Improvement of the prediction accuracy of polar motion using empirical mode decomposition

Previous studies revealed that the error of pole coordinate prediction will significantly increase for a prediction period longer than 100 days, and this is mainly caused by short period oscillations. Empirical mode decomposition （EMD）, which is increasingly popular and has advantages over classical wavelet decomposition, can be used to remove short period variations from observed time series of pole co- ordinates. A hybrid model combing EMD and extreme learning machine （ELM）, where high frequency signals are removed and processed time series is then modeled and predicted, is summarized in this paper. The prediction performance of the hybrid model is compared with that of the ELM-only method created from original time series. The results show that the proposed hybrid model outperforms the pure ELM method for both short-term and long-term prediction of pole coordinates. The improvement of prediction accuracy up to 360 days in the future is found to be 24.91% and 26.79% on average in terms of mean absolute error （MAE） for the xp and yp components of pole coordinates, respectively.

A Potential High-Score Scheme for the Prediction of Atlantic Storm Activity

A new empirical approach for the seasonal prediction of annual Atlantic tropical storm number (ATSN) was developed using precipitation and 500 hPa geopotential height data from the preceding January February and April May.The 2.5°×2.5° resolution reanalysis data from both the US National Center for Environmental Prediction/the National Center for Atmospheric Research (NCEP/NCAR) and the European Center for Medium-Range Weather Forecasting (ECMWF) were applied.The model was cross-validated using data from 1979 2002.The ATSN predictions from the two reanalysis models were correlated with the observations with the anomaly correlation coefficients (ACC) of 0.79 (NCEP/NCAR) and 0.78 (ECMWF) and the multi-year mean absolute prediction errors (MAE) of 1.85 and 1.76,respectively.When the predictions of the two models were averaged,the ACC increased to 0.90 and the MAE decreased to 1.18,an exceptionally high score.Therefore,this new empirical approach has the potential to improve the operational prediction of the annual tropical Atlantic storm frequency.

The dynamic response and damage models of rebar reinforced polymer slabs subjected to contact and near-field explosions

Non aqueous reactive polymer materials produced by the reaction of isocyanate and polyol have been widely used in infrastructure construction,which may be subjected to explosion loads during complex service conditions.The blast response of composite materials is a crucial aspect for applications in engineering structures potentially subjected to extreme loadings.In this work,damage caused to rebar reinforced polymer slabs by surface explosive charges was studied experimentally and numerically.A total of 6 field tests were carried out to investigate the performances of the failure modes of rebar reinforced polymer slabs under contact and near-field explosions.The influence of explosive quantity(10-40 g)and stand-off distances(0-20 cm)at the damage modes were studied.The results show that the failure modes of rebar reinforced polymer slabs under near-field explosion mainly were bending and surface spalling,while under the impact of contact explosion,the failure modes were craters of the top surface,spalling of the bottom surface,and middle perforation.Furthermore,a detailed fully coupled model was developed and validated with the test data.The influences of explosive quantity and slab thickness on rebar reinforced polymer slabs under contact explosion were studied.Based on this,the calculation formula between breach diameter,explosive quantity,and slab thickness is fitted.

Predicting excavation damage zone depths in brittle rocks

During the construction of an underground excavation, damage occurs in the surrounding rock mass due in large part to stress changes. While the predicted damage extent impacts profile selection and support design, the depth of damage is a critical aspect for the design of permeability sensitive excavations, such as a deep geological repository(DGR) for nuclear waste. Review of literature regarding the depth of excavation damage zones(EDZs) indicates three zones are common and typically related to stress induced damage. Based on past developments related to brittle damage prediction using continuum modelling, the depth of the EDZs has been examined numerically. One method to capture stress induced damage in conventional engineering software is the damage initiation and spalling limit(DISL) approach. The variability of depths predicted using the DISL approach has been evaluated and guidelines are suggested for determining the depth of the EDZs around circular excavations in brittle rock masses. Of the inputs evaluated, it was found that the tensile strength produces the greatest variation in the depth of the EDZs. The results were evaluated statistically to determine the best fit relation between the model inputs and the depth of the EDZs. The best correlation and least variation were found for the outer EDZ and the highly damaged zone(HDZ) showed the greatest variation. Predictive equations for different EDZs have been suggested and the maximum numerical EDZ depths, represented by the 68% prediction interval, agreed well with the empirical evidence. This suggests that the numerical limits can be used for preliminary depth prediction of the EDZs in brittle rock for circular excavations.

Efficiency of scalar and vector intensity measures for seismic slope displacements

Ground motion intensity measures are usually used to predict the earthquake-induced displacements in earth dams,soil slopes and soil structures.In this study,the efficiency of various single ground motion intensity measures(scalar IMs)or a combination of them(vector IMs)are investigated using the PEER-NGA strong motion database and an equivalent-linear sliding-mass model.Although no single intensity measure is efficient enough for all slope conditions,the spectral acceleration at 1.5 times of the initial slope period and Arias intensity of the input motion are found to be the most efficient scalar IMs for flexible slopes and stiff slopes respectively.Vector IMs can incorporate different characteristics of the ground motion and thus significantly improve the efficiency over a wide range of slope conditions.Among various vector IMs considered,the spectral accelerations at multiple spectral periods achieve high efficiency for a wide range of slope conditions.This study provides usefiul guidance to the development of more efficient empirical prediction models as well as the ground motion selection criteria for time domain analysis of seismic slope displacements.

A METHOD FOR PREDICTING SEASONAL PRECIPITATION ANOMALY DISTRIBUTION IN SUMMER OVER CHINA

Some main features of spatial-temporal variation of precipitation field in summer over China have been analysed and a skillfull method with physical and statistical consideration for predicting precipitation anomaly distribution in summer over China is suggested.The predictive skill for independent sample of 1994-1998 with the method is assessed,i.e.the averaged anomaly correlation coefficient between the observed and predicted precipitation filed over China is 0.26.