Cooling of strange stars in the color-flavor locked phase with a rotating crust Cooling of strange stars in the color-flavor locked phase with a rotating crust

The presence of the color-flavor locked (CFL) phase strongly suppresses the neutrino emission processes and the quark specific heat. As a result the cooling of the strange stars in the CFL phase is dominated by deconfinement heating and surface emission. The temperature of these stars with strong magnetic field ($B{\geq}10^{10}G$) rise significantly during the first several ten or hundred years, which may be an effective signature of strange stars as implicated by pulsar 0540-69. Furthermore a limit line is predicted, which means compact stars have an upper limit temperature at any moment. We still may search for the candidates for strange stars in the CFL phase along the limit line. The presence of the color-flavor locked (CFL) phase strongly suppresses the neutrino emission processes and the quark specific heat. As a result the cooling of the strange stars in the CFL phase is dominated by deconfinement heating and surface emission. The temperature of these stars with strong magnetic field ($B{\geq}10^{10}G$) rise significantly during the first several ten or hundred years, which may be an effective signature of strange stars as implicated by pulsar 0540-69. Furthermore a limit line is predicted, which means compact stars have an upper limit temperature at any moment. We still may search for the candidates for strange stars in the CFL phase along the limit line.Comment: 9 pages, 3 figures 9 pages, 3 figure

Carbon Nanofiber-Based Materials as Anode Materials for Lithium-Ion Batteries

Considerable efforts have been devoted to the research of high-performance and long-lifespan lithium-ion batteries (LIBs) for their applications in large-scale power units. As one of the most important components in LIBs, anode plays an important role in determining the overall performance of LIBs. Nowadays, graphite has been the most successfully commercialized anode material. However, its limited theoretical capacity (372 mA h g−1) and limited power density seems insufficient for the next-generation LIBs. To overcome these problems, new materials with fundamentally higher capacity and higher power density are urgently needed. Recently, there is an ever-increasing interest in developing novel carbonaceous nanomaterials to replace graphite as the anode materials for LIBs. Such materials have included carbon spheres, carbon nanotubes, carbon nanofibers (CNFs), porous monoliths, and graphene. Among these alternative forms of carbon, CNFs and its morphological-controlled derivatives (such as porous or hollow CNFs) have attracted much attention due to their unique and interesting properties such as one-dimensional (1D) nanostructure, good electronic conductivity, and large surface areas. Moreover, these CNFs can be used to encapsulate various second phases to form some functional composite, meeting further requirements including higher energy density, higher power density or flexible requirements, for the advanced LIB operation

General Influence Coefficient Algorithm in Balancing of Rotating Machinery

The General Influence Coefficient Algorithm (GICA), developed in this article, is a new calculation method for Influence Coefficients (ICs) with a general formula. Compared to the traditional calculation method, GICA can solve the ICs' calculation task when the group of trial weights are installed on the rotor each time, the trial weights are retained on the rotor systems, or there is redundant trial balancing data, when even part of the ICs is known. GICA is also a powerful tool for refining the ICs from redundant balancing data or historical balancing data and serves as a general algorithm. With the general matrix formula, GICA is ready to be applied in a computer-aided balancing system as the key part of calculation software. Examples in industry are also presented to demonstrate the aplication of this new algorithm

Analysis of significant factors on cable failure using the Cox proportional hazard model

This paper proposes the use of the Cox proportional hazard model (Cox PHM), a statistical model, for the analysis of early-failure data associated with power cables. The Cox PHM analyses simultaneously a set of covariates and identifies those which have significant effects on the cable failures. In order to demonstrate the appropriateness of the model, relevant historical failure data related to medium voltage (MV, rated at 10 kV) distribution cables and High Voltage (HV, 110 kV and 220 kV) transmission cables have been collected from a regional electricity company in China. Results prove that the model is more robust than the Weibull distribution, in that failure data does not have to be homogeneous. Results also demonstrate that the method can single out a case of poor manufacturing quality with a particular cable joint provider by using a statistical hypothesis test. The proposed approach can potentially help to resolve any legal dispute that may arise between a manufacturer and a network operator, in addition to providing guidance for improving future practice in cable procurement, design, installations and maintenance