A multicomponent model for computing the thermal structure of collapsing protostellar clouds

A model for simulating the thermal and dynamical evolution of protostellar clouds is presented. In the model, the dust and gas temperatures are treated separately, making it possible to more precisely describe the initial stages of the cloud’s gravitational contraction and collapse. The model is fast enough to be applied in hydrodynamical computations, and has a high enough accuracy for the results to be used to compute emission spectra and comparing them with observational data. Two problems are considered as test examples and simple applications: calculation of the structure of clouds in thermal and hydrostatic equilibrium, and modeling the evolution of a protostellar cloud in a spherically symmetric approximation, including the formation of the first hydrostatic core.     

Self-similar regimes for the collapse of magnetic protostellar clouds

Self-similar solutions describing the homogeneous, free, isothermal collapse of protostellar clouds are considered. One such solution correponds to the critical case of the propagation of a rarefaction wave near the time when it is focused in the central region of the cloud. The speed of the rarefaction front is finite and equal to three times the isothermal sound speed. The asymptotic distributions of gas-dynamical quantities in the central part of the collapsing cloud and the surrounding envelopes are considered at both early and late stages of compression, after the formation of an opaque core (protostar). These solutions are used in a magneto-kinematic approximation to study the geometry and evolution of the large-scale magnetic fields of collapsing protostellar clouds. All the solutions are verified using direct numerical simulations. It is shown that an initially uniform magnetic field acquires an “hourglass” geometry with time. The characteristic opening angles in the self-similar solutions are in satisfactory agreement with observations.     

Determining the parameters of massive protostellar clouds via radiative transfer modeling

A one-dimensional method for reconstructing the structure of prestellar and protostellar clouds is presented. The method is based on radiative-transfer computations and a comparison of theoretical and observed intensity distributions at both millimeter and infrared wavelengths. The radiative transfer of dust emission is modeled for specified parameters of the density distribution, central star, and external background, and the theoretical distribution of the dust temperature inside the cloud is determined. The intensity distributions at millimeter and IR wavelengths are computed and quantitatively compared with observational data. The best-fit model parameters are determined using a genetic minimization algorithm, which makes it possible to reveal the ranges of parameter degeneracy as well. The method is illustrated by modeling the structure of two infrared dark clouds IRDC-320.27+029 (P2) and IRDC-321.73+005 (P2). The derived density and temperature distributions can be used to model the chemical structure and spectral maps in molecular lines.     

A coupled,dynamical and chemical model for the prestellar core L1544: Comparison of modeled and observed C<Superscript>18</Superscript>O,HCO<Superscript>+</Superscript>, and CS emission spectra

We consider radiative transfer in C¹⁸O, HCO⁺, and CS molecular lines in a spherically symmetrical, coupled, dynamical and chemical model of a prestellar core whose evolution is determined by ambipolar diffusion. Theoretical and observed line profiles are compared for the well-studied core L1544, which may be a collapsing protostellar cloud. We study the relationship between the line shapes and model parameters. The structure of the envelope and kinematic parameters of the cloud are the most important factors determining the shape of the lines. Varying the input model parameters for the radiative transfer—the kinetic temperature and microturbulent velocity—within the limits imposed by observations does not result in any substantial variations of the line profiles. The comparison between the model and observed spectra indicates that L1544 displays a flattened structure, and is viewed at an oblique angle. A two-dimensional model is needed to reproduce this structure.     

Modeling of rapid variability in the spectral line profiles of Wolf-Rayet stars

Profiles of variable emission lines in the spectra of Wolf-Rayet stars are calculated using a stochastic cloud model for the inhomogeneous atmospheres of early-type stars. The model assumes that most of the line flux is formed in cold, dense condensations (clouds) that move through a rarified inter-cloud medium whose density monotonically decreases outwards. The formation of clouds is taken to be stochastic. Wavelet analysis is used to estimate the parameters of cloud ensembles. The model can reproduce the general pattern of line-profile variability observed in the spectra of Wolf-Rayet stars.     

Research Status and Progress of Balloon-borne Cloud and Precipitation Particles Probe

The accurate observation of the microphysical structure of cloud and precipitation plays an important role in understanding the formation of clouds and precipitation. In-situ measurement using measuring instruments carried by meteorological balloons is an effective way to obtain the microphysical properties of cloud and precipitation particles, which is a supplementary means for aircraft to observe cloud and precipitation particles. This observation method plays a more and more important role in in-situ measurement. According to the difference of the working principle of the existing balloon-borne cloud and precipitation particles probes, the detectors can be divided into particle impact-sampling sensors, particle imaging sensors, light-scattering sensors, light intensity attenuation sensors and charge measurement sensors. The working principles, key technologies and main advantages and disadvantages of typical instruments were summarized, and their applications to detailed cloud structure acquisition, cloud remote sensing method establishment, cloud and precipitation physical process research and parameterization, and scientific observation of thunderstorm clouds were briefly introduced. Finally, the development trend of balloon-borne cloud precipitation particle detectors was prospected, which will provide reference for related technical research and equipment development.     

Self-similar focusing of rarefaction waves in relativistic collapsing clouds

The development of an inhomogeneous collapse of an initially homogeneous cloud in pressure equilibrium with an external medium is considered in a general-relativistic treatment. It is shown that a rarefaction wave propagating from the outer boundary toward the center of the cloud forms in the initial stage of the collapse. The rarefaction front moves through the collapsing gas at the sound speed, and separates the cloud material into an inner, uniform core and an outer, inhomogeneous envelope. Our analysis distinguishes two possible collapse regimes, depending on the ratio of the focusing time for the rarefaction wave and the free-fall time for the cloud. In massive clouds, the focusing time for the rarefaction wave exceeds the free-fall time, and the collapse of such clouds inevitably leads to the formation of an event horizon and black hole. In low-mass clouds, the focusing time is less than the free-fall time. After the focusing, the collapse of such clouds is fully inhomogeneous, and can be appreciably slowed by the pressure gradient. The compression of a cloud in a transitional regime separating these two scenarios is studied. In this case, a self-similar collapse regime is realized in the central part of the cloud near the focusing time for the rarefaction wave. The constructed self-similar solution describes both early stages in the compression up to the focusing of the rarefaction wave and later stages with the accretion of gas onto the black hole that is formed. Asymptotic distributions of quantities in the inhomogeneous region at large distances from the rarefaction front and in the accreting envelope are found. The structure of space-time in the vicinity of the black hole that is formed at the center of the cloud as a result of the focusing of the rarefaction wave is discussed.     

A method for molecular-line radiative-transfer computations and its application to a two-dimensional model for the starless core L1544

We present a numerical method and the URAN(IA) computer code for two-dimensional, axially symmetric radiative-transfer computations in molecular lines and spectral modeling. The algorithm is based on Monte Carlo computations of the mean radiation intensity and Accelerated Λ Iterations (ALI) to provide self-consistency between the radiation field and molecular excitation. The code is applied to the structure and kinematic properties of the starless core L1544, which is often considered to be the collapsing core of a molecular cloud. This object has been well studied, but none of the one-dimensional models obtained earlier has been able to provide a self-consistent picture of its structure and kinematics. We show that the spectral features of L1544 can be reproduced in a two-dimensional model in which the cloud has an axial ratio of 2: 1, a mean velocity of contraction (collapse) of V_r～50 m/s, and a rotational velocity of up to V _φ ～ 200 m/s. We construct the model of L1544 based on a continuous transition from an initially homogeneous cloud to the observed configuration. The velocity of the contraction is appreciably lower than is predicted by one-dimensional dynamical models. We discuss the problems of interpreting observed molecular-line profiles and prospects for developing self-consistent models for the chemical and dynamical evolution of molecular clouds.     

Using naive Bayes classifier for classification of convective rainfall intensities based on spectral characteristics retrieved from SEVIRI

This paper presents a new algorithm to classify convective clouds and determine their intensity, based on cloud physical properties retrieved from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The convective rainfall events at 15 min, 4 × 5 km spatial resolution from 2006 to 2012 are analysed over northern Algeria. The convective rain classification methodology makes use of the relationship between cloud spectral characteristics and cloud physical properties such as cloud water path (CWP), cloud phase (CP) and cloud top height (CTH). For this classification, a statistical method based on ‘naive Bayes classifier’ is applied. This is a simple probabilistic classifier based on applying ‘Bayes’ theorem with strong (naive) independent assumptions. For a 9-month period, the ability of SEVIRI to classify the rainfall intensity in the convective clouds is evaluated using weather radar over the northern Algeria. The results indicate an encouraging performance of the new algorithm for intensity differentiation of convective clouds using SEVIRI data.     

Circumstellar nebulae of WR and OB stars with strong winds: Simultaneous excitation by stellar radiation and shocks

We use a two-phase model for the structure of the circumstellar nebulae of hot stars to analyze the radiative cooling of a dense, compact cloud behind the shock produced by the compression of the cloud by hot gas from the stellar wind, taking into account ionization and heating by radiation from the central star. We can distinguish three stages of the evolution of the cloud during its compression. In the first stage, relevant for the entire cloud before compression and the gas ahead of the shock front, the state of the gas is determined purely by ionization by the stellar radiation. The next stage is characterized by the simultaneous action of two gas excitation mechanisms—photoionization by the stellar radiation and shock heating. In this stage, the gas intensively radiates thermal energy received at the shock front. After radiative cooling, in the final stage, ionization and heating of the gas are again determined mainly by the star. To compute the spectrum of the cloud radiation, we solved for the propagation of a plane-parallel, homogeneous flux through the shock front in the radiation field of the hot star. The computations show that a combination of two excitation mechanisms considerably enriches the theoretical spectrum. The relative intensities of emission lines of a single cloud may resemble either those for an HII region or of a supernova remnant.     

Formation of galactic shocks and the vertical structure of the gaseous disk of the galaxy in a “turbulent” interstellar medium

The effects on the formation of Galactic shocks and the vertical structure of the Galactic disk due to thermal processes in a cloudy interstellar medium as it flows through a spiral density wave in the plane of the Galactic disk are considered. The evolution of the gas is fundamentally different, depending on the thermal properties of the medium. For example, if it is compressed in the horizontal direction (parallel to the Galactic plane) by the gravitational forces of the spiral density waves responsible for the formation of spiral arms, an isothermal and adiabatic medium is swept out in the vertical direction. However, on the contrary, a medium whose volume loss function increases fairly rapidly with density and temperature is further compressed under the action of the overall gravitational field of the galaxy. This effect is referred to as “self-focusing,” and may serve as an additional mechanism to explain the recently discovered anticorrelation between the width of the atomic hydrogen layer in the Galaxy and the gas density. The difference in the vertical behavior of media with different thermal properties can be used as an indicator of the thermal properties of a particular component of the interstellar gas (atomic or molecular). Attention is drawn to the fact that Galactic shocks themselves represent a mechanism that can heat the ensemble of clouds, i.e., increase the dispersion of cloud velocities. The vertical structure of a Galactic shock front is constructed, which is in qualitative agreement with the “bow shock” inferred from radio data.     

The formation and evolution of the most massive stars

We consider the formation of massive stars under the assumption that a young star accretes material from the protostellar cloud through its accretion disk while losing gas in the polar directions via its stellar wind. The mass of the star reaches its maximum when the intensity of the gradually strengthening stellar wind of the young star becomes equal to the accretion rate. We show that the maximum mass of the forming stars increases with the temperature of gas in the protostellar cloud T ₀, since the rate at which the protostellar matter is accreted increases with T ₀. Numerical modeling indicates that the maximum mass of the forming stars increases to ～900 M _⊙ for T ₀ ～ 300 K. Such high temperatures of the protostellar gas can be reached either in dense star-formation regions or in the vicinity of bright active galactic nuclei. It is also shown that, the lower the abundance of heavy elements in the initial stellar material Z, the larger the maximum mass of the star, since the mass-loss rate due to the stellar wind decreases with decreasing Z. This suggests that supermassive stars with masses up to 10⁶ M _⊙ could be formed at early stages in the evolution of the Universe, in young galaxies that are almost devoid of heavy elements. Under the current conditions, for T ₀ = (30–100) K, the maximum mass of a star can reach ～100M _⊙, as is confirmed by observations. Another opportunity for the most massive stars to increase their masses emerges in connection with the formation and early stages of evolution of the most massive close binary systems: the most massive stars can be produced either by coalescence of the binary components or via mass transfer in such systems.     

基于CloudSat卫星资料的新疆三大山区不同类型云高特征研究

作为空中水资源的重要组成部分,云在地球水循环过程和气候系统中扮演着重要角色,不同高度的云因其物理特性和动力过程的不同而对人工增水作业具有不同的指示意义. 采用2007年1月至2008年12月的美国宇航局（NASA）云卫星（CloudSat） 2B-CLDCLASS资料,从不同类型云的高度分布特征分析了新疆阿尔泰山、天山和昆仑山区的云水资源情况.结果表明：各个季节三大山区高层云所占比例均较大,在20%以上,其中,天山山区和昆仑山区雨层云所占比例也较大,在15%以上. 三大山区不同云的云顶和云底高度年变化趋势基本一致,昆仑山区各类型云的平均云顶和云底的高度最大,阿尔泰山区的最低.     

Application of a 3D photorealistic model for the geological analysis of the Permian carbonates (Khuff Formation) in Saudi Arabia

Three dimensional (3D) photorealistic models of geological outcrops have the potential to enhance the teaching of earth sciences by providing scale models in a virtual reality environment. These models can be run on low-cost desktop computers. Photorealistic models for geological outcrops are a digital illustration of outcrop photographs with either a point cloud representation or Triangular Irregular Network (TIN) mesh of the outcrop surface. The level of detail for these models is dependent on the target resolutions (physical and optical) that were used during data acquisition. In addition, the technique in which the data is rendered as a digital model affects the level of detail that can be observed by the geologists. A colored point cloud representation is suitable for large-scale features, but fine details are lost when the geologist zooms in to view the model close up. In contrast, a photorealistic model that is constructed from photographs draped onto a triangle mesh surface derived from Light Detection and Ranging (LiDAR) point clouds provides a level of detail that is restricted only by the resolution of the photographs.     

Efficient execution of the WRF model and other HPC applications in the cloud

There are many scientific applications that have high performance computing (HPC) demands. Such demands are traditionally supported by cluster- or Grid-based systems. Cloud computing, which has experienced a tremendous growth, emerged as an approach to provide on-demand access to computing resources. The cloud computing paradigm offers a number of advantages over other distributed platforms. For example, the access to resources is flexible and cost-effective since it is not necessary to invest a large amount of money on a computing infrastructure nor pay salaries for maintenance functions. Therefore, the possibility of using cloud computing for running high performance computing applications is attractive. However, it has been shown elsewhere that current cloud computing platforms are not suitable for running some of these kinds of applications since the performance offered is very poor. The reason is mainly the overhead from virtualisation which is extensively used by most cloud computing platforms as a means to optimise resource usage. Furthermore, running HPC applications in current cloud platforms is a complex task that in many cases requires configuring a cluster of virtual machines (VMs). In this paper, we present a lightweight virtualisation approach for efficiently running the Weather Research and Forecasting (WRF) model (a computing- and communication-intensive application) in a cloud computing environment. Our approach also provides a higher-level programming model that automates the process of configuring a cluster of VMs. We assume such a cloud environment can be shared with other types of HPC applications such as mpiBLAST (an embarrassingly parallel application), and MiniFE (a memory-intensive application). Our experimental results show that lightweight virtualisation imposes about 5 % overhead and it substantially outperforms traditional heavyweight virtualisation such as KVM.     

条形基础极限承载力数值分析

根据塑性力学滑移线理论,推导了条形地基在极限平衡状态下的平衡微分方程,然后利用有限差分法推出地基土在极限状态时的有限差分公式,结合边界条件编制出地基承载力计算程序,该程序求解条形地基极限状态下的滑移线区域及相应的地基极限承载力值时可以考虑基础埋深、地基土重度、土的内摩擦角、基础与地基摩擦等参数。利用程序,得到了土的内摩擦角与地基承载力系数N? 的对应表,并全面讨论了基础埋深、地基土重度、内摩擦角及基础与地基摩擦角等参数对地基承载力和滑移线形状的影响,得到了一些有意义的结论。     

进化策略算法在地面沉降量计算参数反演中的应用

多数情况下,评估的研究区缺乏多年积累的地下水位及开采量资料。因此,通常采用土力学模型,根据太沙基固结理论,进行地面沉降量预测。在地面沉降量计算中,土层变形参数值的选取直接影响计算结果的精确性。深层含水层埋深通常大于100m。通过现场勘探,采取土样进行岩土物理力学性质试验获取参数值,成本过于昂贵。通过参考区域土层物理力学性质资料,结合工程经验获取参数值,预测结果的精度得不到保证。针对上述情况,作者提出用非线性优化算法-进化策略算法,根据实测地面沉降量反演土层变形参数值。通过这种方法确定参数值,既节约成本,又保证了计算结果的可靠性。进化策略算法通过模拟生物遗传及进化过程,利用转移概率来帮助指导搜索。搜索结果不依赖于初始点的选择,对于求解全局最优解有很强的鲁棒性。作者将进化策略算法用于某一工程实例土层变形参数的反演,结果表明了该算法的可行性及稳健性,值得在工程实践中推广应用。     

Guest Editorial to the Special Issue: Lessons Learned from post-2008 Wenchuan Earthquake Community Recovery

Identifying the spatial extent of volcanic ash clouds in the atmosphere and forecasting their direction and speed of movement has important implications for the safety of the aviation industry, community preparedness and disaster response at ground level. Nine regional Volcanic Ash Advisory Centres were established worldwide to detect, track and forecast the movement of volcanic ash clouds and provide advice to en route aircraft and other aviation assets potentially exposed to the hazards of volcanic ash. In the absence of timely ground observations, an ability to promptly detect the presence and distribution of volcanic ash generated by an eruption and predict the spatial and temporal dispersion of the resulting volcanic cloud is critical. This process relies greatly on the heavily manual task of monitoring remotely sensed satellite imagery and estimating the eruption source parameters (e.g. mass loading and plume height) needed to run dispersion models. An approach for automating the quick and efficient processing of next generation satellite imagery (big data) as it is generated, for the presence of volcanic clouds, without any constraint on the meteorological conditions, (i.e. obscuration by meteorological cloud) would be an asset to efforts in this space. An automated statistics and physics-based algorithm, the Automated Probabilistic Eruption Surveillance algorithm is presented here for auto-detecting volcanic clouds in satellite imagery and distinguishing them from meteorological cloud in near real time. Coupled with a gravity current model of early cloud growth, which uses the area of the volcanic cloud as the basis for mass measurements, the mass flux of particles into the volcanic cloud is estimated as a function of time, thus quantitatively characterising the evolution of the eruption, and allowing for rapid estimation of source parameters used in volcanic ash transport and dispersion models.

     

The nonthermal radio emission of WR 140 in a model with colliding two-phase winds

We present a model in which the nonthermal radio emission of binary systems containing Wolf-Rayet and O components is due to collisions between clouds belonging to dense phases of the wind of each star. The relativistic electrons are generated during the propagation of fast shock waves through the clouds and their subsequent de-excitation. The initial injection of superthermal particles is due to photoionization of the de-excited cold gas by hard radiation from the shock front. Therefore, the injection takes place in cloud regions fairly far from the front. Further, the superthermal electrons are accelerated by the betatron mechanism to relativistic energies during the isobaric compression of the cloud material, when most of the gas radiates its energy. Collisions between the clouds can occur far beyond the contact boundary between the rarefied wind components. Thus, the model avoids the problem of strong low-frequency absorption of the radiation.