Streaks to Rings to Vortex Grids: Generic Patterns in Transient Convective Spin-Up

We observe the transient formation of a ringed pattern state during spin-up of an evaporating fluid on a time scale of order a few Ekman spin-up times. The ringed state is probed using infrared thermometry and particle image velocimetry and it is demonstrated to be a consequence of the transient balance between Coriolis and viscous forces which dominate inertia, each of which are extracted from the measured velocity field. The breakdown of the ringed state is quantified in terms of the antiphasing of these force components which drives a Kelvin-Helmholtz instability and we show that the resulting vortex grid spacing scales with the ring wavelength. This is the fundamental route to quasi-two dimensional turbulent vortex flow and thus may have implications in astrophysics and geophysics wherein rotating convection is ubiquitous. sics.Comment: 4 pages, 5 figure

Power generation expansion planning model towards low-carbon economy and its application in china

Climate change poses a huge threat to human welfare. Hence, developing a low-carbon economy has become a prevailing and inevitable trend. Decarbonization of power generation, especially converting the current power mix into a low-carbon structure, will be a critical option for CO2 emission mitigation. In this paper, an integrated power generation expansion (PGE) planning model towards low-carbon economy is proposed, which properly integrates and formulates the impacts of various low-carbon factors on PGE models. In order to adapt to the characteristics of PGE models based on low-carbon scenario, a compromised modeling approach is presented, which reasonably decreases complexities of the model, while properly keeping the significant elements and maintaining moderate precision degree. In order to illustrate the proposed model and approach, a numerical case is studied based on the background of China's power sector, making decisions on the optimal PGE plans and revealing the prospects and potentials for CO2 emission reduction. © 2010 IEEE.published_or_final_versio

Retraction of articles by H. Zhong et al.

Retraction of 41 articles by H. Zhong et al.

Strangeness spin, magnetic moment and strangeness configurations of the proton

The implications of the empirical signatures for the positivity of the strangeness magnetic moment $\mu_s$, and the negativity of the strangeness contribution to the proton spin $\Delta_s$, on the possible $uuds\bar s$ configurations of five quarks in the proton are analyzed. The empirical signs for the values of these two observables can only be obtained in configurations where the $uuds$ system is orbitally excited and the $\bar s$ quark is in the ground state. The configurations, in which the $\bar s$ is orbitally excited, which include the conventional $K^+\Lambda^0$ congfiguration, with the exception of that, in which the $uuds$ component has spin 2, yield negative values for $\mu_s$. Here the strangeness spin $\Delta_s$, the strangeness magnetic moment $\mu_s$ and the axial coupling constant $G_A^s$ are calculated for all possible configurations of the $uuds\bar s$ component of the proton. In the configuration with $[4]_{FS}[22]_F[22]_S$ flavor-spin symmetry, which is likely to have the lowest energy, $\mu_s$ is positive and $\Delta_s\simeq G_A^s\simeq -1/3\mu_s$.Comment: 17 page

Analysis of the characteristics of DC nozzle arcs in air and guidance for the search of SF6 replacement gas

It is shown that the arc model based on laminar flow cannot predict satisfactorily the voltage of an air arc burning in a supersonic nozzle. The Prandtl mixing length model (PML) and a modified k-epsilon turbulence model (MKE) are used to introduce turbulence enhanced momentum and energy transport. Arc voltages predicted by these two turbulence models are in good agreement with experiments at the stagnation pressure (P 0) of 10 bar. The predicted arc voltages by MKE for P 0  =  13 bar and 7 bar are in better agreement with experiments than those predicted by PML. MKE is therefore a preferred turbulence model for an air nozzle arc. There are two peaks in ρC P of air at 4000 K and 7000 K due, respectively, to the dissociation of oxygen and that of nitrogen. These peaks produce corresponding peaks in turbulent thermal conductivity, which results in very broad radial temperature profile and a large arc radius. Thus, turbulence indirectly enhances axial enthalpy transport, which becomes the dominant energy transport process for the overall energy balance of the arc column at high currents. When the current reduces, turbulent thermal conduction gradually becomes dominant. The temperature dependence of ρC P has a decisive influence on the radial temperature profile of a turbulent arc, thus the thermal interruption capability of a gas. Comparison between ρC P for air and SF6 shows that ρC P for SF6 has peaks below 4000 K. This renders a distinctive arc core and a small arc radius for turbulent SF6, thus superior arc quenching capability. It is suggested, for the first time, that ρC P provides guidance for the search of a replacement switching gas for SF6

A community merger of optimization algorithm to extract overlapping communities in networks

© 2018 IEEE. A community in networks is a subset of vertices primarily connecting internal components, yet less connecting to the external vertices. The existing algorithms aim to extract communities of the topological features in networks. However, the edges of practical complex networks involving a weight that represents the tightness degree of connection and robustness, which leads a significant influence on the accuracy of community detection. In our study, we propose an overlapping community detection method based on the seed expansion strategy applying to both the unweighted and the weighted networks, called OCSE. First, it redefines the edge weight and the vertex weight depending on the influence of the network topology and the original edge weight, and then selects the seed vertices and updates the edges weight. Comparisons between OCSE approach and existing community detection methods on synthetic and real-world networks, the results of the experiment show that our proposed approach has the significantly better performance in terms of the accuracy

Celebrities-ReID: A Benchmark for Clothes Variation in Long-Term Person Re-Identification

© 2019 IEEE. This paper considers person re-identification (re-ID) in the case of long-time gap (i.e., long-term re-ID) that concentrates on the challenge of clothes variation of each person. We introduce a new dataset, named Celebrities-reID to handle that challenge. Compared with current datasets, the proposed Celebrities-reID dataset is featured in two aspects. First, it contains 590 persons with 10,842 images, and each person does not wear the same clothing twice, making it the largest clothes variation person re-ID dataset to date. Second, a comprehensive evaluation using state of the arts is carried out to verify the feasibility and new challenge exposed by this dataset. In addition, we propose a benchmark approach to the dataset where a two-step fine-tuning strategy on human body parts is introduced to tackle the challenge of clothes variation. In experiments, we evaluate the feasibility and quality of the proposed Celebrities-reID dataset. The experimental results demonstrate that the proposed benchmark approach is not only able to best tackle clothes variation shown in our dataset but also achieves competitive performance on a widely used person re-ID dataset Market1501, which further proves the reliability of the proposed benchmark approach