Cloud Dynamics Research Articles

Numerical Modeling of the Ash Cloud Movement from the Catastrophic Eruption of the Sheveluch Volcano in November 1964

This paper reconstructs, for the first time, the motion dynamics of an eruptive cloud formed during the catastrophic eruption of the Sheveluch volcano in November 1964 (Volcanic Explosivity Index 4+). This became possible due to the public availability of atmospheric reanalysis data from the ERA-40 archive of the European Center for Medium-Range Weather Forecasts (ECMWF) and the development of numerical modeling of volcanic ash cloud propagation. The simulation of the eruptive cloud motion process, which was carried out using the FALL3D and PUFF models, made it possible to clarify the sequence of events of this eruption (destruction of extrusive domes in the crater and the formation of an eruptive column and pyroclastic flows), which lasted only 1 h 12 min. During the eruption, the ash cloud consisted of two parts: the main eruptive cloud that rose up to 15,000 m above sea level (a.s.l.), and the co-ignimbrite cloud that formed above the moving pyroclastic flows. The ashfall in Ust-Kamchatsk (Kamchatka) first occurred out of the eruptive cloud moving at a higher speed, then out of the co-ignimbrite cloud. In Nikolskoye (Bering Island, Commander Islands), ash fell only out of the co-ignimbrite cloud. Under the turbulent diffusion, the forefront of the main eruptive cloud rose slowly in the atmosphere and reached 16,500 m a.s.l. by 04:07 UTC on November 12. Three days after the eruption began, the eruptive cloud stretched for 3000 km over the territories of the countries of Russia, Canada, the USA, Mexico, and over both the Bering Sea and the Pacific Ocean. It is assumed that the well-known long-term decrease in the solar radiation intensity in the northern latitudes from 1963–1966, which was established according to the world remote sensing data, was associated with the spread of aerosol clouds formed not only by the Agung volcano, but those formed during the 1964 Sheveluch volcano catastrophic eruption.

Radiation pressure on dust explaining the low ionized broad emission lines in active galactic nuclei

Context.Broad emission lines are the most characteristic features in the spectra of galaxies with an active galactic nucleus (AGN). They mostly show either single-peaked or double-peaked profiles and originate from a complex dynamics of the likely discrete clouds moving in a spatially extended region known as the broad line region (BLR).Aims.In this paper, we present a large grid of results, which is used to test the model based on calculations of the spectral line generic profiles.Methods.We followed a non-hydrodynamical single-cloud approach to BLR dynamics based on a radiatively dust-driven model. We previously showed in detail that the 2.5D version of the model could provide us with the 3D geometry of the BLR.Results.We show that the shape of profiles not only depends on the accretion rate of the source, the black hole mass, and the viewing angle, but it is most significantly affected by the adopted dust-to-gas mass ratio regulating the strength of the radiation pressure. We also show that the model can aptly explain the low ionized broad emission lines of the mean spectrum of quasars, such as MgII and Hβ.Conclusions.The radiatively dust-driving mechanism can appropriately account for the low-ionized part of BLR of AGNs.

Hybrid Kinetic Model of the Interaction Between the Dense Plasma Clouds and Magnetospheric Plasma on Large Time and Spatial Scales, and Comparison With MMS Observations

AbstractWe present a new simulation results of the cloud dynamics in the ambient magnetospheric plasma on the large time and spatial scales. It was assumed that these impulsive structures observed by the MMS spacecraft originally were created because of the reconnection at the magnetopause. Our new 3‐D hybrid kinetic modeling on the large time and spatial scales captures several of these processes: an excitation of the electromagnetic waves (whistler and shear‐Alfvén waves) and plasma instabilities (mirror and flute); a formation of shock waves, and collapsing diamagnetic cavity; particle acceleration. A strong overshoot in plasma density profile was observed in the modeling and MMS observation at the interface between the cloud and magnetospheric plasma. The cloud expansion into ambient magnetospheric plasma causes the flute waves connected with excitation of the Rayleigh‐Taylor instability observed at the overshoot in plasma density profile across the external magnetic field. The modeling demonstrates a formation of the whistler waves at the initial stage which propagate in the external magnetic field direction. At the later stage, a formation of shear‐Alfvén waves was observed.

Investigation of the Shielding and Attenuation Effects of a Dynamical High-Density Chaff Cloud on the Signal Based on Voxel Splitting

Chaff jamming is a widely used passive interference method. A chaff cloud diffusion model for the widespread chaff cloud was presented. The high-density chaff cloud aerodynamic model can rapidly predict the chaff elements’ time-varying spatial orientation, location, and overall spatial distribution. Basing on these pieces of information, the radar cross section (RCS) for the single chaff fibre can be obtained based on the method of moments (MoM). For high-density chaff clouds, the attenuation and shielding effects on the signal must be considered. This paper proposed a voxel splitting method in rotated coordinates, dividing the chaff cloud into rectangular cells with one side perpendicular to the direction of radar entry. The varied polarized RCS features of the chaff cloud were simulated and analysed on this foundation. By dividing the chaff cloud into dynamic voxels and considering the uneven density distribution of the chaff cloud and the signal attenuation in each segment caused by the continuous fluctuating shape, fine-grained simulations of the chaff cloud radar echoes can be performed.

Fluid Dynamics of Clouds

Fluid Dynamics of Clouds

Mind the Gap - Part 3: Doppler Velocity Measurements From Space

Convective motions and hydrometeor microphysical properties are highly sought-after parameters for evaluating atmospheric numerical models. With most of Earth’s surface covered by water, space-borne Doppler radars are ideal for acquiring such measurements at a global scale. While these systems have proven to be useful tools for retrieving cloud microphysical and dynamical properties from the ground, their adequacy and specific requirements for spaceborne operation still need to be evaluated. Comprehensive forward simulations enable us to assess the advantages and drawbacks of six different Doppler radar architectures currently planned or under consideration by space agencies for the study of cloud dynamics. Radar performance is examined against the state-of-the-art numerical model simulations of well-characterized shallow and deep, continental, and oceanic convective cases. Mean Doppler velocity (MDV) measurements collected at multiple frequencies (13, 35, and 94 GHz) provide complementary information in deep convective cloud systems. The high penetration capability of the 13 GHz radar enables to obtain a complete, albeit horizontally under-sampled, view of deep convective storms. The smaller instantaneous field of view (IFOV) of the 35 GHz radar captures more precise information about the location and size of convective updrafts above 5–8 km height of most systems which were determined in the portion of storms where the mass flux peak is typically located. Finally, the lower mean Doppler velocity uncertainty of displaced phase center antenna (DPCA) radars makes them an ideal system for studying microphysics in shallow convection and frontal systems, as well as ice and mixed-phase clouds. It is demonstrated that a 94 GHz DCPA system can achieve retrieval errors as low as 0.05–0.15 mm for raindrop volume-weighted mean diameter and 25% for rime fraction (for a −10 dBZ echo).

Impact of change in micro climatic factors forincidence and prevalence of powdery mildew diseasein Indian Sandalwood (Santalum album L.)

The summers are hot, while winters are getting cool at Bangalore, Karnataka, probably the possible effects of climate change. The changing climatic conditions have exaggerated the circumstances due to change in distribution pattern, epidemic development and new pathotypes of pest/disease (Yanez-Lopez 2012). The effect of local micro climatic conditions at IWST plays a major role in development of disease and rapid spread of inoculum. Some of the abiotic factors assessed during the study were temperature (t0), relative humidity (RH) and cloud dynamics (CD) determines the incidence of disease. The inoculum tends to manifold in larger quantity under conducive abiotic factor (t0, RH and CD) with a susceptible host (stress plants) and virulent pathogen. The prevailing management strategies for controlling of powdery mildew of S. album using either copper or sulphur fungicide were not found to be effective, which indicates the probability of resistance developed in pathogen. Therefore impact of climate change on plant disease is quiet an alarming situation, where the situation indirectly tells about the evolution of pathogen. It is high time to understand how climate change affects plant disease and host, therefore disease management against emerging and re-emerging pathogens through collaborative multi-facet discipline approaches may be better strategies under climate change

Experimental Investigation of Droplet Generation by Post-Breaking Plunger Waves

Understanding the droplet cloud and spray dynamics is important for the study of the ocean surface and marine boundary layer. The role that the wave energy and the type of wave breaking play in the resulting distribution and dynamics of droplets are yet to be understood. The aim of this work was to generate violent plunging breakers in the laboratory and analyze the spray production post-breaking, i.e. after the crest of the wave impacts in the free surface. The droplet sizes and their dynamics were measured with imaging techniques and the effect of different wind speeds on the droplet production was also considered. It was found that the mean radius increases with the wave energy content and the number of large droplets (radius > 1 mm) in the vertical direction increases with the presence of wind. Furthermore, the normalized distribution of droplet sizes is consistent with the distribution of ligament-mediated spray formation. Also, indications of turbulence affecting the droplet dynamics at wind speeds of 5 m/s were found. The amount of large droplets (radius > 1 mm) found in this work was larger than reported in field studies.

Impulse dispersion of aerosols during playing wind instruments.

Musical activities, especially singing and playing wind instruments, have been singled out as potentially high-risk activities for the transmission of SARS CoV-2, due to a higher rate of aerosol production and emission. Playing wind instruments can produce condensation, droplets of saliva, and aerosol particles, which hover and spread in the environmental air’s convectional flows and which can be potentially infectious. The aim of this study is to investigate the primary impulse dispersion of aerosols that takes place during the playing of different wind instruments as compared to breathing and to speaking. Nine professional musicians (3 trumpeters, 3 flautists and 3 clarinetists) from the Bavarian Symphony Orchestra performed the main theme from the 4th movement of Ludwig van Beethoven‘s 9th symphony in different pitches and loudness. The inhaled air volume was marked with small aerosol particles produced using a commercial e-cigarette. The expelled aerosol cloud was recorded by cameras from different perspectives. Afterwards, the dimensions and dynamics of the aerosol cloud were measured by segmenting the video footage at every time point. Overall, the flutes produced the largest dispersion at the end of the task, reaching maximum forward distances of 1.88 m. An expulsion of aerosol was observed in different directions: upwards and downwards at the mouthpiece, at the end of the instrument, and along the flute at the key plane. In comparison, the maximum impulse dispersions generated by the trumpets and clarinets were lower in frontal and lateral direction (1.2 m and 1.0 m towards the front, respectively). Also, the expulsion to the sides was lower.

Convective and Turbulent Motions in Nonprecipitating Cu. Part II: LES Simulated Cloud Represented by a Starting Plume

Abstract The dynamic structure of a small trade wind cumulus (Cu) is analyzed using a novel approach. Cu developing in a shear-free environment is simulated by 10-m-resolution LES model with spectral bin microphysics. The aim is to clarify the dynamical nature of cloud updraft zone (CUZ) including entrainment and mixing in growing Cu. The validity of concept stating that a cloud at developing state can be represented by a parcel or a jet is tested. To investigate dynamical entrainment in CUZ performed by motions with scales larger than the turbulence scales, the modeled fields of air velocity were filtered by wavelet filter that separated convective motions from turbulent ones. Two types of objects in developing cloud were investigated: small volume ascending at maximal velocity (point parcel) and CUZ. It was found that the point parcel representing the upper part of cloud core is adiabatic. The motion of the air in this parcel ascending from cloud base determines cloud-top height. The top-hat (i.e., averaged) values of updraft velocity and adiabatic fraction in CUZ are substantially lower than those in the point parcel. Evaluation of the terms in the dynamical equation typically used in 1D cloud parcel models show that this equation can be applied for calculation of vertical velocities at the developing stage of small Cu, at least up to the heights of the inversion layer. Dynamically, the CUZ of developing cloud resembles the starting plume with the tail of nonstationary jet. Both the top-hat vertical velocity and buoyancy acceleration linearly increase with the height, at least up to the inversion layer. An important finding is that lateral entrainment of convective (nonturbulent) nature has a little effect on the top-hat CUZ velocity and cannot explain the vertical changes of conservative variables qt and θl. In contrast, entrained air lifting inside CUZ substantially decreases top-hat liquid water content and its adiabatic fraction. Possible reasons of these effects are discussed. Significance Statement (i) The study improves the understanding of the effects of lateral entrainment and mixing. (ii) The study shows the dominating role of the convective-scale motions in cloud microphysics and dynamics. (iii) The comparison of results of 10-m-resolution large-eddy simulations with a simple cloud model allows evaluating validity of current schemes of convective parameterization.

Dynamics of the Cloud–Environment Interface and Turbulence Effects in an LES of a Growing Cumulus Congestus

AbstractA giga-large-eddy simulation of a cumulus congestus has been performed with a 5-m resolution to examine the fine-scale dynamics and mixing on its edges. At 5-m resolution, the dynamical production of subgrid turbulence clearly dominates over the thermal production, whereas the situation is reversed for resolved turbulence, the tipping point occurring near the 250-m scale. For cloud dynamics, the toroidal circulation already obtained in previous observational and numerical studies remains, with a strong signature on the resolved turbulent fluxes, the most important feature for the exchanges between the cloud and its environment even though numerous smaller eddies are also well resolved. The environment compensates for the upward mass flux through a large-scale compensating subsidence and the so-called subsiding shell composed of cloud-edge downdrafts, both having a significant contribution. A partition is used to characterize the dynamics, buoyancy, and turbulence of the inner and outer edges of the cloud, the cloud interior, and the far environment. On the edges of the cloud, downdrafts caused by the eddies and by evaporative cooling effects coexist with a buoyancy reversal while the cloud interior is mostly rising and positively buoyant. An alternative simulation in which evaporative cooling is suppressed indicates that this process reinforces the downdrafts near the edges of the cloud and causes a general decrease of the convective circulation. Evaporative cooling also has an impact on the buoyancy reversal and on the fate of the engulfed air inside the cloud.

Combined Effect of the Wegener–Bergeron–Findeisen Mechanism and Large Eddies on Microphysics of Mixed-Phase Stratiform Clouds

Abstract The process of glaciation in mixed-phase stratiform clouds was investigated by a novel Lagrangian–Eulerian model (LEM) in which thousands of adjoining Lagrangian parcels moved within a turbulent-like velocity field with statistical parameters typical of the Arctic boundary layer. We used detailed bin microphysics to describe the condensation/evaporation processes in each parcel, in which droplets, aerosols, and ice particles were described using size distributions of 500 mass bins. The model also calculated aerosol mass inside droplets and ice particles. Gravitational sedimentation of droplets and ice particles was also accounted for. Assuming that droplet freezing is the primary source of ice particles, the Arctic clouds observed in Indirect and Semi-Direct Aerosol Campaign (ISDAC) were successfully simulated. The model showed that at a low ice particle concentration typical of ISDAC, large vortices (eddies) led to a quasi-stationary regime, in which mixed-phase St existed for a long time. The large eddies controlled the water partitioning in the mixed-phase clouds. Droplets formed and grew in updrafts, typically reaching the cloud top, and evaporated in downdrafts. Ice particles grew in updrafts and downdrafts. The Wegener–Bergeron–Findeisen (WBF) mechanism was efficient in downdrafts and some parts of updrafts, depending on ice concentration and vertical velocity. At low ice concentrations, the effect of ice on the phase partitioning was negligible. In this regime, liquid droplets were found near the cloud top, whereas ice particles precipitated through the cloud base. When ice concentration exceeded about 10 L−1, the WBF mechanism led to glaciation of almost the entire cloud, with the exception of narrow cloud regions associated with strong updrafts. At ice particle concentrations of a few tens per liter, the oscillatory regime took place due to the ice–liquid interaction. The microphysical structure of mixed-phase St forms as a combined effect of cloud dynamics (large eddies) and the WBF mechanism.

Evaluating cloud liquid detection against Cloudnet using cloud radar Doppler spectra in a pre-trained artificial neural network

Abstract. Detection of liquid-containing cloud layers in thick mixed-phase clouds or multi-layer cloud situations from ground-based remote-sensing instruments still poses observational challenges, yet improvements are crucial since the existence of multi-layer liquid layers in mixed-phase cloud situations influences cloud radiative effects, cloud lifetime, and precipitation formation processes. Hydrometeor target classifications such as from Cloudnet that require a lidar signal for the classification of liquid are limited to the maximum height of lidar signal penetration and thus often lead to underestimations of liquid-containing cloud layers. Here we evaluate the Cloudnet liquid detection against the approach of Luke et al. (2010) which extracts morphological features in cloud-penetrating cloud radar Doppler spectra measurements in an artificial neural network (ANN) approach to classify liquid beyond full lidar signal attenuation based on the simulation of the two lidar parameters particle backscatter coefficient and particle depolarization ratio. We show that the ANN of Luke et al. (2010) which was trained under Arctic conditions can successfully be applied to observations at the mid-latitudes obtained during the 7-week-long ACCEPT field experiment in Cabauw, the Netherlands, in 2014. In a sensitivity study covering the whole duration of the ACCEPT campaign, different liquid-detection thresholds for ANN-predicted lidar variables are applied and evaluated against the Cloudnet target classification. Independent validation of the liquid mask from the standard Cloudnet target classification against the ANN-based technique is realized by comparisons to observations of microwave radiometer liquid-water path, ceilometer liquid-layer base altitude, and radiosonde relative humidity. In addition, a case-study comparison against the cloud feature mask detected by the space-borne lidar aboard the CALIPSO satellite is presented. Three conclusions were drawn from the investigation. First, it was found that the threshold selection criteria of liquid-related lidar backscatter and depolarization alone control the liquid detection considerably. Second, all threshold values used in the ANN framework were found to outperform the Cloudnet target classification for deep or multi-layer cloud situations where the lidar signal is fully attenuated within low liquid layers and the cloud radar is able to detect the microphysical fingerprint of liquid in higher cloud layers. Third, if lidar data are available, Cloudnet is at least as good as the ANN. The times when Cloudnet outperforms the ANN in liquid detections are often associated with situations where cloud dynamics smear the imprint of cloud microphysics on the radar Doppler spectra.

Breaking wave bubble measurements around ship model by optical probe

The bubble sweep-down phenomenon around oceanographic research vessels generates acoustic disturbances. The phenomenon can be reproduced on a 1/30 scale ship model in a wave and current circulating flume tank taking into account ship motions. Optical probe can then be used to measure locally the size and the velocity of the bubbles generated by breaking waves. A comparison of the obtained results with more classical results obtained from bubble detection by image tracking is discussed. The two methods provide complementary results for bubble characteristics. However, bubble detection by optical probe has the advantage of knowing the bubble position in the three dimensions of space. The overall results of this paper provide new elements for the study and the understanding of the bubble sweep-down phenomenon in addition to previous 2D and 3D studies, where the dynamics of bubble clouds have been characterized.

Seasonal Cycle of Idealized Polar Clouds: Large Eddy Simulations Driven by a GCM

AbstractThe uncertainty in polar cloud feedbacks calls for process understanding of the cloud response to climate warming. As an initial step toward improved process understanding, we investigate the seasonal cycle of polar clouds in the current climate by adopting a novel modeling framework using large eddy simulations (LES), which explicitly resolve cloud dynamics. Resolved horizontal and vertical advection of heat and moisture from an idealized general circulation model (GCM) are prescribed as forcing in the LES. The LES are also forced with prescribed sea ice thickness, but surface temperature, atmospheric temperature, and moisture evolve freely without nudging. A semigray radiative transfer scheme without water vapor and cloud feedbacks allows the GCM and LES to achieve closed energy budgets more easily than would be possible with more complex schemes. This enables the mean states in the two models to be consistently compared, without the added complications from interaction with more comprehensive radiation. We show that the LES closely follow the GCM seasonal cycle, and the seasonal cycle of low‐level clouds in the LES resembles observations: maximum cloud liquid occurs in late summer and early autumn, and winter clouds are dominated by ice in the upper troposphere. Large‐scale advection of moisture provides the main source of water vapor for the liquid‐containing clouds in summer, while a temperature advection peak in winter makes the atmosphere relatively dry and reduces cloud condensate. The framework we develop and employ can be used broadly for studying cloud processes and the response of polar clouds to climate warming.

Data-Driven Cloud Clustering via a Rotationally Invariant Autoencoder

Advanced satellite-born remote sensing instruments produce high-resolution multi-spectral data for much of the globe at a daily cadence. These datasets open up the possibility of improved understanding of cloud dynamics and feedback, which remain the biggest source of uncertainty in global climate model projections. As a step towards answering these questions, we describe an automated rotation-invariant cloud clustering (RICC) method that leverages deep learning autoencoder technology to organize cloud imagery within large datasets in an unsupervised fashion, free from assumptions about predefined classes. We describe both the design and implementation of this method and its evaluation, which uses a sequence of testing protocols to determine whether the resulting clusters: (1) are physically reasonable, (i.e., embody scientifically relevant distinctions); (2) capture information on spatial distributions, such as textures; (3) are cohesive and separable in latent space; and (4) are rotationally invariant, (i.e., insensitive to the orientation of an image). Results obtained when these evaluation protocols are applied to RICC outputs suggest that the resultant novel cloud clusters capture meaningful aspects of cloud physics, are appropriately spatially coherent, and are invariant to orientations of input images. Our results support the possibility of using an unsupervised data-driven approach for automated clustering and pattern discovery in cloud imagery.

Infrared signatures of a quantum bounce in a minisuperspace analysis of Lemaître-Tolman-Bondi dust collapse

In the quantum treatment of collapsing matter, a viable mode analysis is supposed to give information regarding emission during the collapse. Nevertheless, partly owing to operator ordering ambiguities involved in a typical quantum gravity analysis, the availability of such well-defined modes is not guaranteed. We study the mode decomposition of the unitarily evolving wave packet constructed for the quantum model of spherically symmetric dust collapsing in a marginally bound Lema\^{\i}tre-Tolman-Bondi (LTB) model. We identify the observable depicting mode decomposition, and using the freedom of operator ordering ambiguity, we obtain the Hermitian extension of this operator alongside the Hermitian Hamiltonian. After identifying incoming and outgoing modes with this operator's eigenstates, we estimate their contributions to the radiation profile. The infrared sector of this process demonstrates some characteristic features which turn out to be highly sensitive to the near-bounce dynamics of the dust cloud. Near the epoch of classical singularity, there is a significant contribution from incoming/outgoing modes of small wavenumber in the expanding/collapsing phase of the dust cloud, which keeps on decreasing as one moves away from the singularity. The information of the bounce is carried over to the infrared modes through a flip from largely incoming to largely outgoing radiation as the evolution progresses from collapsing to expanding phase, much before the information of bounce comes about to any observer. In the infrared sector, the saturation value of the amplitude marks the bounce radius. Thus, we argue that the information of the short scale physics is essentially carried over to the longest wavelength in this quantum gravity model, which we argue is rather more prominent for low energy processes.

Meteorites that produce K-feldspar-rich ejecta blankets correspond to mass extinctions

Meteorite impacts load the atmosphere with dust and cover the Earth's surface with debris. They have long been debated as a trigger of mass extinctions throughout Earth history. Impact winters generally last <10 0 years, whereas ejecta blankets persist for 10 3 –10 5 years. We show that only meteorite impacts that emplaced ejecta blankets rich in K-feldspar (Kfs) correlate to Earth system crises ( n = 11, p < 0.000005). Kfs is a powerful ice-nucleating aerosol, yet is normally rare in atmospheric dust mineralogy. Ice nucleation plays an important part in cloud microphysics, which modulates the global albedo. A conceptual model is proposed whereby the anomalous presence of Kfs post impact is posited to have two key effects on cloud dynamics: (1) Kfs reduces the average albedo of mixed-phase clouds, which leads to a hotter climate; and (2) Kfs weakens the cloud albedo feedback mechanism, which increases climate sensitivity. These mechanisms offer an explanation as to why this otherwise benign mineral is correlated so strongly with mass extinction events: every Kfs-rich ejecta blanket corresponds to a severe extinction episode over the last 600 myr. This model may also explain why many kill mechanisms only variably correlate with extinction events through geological time: they coincide with these rare periods of climate destabilization by atmospheric Kfs. Supplementary material : Extended Fig. 1 from main text is available at https://doi.org/10.6084/m9.figshare.c.5690646

A Lagrangian-Relaxation-Based Approach for Service Function Chain Dynamic Orchestration for the Internet of Things

Network function virtualization and multiaccess edge computing have been introduced by Internet service providers to deal with various challenges, which hinder them from satisfying the increasing demand of the low-latency network applications for the Internet of Things (IoT). In edge clouds, any network application for the IoT can be expressed as a service function chain (SFC) consisting of several strictly ordered virtual network functions (VNFs), which can be geographically placed onto edge clouds close to the terminals. However, regarding the large number of terminals and constantly dynamics of edge clouds, determining the placement of VNFs and routing service paths that optimizes the end-to-end delays is a challenging problem. This problem can be also called SFC dynamic orchestration problem. To exactly solve the problem, an integer linear programming (ILP) model is formulated. Then, it is difficult to apply the exact method to deal with the SFC dynamic orchestration problem in the large-scale networks, and this article presents a Lagrangian relaxation heuristic-based algorithm for the optimization, thus reducing the computational complexity. It is demonstrated that the proposed algorithm can efficiently achieve a near-optimal solution with a theoretical analysis. The obtained simulation results show that the proposed algorithm can approximate the performance of ILP’s solution and outperform the current benchmarks in terms of the end-to-end delay and service acceptance ratio.

ОЦЕНКА ВЛИЯНИЯ ОБЪЕМНОГО ЗАРЯДА НА РАЗРЕШЕНИЕ ИОН-ДРЕЙФОВОГО СПЕКТРОМЕТРА

The paper presents an analytical model describing the dynamics of ion cloud, taking into account the action of space charge during a motion in ion mobility spectrometer — starting from the reaction region, where the shutter forms an ion pulse, and the further drift of the formed ion pulse towards the collector. The presented model lets to estimate the degree of influence of the space charge on possible ion losses and the resolution of ion mobility spectrometer. The effect of the space charge becomes noticeable, starting with the ion density of 106 cm–3. Comparison of the results obtained using the analytical model with the results of numerical solution of the initial equations shows that they practically coincide.