In the extra-thick coal seams and multi-layered hard roofs, the longwall hydraulic support yielding, coal face spalling, strong deformations of goaf-side entry, and severe ground pressure dynamic events typically occur at the longwall top coal caving longwall faces. Based on the Key strata theory an overburden caving model is proposed here to predict the multilayered hard strata behaviour. The proposed model together with the measured stress changes in coal seam and underground observations in Tongxin coal mine provides a new idea to analyse stress changes in coal and help to minimise rock bursts in the multi-layered hard rock ground. Using the proposed primary Key and the sub-Key strata units the model predicts the formation and instability of the overlying strata that leads to abrupt dynamic changes to the surrounding rock stress. The data obtained from the vertical stress monitoring in the 38 m wide coal pillar located adjacent to the longwall face indicates that the Key strata layers have a significant influence on ground behaviour. Sudden dynamically driven unloading of strata was caused by the first caving of the sub-Key strata while reloading of the vertical stress occurred when the goaf overhang of the sub-Key strata failed. Based on this findings several measures were recommended to minimise the undesirable dynamic occurrences including pre-split of the hard Key strata by blasting and using the energy consumption yielding reinforcement to support the damage prone gate road areas. Use of the numerical modelling simulations was suggested to improve the key theory accuracy.
Forecasting yield curves with regime switches is important in academia and financial industry. As the number of interest rate maturities increases, it poses difficulties in estimating parameters due to the curse of dimensionality. To deal with such a feature, factor models have been developed. However, the existing approaches are restrictive and largely based on the stationarity assumption of the factors. This inaccuracy creates non-ignorable financial risks, especially when the market is volatile. In this paper, a new methodology is proposed to adaptively forecast yield curves. Specifically, functional principal component analysis (FPCA) is used to extract factors capable of representing the features of yield curves. The local AR(1) model with time-dependent parameters is used to forecast each factor. Simulation and empirical studies reveal the superiority of this method over its natural competitor, the dynamic Nelson-Siegel (DNS) model. For the yield curves of the U.S. and China, the adaptive method provides more accurate 6- and 12-month ahead forecasts.
This paper proposes a new dc-side active filter for wind generators that combines 12-pulse polygon auto-transformer rectifier with dc-side current injection method and dual-buck full-bridge inverter having not the “shoot-through” problem in conventional bridge-type inverters, and therefore this system with the character low harmonic distortion and high reliability. The proposed dc-side active filter is realized by using dual-buck full bridge converter, which directly injects compensation current at dc-side of two six-pulse diode bridges rectifiers. Compared with the conventional three-phase active power filter at ac-side, the system with the dc-side active filter draws nearly sinusoidal current by shaping the diode bridges output current to be triangular without using the instantaneous reactive power compensation technology, only using simple hysteretic current control, even though under load variation and unbalanced voltage disturbances, and while an acceptable linear approximation to the accurate waveform of injection current is recommended. The perfor- mance of the system was simulated using MATLAB/Simulink, and the possibility of the dc-side active filter eliminating current harmonics was confirmed in steady and transient states. The simulation results indicate, the system has a total harmonic distortion of current reduced closely to 1%, and a high power factor on the wind generator side.