Abstract

This article reports on a project that is the first step the LIGO Scientific Collaboration and the Virgo Collaboration have taken to prepare for the mutual search for inspiral signals. The project involved comparing the analysis pipelines of the two collaborations on data sets prepared by both sides, containing simulated noise and injected events. The ability of the pipelines to detect the injected events was checked, and a first comparison of how the parameters of the events were recovered has been completed. Comment: GWDAW-9 proceeding

Abstract

We report on an investigation of Virgo Commissioning run 4 data, dedicated to searching signals of the kind supposed to be emitted by inspiral neutron star binary systems. Given the still relatively limited sensitivity, the goal was to test some of the elements of the analysis chain, using simulated events, hardware and software injected in the data; the test allowed us to also characterize the detector stability during the run, for the purposes of the inspiral event search.

Abstract

Aiming to successfully meet the requirements of a large output torque and a wide range of flux weakening speed expansion in permanent magnet synchronous motors (PMSM) for electric vehicles, a novel surface insert permanent magnet synchronous motor (SIPMSM) is developed. The method of notching auxiliary slots between the magnetic poles in the rotor and unequal thickness magnetic poles is proposed to improve the performance of the motor. By analyzing the magnetic circuit characteristics of the novel SIPMSM, the notching auxiliary slots between the adjacent magnetic poles can affect the q-axis inductance, and the shape of magnetic pole effects the d-axis inductance of the motor. The combined action of the two factors not only weakens the cogging torque, but also improves the flux weakening capability of the motor. In this paper, the response surface methodology (RSM) is used to establish a mathematical model of the relationship between the structural parameters of the motor and the optimization objectives, and the optimal design of the motor is completed by solving the mathematical model. Experimental validation has been conducted to show the correctness and effectiveness of the proposed SIPMSM. Document type: Article

Abstract

New urbanization (NU) and sustainable transportation (ST) are two important issues in urbanization, and their symmetrical coupling is an important factor for measuring the development of the urbanization process. To comprehensively explore the symmetrical coupling level of NU and ST in the urbanization process, this study proposed a coupling coordination degree (CCD) model and calculated the CCD values of China&rsquo s nine metropolises using panel data from 2007 to 2016. The results showed that: (1) From the perspective of each city&rsquo s development, the CCD values for Beijing, Tianjin and Chongqing showed a downward trend, and those for Shanghai, Guangzhou, Chengdu and Wuhan exhibited a rising trend, while the CCD values for Zhengzhou and Xi&rsquo an fell initially and then rose gradually (2) Based on the regions of the nine cities, the CCD values of the eastern cities and the central cities all demonstrated a growth trend, while those of the western cities were consistently lower than the central and eastern cities however, the western cities experienced the highest growth rate. (3) Predictive results showed that the CCD levels of new urbanization and sustainable transportation in the eastern, central and western cities are projected to remain unchanged. Finally, it is expected that regionally balanced development will be realized in 2025. From the symmetrical coupling perspective, this study measured and predicted the coupling coordination level of NU and ST of nine metropolises undergoing the urbanization process, which provides a theoretical basis for effective decision-making for comprehensive and sustainable development of China&rsquo s urbanization. Document type: Article

Abstract

Timely predicting and controlling the traffic congestion in a station caused by an emergency is an important task in railway emergency management. However, traffic forecasting in an emergency is subject to a dynamic service network, with uncertainty surrounding elements such as the capacity of the transport network, schedules, and plans. Accurate traffic forecasting is difficult. This paper proposes a practical time&ndash space network model based on a train diagram for predicting and controlling the traffic congestion in a station caused by an emergency. Based on the train diagram, we constructed a symmetric time&ndash space network for the first time by considering the transition of the railcar state. On this basis, an improved A* algorithm based on the railcar flow route was proposed to generate feasible path sets and a dynamic railcar flow distribution model was built to simulate the railcar flow distribution process in an emergency. In our numerical studies, these output results of our proposed model can be used to control traffic congestion. Document type: Article