Cloud Size Research Articles

Nonadiabatic Energy Fluctuations of Scale-Invariant Quantum Systems in a Time-Dependent Trap.

We consider the nonadiabatic energy fluctuations of a many-body system in a time-dependent harmonic trap. In the presence of scale-invariance, the dynamics becomes self-similar and the nondiabatic energy fluctuations can be found in terms of the initial expectation values of the second moments of the Hamiltonian, square position, and squeezing operators. Nonadiabatic features are expressed in terms of the scaling factor governing the size of the atomic cloud, which can be extracted from time-of-flight images. We apply this exact relation to a number of examples: the single-particle harmonic oscillator, the one-dimensional Calogero-Sutherland model, describing bosons with inverse-square interactions that includes the non-interacting Bose gas and the Tonks-Girdardeau gas as limiting cases, and the unitary Fermi gas. We illustrate these results for various expansion protocols involving sudden quenches of the trap frequency, linear ramps and shortcuts to adiabaticity. Our results pave the way to the experimental study of nonadiabatic energy fluctuations in driven quantum fluids.

Kinematics and Dynamics of Multiphase Outflows in Simulations of the Star-forming Galactic Interstellar Medium

Abstract Galactic outflows produced by stellar feedback are known to be multiphase in nature. Observations and simulations indicate that the material within several kiloparsecs of galactic disk midplanes consists of warm clouds embedded within a hot wind. A theoretical understanding of the outflow phenomenon, including both winds and fountain flows, requires study of the interactions among thermal phases. We develop a method to quantify these interactions via measurements of mass, momentum, and energy flux exchanges using temporally and spatially averaged quantities and conservation laws. We apply this method to a star-forming interstellar medium simulation based on the TIGRESS framework, for solar neighborhood conditions. To evaluate the extent of interactions among the phases, we examine the validity of the “ballistic model,” which predicts the trajectories of the warm phase (5050 K < T < 2 × 104 K) treated as non-interacting clouds. This model is successful at intermediate vertical velocities ( ), but at higher velocities, we observe an excess in simulated warm outflow compared to the ballistic model. This discrepancy cannot be fully accounted for by cooling of high-velocity, intermediate-temperature (2 × 104 K < T < 5 × 105 K) gas. We examine the fluxes of mass, momentum, and energy and conclude that the warm phase gains mass via cooling of the intermediate phase and momentum from the hot (T > 5 × 105 K) phase. The large energy flux from the hot outflow, transferred to the warm and intermediate phases, is quickly radiated away. A simple interaction model implies an effective warm cloud size in the fountain flow of a few 100 pc, showing that warm–hot flux exchange mainly involves a few large clouds rather than many small ones.

Expansion of the strongly interacting superfluid Fermi gas: Symmetries and self-similar regimes

We consider an expansion of the strongly interacting superfluid Fermi gas in a vacuum, assuming absence of the trapping potential, in the so-called unitary regime (see, for instance, \cite{pitaevskii2008superfluid}) when the chemical potential $\mu \propto \hbar^2n^{2/3}/m$ where $n$ is the density of the Bose-Einstein condensate of Cooper pairs of fermionic atoms. In low temperatures, $T\to 0$, such expansion can be described in the framework of the Gross-Pitaevskii equation (GPE). Because of the chemical potential dependence on the density, $\sim n^{2/3}$, the GPE has additional symmetries, resulting in the existence of the virial theorem \cite% {vlasov1971averaged}, connecting the mean size of the gas cloud and its Hamiltonian. It leads asymptotically at $t\to\infty$ to the gas cloud expansion, linearly growing in time. We study such asymptotics, and reveal the perfect match between the quasi-classical self-similar solution and the asymptotic expansion of the non-interacting gas. This match is governed by the virial theorem, derived through utilizing the Talanov transformation \cite{talanov1970focusing}, which was first obtained for the stationary self-focusing of light in media with a cubic nonlinearity due to the Kerr effect. In the quasi-classical limit, the equations of motion coincide with 3D hydrodynamics for the perfect monoatomic gas with $\gamma=5/3$. Their self-similar solution describes, on the background of the gas expansion, the angular deformities of the gas shape in the framework of the Ermakov--Ray--Reid type system.

On the temperature influence on cavitation erosion in micro-channels

The effect of fuel temperature on the erosion intensity in micro-channels for different fuels like calibration fluid ISO 4113 and dodecane is investigated. A high-pressure closed loop test bench for fuels under elevated temperatures up to 160 °C is used to erode micro-channels made of Al 99.0 at a maximum pressure of 500 bar. The evaluation of the erosion intensity reveals a temperature of maximum erosion for each fuel. The temperature of maximum erosion correlates with the temperature dependence of the maximum collapse pressure obtained by the Rayleigh-Plesset equation. Infrared thermography shows a local temperature drop in the cavitation region of the channels. 2D CFD simulations with a thermodynamic cavitation model supplement the measurement results by an assessment of the temporal evolution of the temperature field. Similar to the measurements, the CFD results yield a local cooling by the thermodynamic effect and thus support the measurement results. At high fluid temperatures one crucial link between the progressing local temperature drop and the erosion reduction is pointed out: the change of the detached cloud size distribution with temperature.

Cloud and Precipitation Properties of MCSs Along the Meiyu Frontal Zone in Central and Southern China and Their Associated Large‐Scale Environments

AbstractThis study focuses on investigating the cloud and precipitation features of Meiyu mesoscale convective systems (MCSs) and their relation to the large‐scale environments in central and southern China using satellite observations and reanalysis data during the period 2014–2018. MCSs from two different locations, the Yangtze River Basin (YRB) and Southern China (SC), are examined separately. The Meiyu MCSs have a mean precipitation rate of 3.6 mm/hr and contribute 20% to 60% of the total precipitation during the Meiyu period. The diurnal cycle of Meiyu MCSs shows a maximum precipitation amount in the morning, which is associated with the enhanced nocturnal low‐level jet (LLJ) overnight. Although the synoptic setups in YRB and SC are found to be similar when normalized around the MCS initiation locations, MCSs exhibit some differences in terms of the cloud top height, precipitation rate, and duration, which are likely by the differences in the local forcing. Large interannual variations are found in MCSs' number, cloud size, lifetime, and rainfall intensity, which is found to be associated with the interannual variabilities in the large‐scale environments. By comparing the large‐scale environments with climatological mean states, we find that the year with the most intense MCS activity during the study period is characterized by an intensified southwesterly LLJ, which increases the moisture transport from the Indian Ocean and an enhancement of the midtropospheric westerly jet, which induces adiabatic ascent along the Meiyu front, creating more favorable conditions for convection.

The Role of Cloud Size and Environmental Moisture in Shallow Cumulus Precipitation

AbstractCloud models show that precipitation is more likely to occur in larger shallow clouds and/or in an environment with more moisture, in part as a result of decreasing the impacts of entrainment mixing on the updrafts. However, the role of cloud size in shallow cloud precipitation onset from global satellite observations has mostly been examined with precipitation proxies from imagers and has not been systematically examined in active sensors, primarily because of sensitivity limitations of previous spaceborne active instruments. Here we use the more sensitive CloudSat/CALIPSO observations to identify and characterize the properties of individual contiguous shallow cumulus cloud objects. The objects are conditionally sampled by cloud-top height to determine the changes in precipitation likelihood with increasing cloud size and column water vapor. On average, raining shallow cumulus clouds are typically taller by a factor of 2 and have a greater horizontal extent than their nonraining counterparts. Results show that for a fixed cloud-top height the likelihood of precipitation increases with increasing cloud size and generally follows a double power-law distribution. This suggests that the smallest cloud objects are able to grow freely within the boundary layer but the largest cloud objects are limited by environmental moisture. This is supported by our results showing that, for a fixed cloud-top height and cloud size, the precipitation likelihood also increases as environmental moisture increases. These results are consistent with the hypothesis that larger clouds occurring in a wetter environment may be better able to protect their updrafts from entrainment effects, increasing their chances of raining.

Q-learning based dynamic task scheduling for energy-efficient cloud computing

High energy consumption has become a growing concern in the operation of complex cloud data centers due to the ever-expanding size of cloud computing facilities and the ever-increasing number of users. It is critical to find viable solutions to cloud task scheduling so that cloud resources can be utilized in an energy-efficient way while still meeting diverse user requirements in real time. In this research we propose a Q-learning based task scheduling framework for energy-efficient cloud computing (QEEC). QEEC has two phases. In the first phase a centralized task dispatcher is used to implement the M/M/S queueing model, by which the arriving user requests are assigned to each server in a cloud. In the second phase a Q-learning based scheduler on each server first prioritizes all the requests by task laxity and task life time, then uses a continuously-updating policy to assign tasks to virtual machines, applying incentives to reward the assignments that can minimize task response time and maximize each server’s CPU utilization. We have conducted simulation experiments, which have confirmed that implementing a M/M/S queueing system in a cloud can help to reduce the average task response time. The experiments have also demonstrated that the QEEC approach is the most energy-efficient as compared to other task scheduling policies, which can be largely credited to the M/M/S queueing model and the Q-learning strategy implemented in QEEC.

ConvPoint: Continuous convolutions for point cloud processing

Point clouds are unstructured and unordered data, as opposed to images. Thus, most machine learning approach developed for image cannot be directly transferred to point clouds. In this paper, we propose a generalization of discrete convolutional neural networks (CNNs) in order to deal with point clouds by replacing discrete kernels by continuous ones. This formulation is simple, allows arbitrary point cloud sizes and can easily be used for designing neural networks similarly to 2D CNNs. We present experimental results with various architectures, highlighting the flexibility of the proposed approach. We obtain competitive results compared to the state-of-the-art on shape classification, part segmentation and semantic segmentation for large-scale point clouds.

Numerical analysis of flammable vapour cloud formation from gasoline pool

In order to assess the potential hazard of oil and oil product spills, it is necessary to accurately determine the evaporation rate from the multi-component spill surface. In this paper, a multi-component pool evaporation model has been built and applied to the gasoline spill. The computational procedure has been implemented in the ANSYS Fluent code 18.0 through user-defined functions (UDFs). Gasoline is represented as a mixture consisting of a fixed number of individual components, and pseudo components (narrow boiling fractions). The model has been validated against the experimental data obtained in this study. The sensitivity analysis has been performed to assess the influence of wind velocity, pool thickness, and bund walls on the pool evaporation, the mass of vapour within the flammability limits, and the size of the flammable cloud for hypothetical gasoline spills.

Is multiphase gas cloudy or misty?

ABSTRACT Cold T ∼ 104 K gas morphology could span a spectrum ranging from large discrete clouds to a fine ‘mist’ in a hot medium. This has myriad implications, including dynamics and survival, radiative transfer, and resolution requirements for cosmological simulations. Here, we use 3D hydrodynamic simulations to study the pressure-driven fragmentation of cooling gas. This is a complex, multistage process, with an initial Rayleigh–Taylor unstable contraction phase that seeds perturbations, followed by a rapid, violent expansion leading to the dispersion of small cold gas ‘droplets’ in the vicinity of the gas cloud. Finally, due to turbulent motions, and cooling, these droplets may coagulate. Our results show that a gas cloud ‘shatters’ if it is sufficiently perturbed out of pressure balance (δP/P ∼ 1) and has a large final overdensity χf ≳ 300, with only a weak dependence on the cloud size. Otherwise, the droplets reassemble back into larger pieces. We discuss our results in the context of thermal instability and clouds embedded in a shock-heated environment.

Analyzing the instability dynamics of spherical complex astroclouds in a magnetized meanfluidic fabric

A generalized magnetohydrodynamic meanfluidic model is theoretically constructed to analyze the gravitational (Jeans) instability dynamics excitable in a spherical complex astrocloud on the non-relativistic classical astroscales of space and time. It concurrently includes the effects of viscoelasticity, buoyancy, polytropicity, volumetric thermal expansion, and so forth. Application of spherical normal mode analysis with no usual quasi-classic approximation over the non-Newtonian (Maxwellian) astrocloud yields a unique form of a generalized linear cubic dispersion relation. A numerical illustrative platform shows that the equilibrium temperature, polytropicity, viscoelastic relaxation time, effective generalized viscosity, and radial cloud size act as stabilizing agents to the excited gravito-magneto-acoustic instability. Conversely, the mean constitutive mass and magnetic field act as the cloud destabilizing factors against the inward non-local self-gravity. It is interestingly found that the magnetic field moderated in the presence of adopted non-ideality effects in the spherical astrocloud acts as a destabilizing agent against the typical landscape of stability influences by the unmoderated pure magnetic counterpart. It sets out a new theoretical support to the existing various astronomic observations on the magnetic field acting as a cloud destabilizing agency in the presence of geometrical curvature (spherical) effects widely reported in the literature.A generalized magnetohydrodynamic meanfluidic model is theoretically constructed to analyze the gravitational (Jeans) instability dynamics excitable in a spherical complex astrocloud on the non-relativistic classical astroscales of space and time. It concurrently includes the effects of viscoelasticity, buoyancy, polytropicity, volumetric thermal expansion, and so forth. Application of spherical normal mode analysis with no usual quasi-classic approximation over the non-Newtonian (Maxwellian) astrocloud yields a unique form of a generalized linear cubic dispersion relation. A numerical illustrative platform shows that the equilibrium temperature, polytropicity, viscoelastic relaxation time, effective generalized viscosity, and radial cloud size act as stabilizing agents to the excited gravito-magneto-acoustic instability. Conversely, the mean constitutive mass and magnetic field act as the cloud destabilizing factors against the inward non-local self-gravity. It is interestingly found that the magnetic fi...

The Added Value of Large-eddy and Storm-resolving Models for Simulating Clouds and Precipitation

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short), the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similarly to past studies we found an improved representation of precipitation at kilometer scales, as compared to models with parameterized convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simulations in these respects. It does, however, lead to a reduction in the precipitation on the time-scales considered – most notably over the ocean in the tropics. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hectometer scales. Hectometer scales appear to be more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, and to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when one reduces the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct connection between the circulation and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with already improved simulation as compared to more parameterized models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change.

Magnetized Dust Clouds Penetrating the Terrestrial Bow Shock Detected by Multiple Spacecraft

AbstractClouds of charged nanometer dust, produced in intra‐meteoroid collisions and accelerated by the magnetized solar wind, twist the interplanetary magnetic field as they are accelerated. Depending on the cloud size, minutes to hours‐long perturbations are observed by interplanetary spacecraft and have been termed interplanetary field enhancements (IFEs). This dust‐solar wind interaction hypothesis is supported by reconstructed magnetic field geometry using IFEs detected nearly simultaneously by multiple spacecraft. On 16 January 2018, an IFE was observed by eight spacecraft in the solar wind and later by four spacecraft in the magnetosheath, after the IFE crossed the bow shock. The post‐shock magnetic field geometry differed from that in the solar wind in a way compatible with the dust cloud having interacted with the shocked solar wind. These observations of dust clouds surfing in the solar wind show us how submicron‐sized interplanetary dust is transported and ultimately expelled from the solar system.

ОСОБЛИВОСТІ ФУНКЦІОНУВАННЯ ТА РОЗРОБКИ ТЕРМОБАРИЧНИХ БОЄПРИПАСІВ

У статті акцентовано увагу на особливості функціонування термобаричних вибухових речовин. Показано основні переваги та недоліки термобаричних вибухових речовин різних поколінь. Проведено оцінку стадій вибух термобаричних зарядів. Проаналізовано характер навантаження при оцінці уражаючої дії термобаричних вибухових речовин. Визначено, що характер навантаження пов'язаний зі співвідношенням тривалості фази стискання в ударній хвилі та періоду власних коливань об'єкта.

Fast non-rigid points registration with cluster correspondences projection

In this paper, we propose a fast non-rigid points registration method based on cluster correspondences projection. Firstly, a distance based clustering method is applied on the large scale points clouds. Then, the cluster centers are extract to represent the shape of the template and target object. After that, the target and template data are efficiently registered by an EM-like non-rigid registration method with a clustering projection between the cluster centers and all the points in the clusters. To more improve the computation efficiency, a fast deformation estimation is applied in reproducing kernel Hilbert space. As the size of cluster centers is much less than the size of the original point cloud and the cluster correspondences projection well keeps the points deformed smoothly in the clusters, the proposed method is robust and extremely efficient for large scale points registration with rigid and non-rigid deformations without loss accuracy. Experimental results show that, the efficiency of our approach outperforms on both synthesized and real datasets than the state-of-the-art methods under various types of distortions.

On the survival of cool clouds in the circumgalactic medium

ABSTRACT We explore the survival of cool clouds in multiphase circumgalactic media. We revisit the ‘cloud-crushing problem’ in a large survey of simulations including radiative cooling, self-shielding, self-gravity, magnetic fields, and anisotropic Braginskii conduction and viscosity (with saturation). We explore a wide range of parameters including cloud size, velocity, ambient temperature and density, and a variety of magnetic field configurations and cloud turbulence. We find that realistic magnetic fields and turbulence have weaker effects on cloud survival; the most important physics is radiative cooling and conduction. Self-gravity and self-shielding are important for clouds that are initially Jeans-unstable, but largely irrelevant otherwise. Non-self-gravitating, realistically magnetized clouds separate into four regimes: (1) at low column densities, clouds evaporate rapidly via conduction; (2) a ‘failed pressure confinement’ regime, where the ambient hot gas cools too rapidly to provide pressure confinement for the cloud; (3) an ‘infinitely long-lived’ regime, in which the cloud lifetime becomes longer than the cooling time of gas swept up in the leading bow shock, so the cloud begins to accrete and grow; and (4) a ‘classical cloud destruction’ regime, where clouds are eventually destroyed by instabilities. In the final regime, the cloud lifetime can exceed the naive cloud-crushing time owing to conduction-induced compression. However, small and/or slow-moving clouds can also evaporate more rapidly than the cloud-crushing time. We develop simple analytic models that explain the simulated cloud destruction times in this regime.

Effect of turbulent pressure on the origin of low-frequency quasi-periodic oscillations in rotating black holes

ABSTRACT Quasi-periodic oscillation (QPO), particularly of low frequency (LF), is a very obvious feature of outbursting black hole candidates. The association of QPOs in a specific spectral state and their transition with states make them a key ingredient in understanding the underlying physical processes that produce them. Observations have revealed that generally, in the hard spectral state of the outburst, the size of the Compton cloud is relatively bigger, which produces low-frequency QPOs (LFQPOs). In progressive days increased cooling shrinks the area of the cloud, the inner edge of the disc comes close to the black holes, and produces higher frequency QPOs. However, rotating black holes with higher spin values are likely to produce LFQPOs even if their inner edge of the disc is closer to the hole. Here, for the first time, we address the issue, solving hydrodynamic flow equations in the presence of qualitative turbulent pressure and cooling in pseudo-Kerr geometry. Increasing turbulence slackens the infalling flow, thus the infall time becomes longer, producing LFQPOs. Our study discovers that the effect of turbulence modifies LFQPOs value significantly, by a factor of a few lower throughout the angular momentum distribution of the flow. We find a strong correlation between the turbulence and the spin parameter of the hole. Finally, we discuss the observed results in light of the present solution.

On the model of the circumgalactic mist: the implications of cloud sizes in galactic winds and haloes

ABSTRACT Ubiquitous detections of cold/warm gas around galaxies indicate that the circumgalactic medium (CGM) is multiphase and dynamic. Recent state-of-the-art cosmological galaxy simulations have generally underproduced the column density of cold halo gas. We argue that this may be due to a mismatch of spatial resolution in the circumgalactic space and the relevant physical scales at which the cold gas operates. Using semi-analytic calculations and a set of magnetohydrodynamic simulations, we present a multiphase model of the gaseous haloes around galaxies, the circumgalactic mist (CGmist). The CGmist model is based on the idea that the observed cold halo gas may be a composite of cold, dense, and small cloudlets embedded in a hot diffuse halo, resembling terrestrial clouds and mist. We show that the resulting cold gas from thermal instabilities conforms to a characteristic column density of $N_{\rm H}\approx 10^{17}\, \rm {cm^{-2}}$ as predicted by the cstcool ansatz. The model implies a large number of cold clumps in the inner galactic halo with a small volume filling factor but a large covering fraction. The model also naturally gives rise to spatial extents and differential covering fractions of cold, warm, and hot gas. To self-consistently model the co-evolution of the CGM and star formation within galaxies, future simulations must address the mismatch of the spatial resolution and characteristic scale of cold gas.

The Dependence of Shallow Cumulus Macrophysical Properties on Large‐Scale Meteorology as Observed in ASTER Imagery

AbstractThis study identifies meteorological variables that control the macrophysical properties of shallow cumulus cloud fields over the tropical ocean. We use 1,158 high‐resolution Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER) images to derive properties of shallow cumuli, such as their size distribution, cloud top heights, fractal dimensions, and spatial organization, as well as cloud amount. The large‐scale meteorology is characterized by the lower‐tropospheric stability, subsidence rate, sea surface temperature, total column water vapor, wind speed, wind shear, and Bowen ratio. The surface wind speed emerges as the most powerful control factor. With increasing wind speed the cloud amount and cloud top heights show a robust increase accompanied by a marked shift in the cloud size distribution toward larger clouds with smoother shapes. These results lend observational support to the deepening response of a wind‐driven marine boundary layer as simulated by large‐eddy models. The other control factors cause smaller changes in the cloud field properties. We find a robust increase in cloud amount with increasing stability and decreasing sea surface temperature, respectively, which confirms a well‐known behavior of marine stratocumulus also for shallow cumulus clouds. Due to the high resolution of cloud images, we are able to study the lower end of the cloud size distribution and find a robust double power law behavior with a scale break at 590 m. We find a variation in the shape of the cloud size distribution with Bowen ratio, qualitatively consistent with modeling results and suggesting the Bowen ratio as a new potential control factor on shallow cumulus clouds.

Jeans smoothing of the Ly forest absorption lines

We investigate a contribution of the Jeans smoothing to the minimal width of Ly forest lines and discuss how the accounting for this additional broadening affects the inferred parameters of the intergalactic matter equation of state. We estimate a power-law index γ of the equation of state, a temperature at the mean density T0 and a hydrogen photoionization rate Γ within 4 redshift bins. Furthermore, in each bin we obtain an upper limit on the scale-parameter fJ, which sets the relation between the Jeans length and the characteristic physical size of the absorber clouds.