Numerical Study on Discharging Characteristics of Pebble Cluster Flow in Pebble Bed

To better understand the flow features of pebble cluster in pebble bed, discharging of the pebble cluster were simulated by DEM. The pebble entangled cluster was composed of eight particles connected by rigid bonds and the simulated cluster models are divided into two types: axisymmetric u-particle and distorted z-particle. The simulation starts with the closed discharge outlet and the bonded clusters with different ID are randomly added from the entrance section. The pebbles fall freely and accumulate freely in the pebble bed. The discharge hole opens after all the pebbles being stationary for a period. Then the pebbles are discharged from the pebble bed under gravity. The discharging process is time-dependent bulk-movement behavior. There is not much mixing between layers on the boundary. The vertical end makes the packing loose, but also intensifies the interaction between particles due to entanglement. Consequently, the discharge features of pebble clusters of different included angles were quantified. The results show that the pebble discharging speeds depend on entanglement angle (α of u-particle and η of z-particle) and discharging outlet diameter. A large included angle may play the role of retarding or inhibiting the discharging flowrate. Therefore, the entanglement of particles component also always plays the key role of retarding the discharge.

Рентгеновские лазеры в потоках кластеров и в наноструктурированных мишенях

The paper presents a brief review of recent works concerning the modeling of X-ray lasers in cluster flows and in nanostructured targets. Calculations of the atomic characteristics are based on relativistic perturbation theory with a model potential of zero approximation. Two new results are discussed: (1) it is shown that a subpicosecond X-ray laser with λ = 41.8 nm formed in a xenon cluster flow can serve as an alternative to a free-electron laser and (2) in heavy Ni-like ions ( Z ≥ 60), the ionization of ions and recombination of electrons are balanced at electronic temperatures ≥1500 eV; thus, the state of a Ni-like ion is quasi-steady-state. The inversions of many transition levels of an X-ray laser are also quasi-steady-state. The possibility of experimental observation of X-ray lasers based on 3 p ^54 d ^104 p [ J = 0] – 3 p ^63 d ^94 p [ J = 1] intrashell transitions in Gd^36+ with wavelengths in the water window region is discussed.

Cluster Flow: A user-friendly bioinformatics workflow tool

Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.

Constructing Transit Origin–Destination Matrices with Spatial Clustering

So-called tap-in–tap-off smart card data have become increasingly available and popular as a result of the deployment of automatic fare collection systems on transit systems in many cities and areas worldwide. An opportunity to obtain much more accurate transit demand data than before has thus been opened to both researchers and practitioners. However, given that travelers in some cases can choose different origin and destination stations, as well as different transit lines, depending on their personal acceptable walking distances, being able to aggregate the demand of spatially close stations becomes essential when transit demand matrices are constructed. With the aim of investigating such problems using data-driven approaches, this paper proposes a k-means-based station aggregation method that can quantitatively determine the partitioning by considering both flow and spatial distance information. The method was applied to a case study of Haaglanden, Netherlands, with a specified objective of maximizing the ratio of average intra-cluster flow to average inter-cluster flow while maintaining the spatial compactness of all clusters. With a range of clustering of different K performed first using the distance feature, a distance-based metric and a flow-based metric were then computed and ultimately combined to determine the optimal number of clusters. The transit demand matrices constructed by implementing this method lay a foundation for further studies on short-term transit demand prediction and demand assignment.

Cluster Flow: A user-friendly bioinformatics workflow tool

Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.