a lattice point, we study the moments and their limiting behavior. Additionally, the effect of intermittency of the infected particles is studied for a supercritical branching process at each lattice point. Simulations are presented to demonstrate the effect of limit clustering for the epidemiological model.

Evolution under dark conditions of particles from old and modern diesel vehicles in a new environmental chamber characterized with fresh exhaust emissions

Abstract. Atmospheric particles have several impacts on health and the environment, especially in urban areas. Parts of those particles are not fresh and have undergone atmospheric chemical and physical processes. Due to a lack of representativeness of experimental conditions and experimental artifacts such as particle wall losses in chambers, there are uncertainties on the effects of physical processes (condensation, nucleation and coagulation) and their role in particle evolution from modern vehicles. This study develops a new method to correct wall losses, accounting for size dependence and experiment-to-experiment variations. It is applied to the evolution of fresh diesel exhaust particles to characterize the physical processes which they undergo. The correction method is based on the black carbon decay and a size-dependent coefficient to correct particle distributions. Six diesel passenger cars, Euro 3 to Euro 6, were driven on a chassis dynamometer with Artemis Urban cold start and Artemis Motorway cycles. Exhaust was injected in an 8 m3 chamber with Teflon walls. The physical evolution of particles was characterized during 6 to 10 h. Increase in particle mass is observed even without photochemical reactions due to the presence of intermediate-volatility organic compounds and semi-volatile organic compounds. These compounds were quantified at emission and induce a particle mass increase up to 17 % h−1, mainly for the older vehicles (Euro 3 and Euro 4). Condensation is 4 times faster when the available particle surface is multiplied by 6.5. If initial particle number concentration is below [8–9] × 104 cm−3, a nucleation mode seems to be present but not measured by a scanning mobility particle sizer (SMPS). The growth of nucleation-mode particles results in an increase in measured [PN]. Above this threshold, particle number concentration decreases due to coagulation, up to −27 % h−1. Under those conditions, the chamber and experimental setup are well suited to characterizing and quantifying the process of coagulation.

Autoresonance phenomenon in a long mirror

The paper describes an implementation of a long mirror-based variant of cyclotron autoresonance which permits a local temporary change in the mirror`s induction and provides a mode for filling the trap with primary plasma, and for the generation of plasma bunches with an energetic electron component and their accumulation within a single cavity. The approach does not require injection of external particles into the acceleration zone as particles can be generated directly within the mirror using specialized conditions of electron cyclotron resonance (ECR) as part of the operational mode. A detailed study of the spectral-angular distribution of Bremsstrahlung in various operational modes has been undertaken. The results of this study permit the optimal value of the time sequence between the leading edge of the pulsed magnetic field and the microwave pulse to be determined, which ensures the optimal mode of electron trapping in the cyclotron autoresonance mode. Bremsstrahlung radiation recorded in the transverse direction has a significantly higher intensity of photons and energy compared to the longitudinal direction during the acceleration and subsequent confinement mode of plasma bunches. The observed changes in the intensity and spectral distribution of the Bremsstrahlung, which depend on the values of the operating parameters for acceleration, afford the possibility to define the dependence of the number of initial plasma particles trapped by cyclotron autoresonance for the different operating modes. The results will improve our understanding of the processes taking place at various stages of the operational modes. In general, such studies are important for gaining an improved understanding of the mechanisms of generation and confinement of hot electron plasma bunches with an energetic electron component for autoresonant interaction in a long mirror.

Distribution of non-spherical nanoparticles in turbulent flow of ventilation chamber considering fluctuating particle number density

The Reynolds-averaged general dynamic equation (RAGDE) for the nanoparticle size distribution function is derived, including the contribution to particle coagulation resulting from the fluctuating concentration. The equation together with that of a turbulent gas flow is solved numerically in the turbulent flow of a ventilation chamber with a jet on the wall based on the proposed model relating the fluctuating coagulation to the gradient of mean concentration. Some results are compared with the experimental data. The results show that the proposed model relating the fluctuating coagulation to the gradient of mean concentration is reasonable, and it is necessary to consider the contribution to coagulation resulting from the fluctuating concentration in such a flow. The changes of the particle number concentration M0 and the geometric mean diameter dg are more obvious in the core area of the jet, but less obvious in other areas. With the increase in the initial particle number concentration m00, the values of M0 and the standard deviation of the particle size σ decrease, but the value of dg increases. The decrease in the initial particle diameter leads to the reduction of M0 and σ, and the increase in dg. With the increase in the Reynolds number, particles have few chances of collision, and hence the coagulation rate is reduced, leading to the increase in M0 and σ, and the decrease in dg.

Rank dependent branching-selection particle systems

We consider a large family of branching-selection particle systems. The branching rate of each particle depends on its rank and is given by a function $b$ defined on the unit interval. There is also a killing measure $D$ supported on the unit interval as well. At branching times, a particle is chosen among all particles to the left of the branching one by sampling its rank according to $D$. The measure $D$ is allowed to have total mass less than one, which corresponds to a positive probability of no killing. Between branching times, particles perform independent Brownian Motions in the real line. This setting includes several well known models like Branching Brownian Motion (BBM), $N$-BBM, rank dependent BBM, and many others. We conjecture a scaling limit for this class of processes and prove such a limit for a related class of branching-selection particle system. This family is rich enough to allow us to use the behavior of solutions of the limiting equation to prove the asymptotic velocity of the rightmost particle under minimal conditions on $b$ and $D$. The behavior turns out to be universal and depends only on $b(1)$ and the total mass of $D$. If the total mass is one, the number of particles in the system $N$ is conserved and the velocities $v_N$ converge to $\sqrt{2 b(1)}$. When the total mass of $D$ is less than one, the number of particles in the system grows up in time exponentially fast and the asymptotic velocity of the rightmost one is $\sqrt{2 b(1)}$ independently of the number of initial particles.

First Principal Treatment of Size of Inflaton Potential, Inflaton Mass, Scale Factors, and Frequency of Emitted Radiation, Using Linde and Padmanabhan Models of Early Cosmology and BEC

Using a Linde reference, as well as another one from Padmanabhan for calculation of how the early universe expands, we obtain, by default the coefficient of scale factor expansion, t to the alpha value, with alpha being approximately the square root of five in value. We from there make an estimate as to the number of initial particles produced in the very beginning, which leads us to conclude that a graviton, would be a preferred initial by product. The argument as to gravitons, also reflects a choice of how the decay of initial BEC condensates of Planck sized black holes would commence, using the work produced by Chavanis, as to BEC condensates and black holes. The object will be to obtain initial frequency spread plus strength of GW production plus a suggestion as to what polarization state may be accessible from initial conditions.

Comprehensive Analysis of Magnetospheric Gaps around Kerr Black Holes Using 1D GRPIC Simulations

Abstract Spark gaps are likely the source of plasma in active black hole (BH) magnetospheres. In this paper, we present results of 1D general relativistic particle-in-cell simulations of a starved BH magnetosphere with a realistic treatment of inverse-Compton scattering and pair production, for a broad range of conditions, run times longer than in previous studies, and different setups. We find that following the initial discharge, the system undergoes gradual evolution over prolonged time until either restoring the vacuum state or reaching a state of quasiperiodic oscillations, depending on the spectral shape and luminosity of the ambient radiation field. The oscillations occur near the null charge surface in cases where the global magnetospheric current is in the direction defined by the product of the asymptotic Goldreich–Julian charge density and the radial velocity, while they occur near the boundary of the simulation box when it is the opposite direction (return current). Their amplitude and the resultant luminosity of TeV photons emitted from the gap depend sensitively on the conditions; for the cases studied here the ratio of TeV luminosity to the Blandford–Znajek power ranges from 10−5 to 10−2, suggesting that strong flares may be generated by moderate changes in disk emission. We also examined the dependence of the solution on the initial number of particles per cell (PPC) and found convergence for PPC of about 50 for the cases examined. At lower PPC values the pair multiplicity is found to be artificially high, affecting the solution considerably.

Numerical study on evolution of ultrafine particles emitted from vehicle exhaust with multi-dynamical behaviors

In this study, a numerical investigation is performed to simulate the evolution process of ultrafine particles emitted from diesel vehicle exhausts. The Taylor expansion method of moments (TEMOM)-CFD coupled model is primarily applied to the non-spherical particles for simultaneously simulating four kinds of particle dynamical behaviors including coagulation, deposition, condensation and nucleation. Compared with previous simulation studies, the developed model shows closer results to the experimental data. The effects of initial particle number, initial particle size, environmental temperature, relative humidity, fuel sulfur content, and exhaust velocity on the evolution process are systematically analyzed. The results show that the increase rate of the geometric mean diameter (GMD) and the increase margin of GMD are proportional to the initial particle number concentration (PNC) and the environmental temperature. When the relative humidity or the fuel sulfur content is higher, the larger increase margin of the GMD appears, but the increase rate of GMD is not affected obviously. Moreover, the initial PNC gives nearly no contributions to the diffusion range. The initial GMD also shows no markedly effects on the decrease rate of the volume concentration. The fuel sulfur content could affect the PNC distribution in a larger region of the flow field, while the environmental relative humidity and temperature have no evident effects on the distribution range of the PNC.

Mathematical modeling of vaporization process for a polydisperse ensemble of liquid drops

In this paper, we study the vaporization process of a polydisperse ensemble of liquid drops on the basis of a nonlinear set of balance and kinetics equations for the particle‐radius distribution function and temperature in the gaseous phase. We found an exact parametric solution to this problem using a modified time variable and the Laplace integral transform method. The distribution function of vaporizing drops as well as its moments, the temperature dynamics in gas, and the unvaporized mass of drops are found. The initial particle‐radius distribution shifts to smaller particle radii with increasing the vaporization time. As this takes place, the temperature difference between the drops and gas decreases with time. It is shown that the heat of vaporization and initial total number of particles in the system substantially influence the dynamics of a polydisperse ensemble of liquid drops.

Atmospheric aerosol properties at a semi-rural location in southern India: particle size distributions and implications for cloud droplet formation

Particle number size distributions in the diameter range of 5 nm–34 µm were measured in tropical southern India during the transition season from May (pre-monsoon) to June–July (monsoon). Averaged over the entire measurement period, the particle number size distributions were bimodal with a total particle number concentration of NTot = (4.5 ± 2.7) × 103 cm−3 (arithmetic mean ± standard deviation). The ratio of Aitken to accumulation mode particle number concentrations (NAit/NAcc) ranged from 1.06 to 2.07, increasing from May to June–July due to a pronounced decrease in the accumulation mode particles with the onset of the monsoon. Cloud condensation nuclei concentrations at 0.4% supersaturation (CCN0.4) were calculated under the assumption of an average continental hygroscopicity parameter of κ = 0.3. The calculated CCN0.4 concentrations are mostly sensitive to variations in NAcc and vary accordingly between the May and June–July. Using a cloud parcel model, we investigated the formation of cloud droplets using the measured average particle number size distributions, updraft velocities up to 20 m s−1, and initial aerosol particle number concentrations up to 25,000 cm−3. We found different regimes of CCN activation and cloud formation for the month of May (shifting from aerosol-limited regime to transitional regime) and for June–July (transitional regime), which was primarily due to the variability of particle number concentrations in the accumulation mode.

Diffusion-controlled coalescence, fragmentation, and collapse of d-dimensional A-particle islands in the B-particle sea.

We present a systematic analysis of diffusion-controlled interaction and collapse of two identical spatially separated d-dimensional A-particle islands in the B-particle sea at propagation of the sharp reaction front A+B→0 at equal species diffusivities. We show that at a sufficiently large initial distance between the centers of islands 2ℓ compared to their characteristic initial size and a relatively large initial ratio of island to sea concentrations, the evolution dynamics of the island-sea-island system is determined unambiguously by the dimensionless parameter Λ=N_{0}/N_{Ω}, where N_{0} is the initial particle number in the island and N_{Ω} is the initial number of sea particles in the volume Ω=(2ℓ)^{d}. It is established that (a) there is a d-dependent critical value Λ_{★} above which island coalescence occurs; (b) regardless of d the centers of each of the islands move toward each other along a universal trajectory merging in a united center at the d-dependent critical value Λ_{s}≥Λ_{★}; (c) in one-dimensional systems Λ_{★}=Λ_{s}, therefore, at Λ<Λ_{★} each of the islands dies individually, whereas at Λ>Λ_{★} coalescence is completed by collapse of a single-centered island in the system center; (d) in two- and three-dimensional systems in the range Λ_{★}<Λ<Λ_{s} coalescence is accompanied by subsequent fragmentation of a two-centered island and is completed by individual collapse of each of the islands. We discuss a detailed picture of coalescence, fragmentation, and collapse of islands focusing on evolution of their shape and on behavior of the relative width of the reaction front at the final collapse stage and in the vicinity of starting coalescence and fragmentation points. We demonstrate that in a wide range of parameters, the front remains sharp up to a narrow vicinity of the coalescence, fragmentation, and collapse points.