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Research on the influence of performance parameters on the super high speed permanent magnet synchronous generator external characteristic

Qiu H., Tang B., Yang C., Cui G.

Archives of Electrical Engineering

2018

Vol. 67, nr 1

179--192

Super high speed permanent magnet generators (SHSPMG) usually operate at high frequency. The external characteristic of the SHSPMG under condition of high frequency operation is quite different from that of conventional generators. Therefore, it is necessary to study the external characteristic of the SHSPMG. Based on the finite element method, this paper studied the factors that affect the external characteristic of the SHSPMG. Combining the vector method and the finite element method, the external characteristic of the SHSPMG with the inductive load and the resistance load was studied. The variation law of the generator terminal voltage with the change of the load and current was obtained, and the key factors affecting the external characteristic of the SHSPMG were determined. The influences of the armature resistance, power factor, frequency and permanent magnet performance on the external characteristic of the SHSPMG were studied. The influence mechanism of different parameters on the generator external characteristic was revealed. The influence degree of each factor on the voltage regulation was determined. The conclusions can provide reference for the design and research of the SHSPMG.

Sensitivity analysis study of the source parameter uncertainty factors for predicting near-field strong ground motion

Li Z., Gao M., Jiang H., Chen X., Li T., Zhao X.

Acta Geophysica

2018

Vol. 66, no. 4

523--540

Uncertainty factors have substantial influences on the numerical simulations of earthquakes. However, most simulation methods are deterministic and do not sufficiently consider those uncertainty factors. A good approach for predicting future destructive earthquakes that is also applied to probabilistic hazard analysis is studying those uncertainty factors, which is very significant for improving the reliability and accuracy of ground-motion predictions. In this paper, we investigated several uncertainty factors, namely the initial rupture point, stress drop, and number of sub-faults, all of which display substantial influences on ground-motion predictions, via sensitivity analysis. The associated uncertainties are derived by considering the uncertainties in the parameter values, as those uncertainties are associated with the ground motion itself. A sensitivity analysis confirms which uncertainty factors have large influences on ground motion predictions, based upon which we can allocate appropriate weights to those uncertainty factors during the prediction process. We employ the empirical Green function method as a numerical simulation tool. The effectiveness of this method has been previously validated, especially in areas with sufficient earthquake record data such as Japan, Southwest China, and Taiwan, China. Accordingly, we analyse the sensitivities of the uncertainty factors during a prediction of strong ground motion using the empirical Green function method. We consequently draw the following conclusions. (1) The stress drop has the largest influence on ground-motion predictions. The discrepancy between the maximum and minimum PGA among three different stations is very large. In addition, the PGV and PGD also change drastically. The Arias intensity increases exponentially with an increase in the stress drop ratio of two earthquakes. (2) The number of sub-faults also has a large influence on various ground-motion parameters but a small influence on the Fourier spectrum and response spectrum. (3) The initial rupture point largely influences the PGA and Arias intensity. We will accordingly pay additional attention to these uncertainty factors when we conduct ground-motion predictions in the future.