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The purpose of this paper is to understand the natural wind field characteristics of the tunnel entrance section and analyzing the aerodynamic performance of high-speed railway trains (HSRTs) under natural winds.

Three typical tunnel entrance section sites, namely, tunnel–bridge in a dry canyon (TBDC), tunnel–bridge in a river canyon (TBRC) and tunnel–flat ground (TF), are selected to conduct a continuous wind field measurement. Based on the measured wind characteristics, the natural winds of the TBDC and TF sites are reconstituted and imported into the two corresponding full-scale computational fluid dynamics models. The aerodynamic loads of the HSRT running on TBDC and TF with reconstituted winds are simply analyzed.

The von Kármán spectrum can be used to describe the wind field at the tunnel entrance section. In the reconstituted natural wind condition, a time-varying feature of wind speed distribution and leeward side vortex around the HSRT caused by the wind speed fluctuation is found. The fluctuating amplitude of aerodynamic loads at the TBDC infrastructure is up to 97.9% larger than that at the TF infrastructure.

The natural wind characteristics at tunnel entrance sections on the high-speed railway are first measured and analyzed. A numerical reconstitution scheme considering the temporal and spatial variation of natural wind speed is proposed and verified based on field measurement results. The aerodynamic performance of an HSRT under reconstituted natural winds is first investigated.

This paper aims to present a simplified method to predict the pressure of the recess, no matter whether the tilt center coincides with the geometric center of the hydrostatic journal bearings.

To validate the effectiveness of the presented model, computational fluid dynamics (CFD) method and experimental method are performed in this study.

By comparing the CFD results and the experimental results, the pressure of the recess is related to the tilt direction, the tilt center, the width of the land and the circumferential angle of the land.

The mathematic model requires equivalent resistance of land edge – tilt position, tilt direction, tilt angle and the thickness of oil film instead of any digital iteration. Furthermore, a novel experimental apparatus including a circular hydrostatic bearing called ball bearing is designed to study the tilt effect produced by manufacturing error and offset load force on the pressure of the recess.

How can governments and survivors prepare for and manage natural disasters? Post-disaster reconstruction researchers advocate that community involvement is needed to help survivors recover effectively. This study aims to propose that cooperative goals between government officials and survivors develop guanxi relationships and constructive controversy wherein survivors voice their opinions to aid disaster recovery.

The authors adopted the critical incident technique (CIT), which has proved especially useful for studying complex issues, as well as site-intensive research for interviews and participant observation. After developing a local reputation and rapport by working in a residential resettlement area for two months, an author used the CIT to ask 118 survivors of the 2008 Sichuan earthquake to describe specific incidents when they interacted with government officials about recovery issues and then to rate survey items that measure independent and dependent variables.

Results, including structural equation analyses, support the reasoning that cooperative goals between government and survivors facilitate guanxi and constructive controversy, which in turn produced effective disaster recovery, as indicated by survivors’ social support, satisfaction, reduced stress and beliefs that government officials led effectively.

The data are self-reported and subject to biases and may not be accurate.

In addition to developing theoretical understanding, the results can have important practical implications for strengthening relationships and constructive controversy between government and survivors.

Results suggest that communities have practical ways to prepare for disasters. Structuring cooperative goals among survivors, encouraging guanxi relationships, and training in constructive controversy should promote effective recovery from natural disasters.

The paper develops theory and research on how leaders can promote community involvement for effective disaster management. The paper proposes that high-quality interpersonal relationships, also referred to guanxi, and the open-minded discussion of opposing ideas, labeled constructive controversy, are major components of effective community involvement. The paper adds to the literature by empirically documenting the utility of the Western-developed theory of cooperation and competition and the concept of constructive controversy for understanding the effectiveness of government leadership for disaster recovery in China.

The paper aims to provide an adaptive neural network controller for permanent magnet synchronous motor (PMSM) under direct torque control (DTC) algorithm to minimize the torque ripple and EMI noise.

The design methodology is based on vector control used for electrical machines. MATLAB simulations supported with experimental study under C++ are used.

The simulated and experimental results show that considerable torque ripple as well as current ripple and EMI noise reduction can be achieved by utilizing adaptive neural switching algorithm to fire the inverter supplying the PMSM.

This research is limited to PMSM, however the research can be extended to include other AC motors as well. In addition, the following points can be studied: the effects of harmonics in control signals on the torque ripple can be analyzed; the actual mathematical relation between the torque and flux ripple can be studied to set the flux and torque bands width in reasonable value; different neural network algorithms can be applied to the system to solve the similar problems.

Based on existing DTC control system, it is only required to change the software switching algorithm, to provide smooth torque, given that the switching frequency of the inverter module is more than or equal to 15 MHz and the system is supplied with timers. In addition a relatively higher DC voltage may be required to achieve higher speed compared with the traditional DTC.

In this paper, the stator flux position, and errors due to deviations from reference values of the torque and stator flux are used to select two active vectors while at the same time the absolute value of the torque error and the stator flux position are used neural network structure to adapt the switching of the inverter in order to control the applied average voltage level in such a way as to minimize the torque ripple, so instead of fixed time table structure, a neural network controller is used to calculate the switching time for the selected vectors and no PI controller is used as the case in the traditional space vector modulation. This work is directed to motor drive system designers who seek highly smooth torque performance with EMI noise reduction.