This paper presents a concise summary of recent studies on the long-term variations of haze in NorthChina and on the environmental and dynamic conditions for severe persistent haze events. Resultsindicate that haze da...This paper presents a concise summary of recent studies on the long-term variations of haze in NorthChina and on the environmental and dynamic conditions for severe persistent haze events. Resultsindicate that haze days have an obviously rising trend over the past 50 years in North China. Theoccurrence frequency of persistent haze events has a similar rising trend due to the continuous riseof winter temperatures, decrease of surface wind speeds, and aggravation of atmospheric stability. InNorth China, when severe persistent haze events occur, anomalous southwesterly winds prevail in thelower troposphere, providing sufficient moisture for the formation of haze. Moreover, North China ismainly controlled by a deep downdraft in the mid-lower troposphere, which contributes to reducing thethickness of the planetary boundary layer, obviously reducing the atmospheric capacity for pollutants.This atmospheric circulation and sinking motion provide favorable conditions for the formation andmaintenance of haze in North China.展开更多
A new method is proposed to assess the condition of structures under unknown support excitation by simultaneously detecting local damage and identifying the support excitation from several structural dynamic responses...A new method is proposed to assess the condition of structures under unknown support excitation by simultaneously detecting local damage and identifying the support excitation from several structural dynamic responses. The support excitation acting on a structure is modeled by orthogonal polynomial approximations, and the sensitivities of structural dynamic response with respect to its physical parameters and orthogonal coefficients are derived. The identification equation is based on Taylor＇s first order approximation, and is solved with the damped least-squares method in an iterative procedure. A fifteen-story shear building model and a five-story three-dimensional steel frame structure are studied to validate the proposed method. Numerical simulations with noisy measured accelerations show that the proposed method can accurately detect local damage and identify unknown support excitation from only several responses of the structure. This method provides a new approach for detecting structural damage and updating models with unknown input and incomplete measured output information.展开更多
Through manual pickup of seismic phases,the number of recording stations,the farthest observation distance of station and received energy are determined,then optimal operating condition processing software is develope...Through manual pickup of seismic phases,the number of recording stations,the farthest observation distance of station and received energy are determined,then optimal operating condition processing software is developed to evaluate the excitation effect of operating conditions. The optimal operating conditions in the Mianhuatan Reservoir are determined using this software. They are: optimal water depth 25 m,airgun array sink depth 9m and airgun array size 7m × 7m. At the same time,accumulative stacking results for every 10 times are analyzed for 300 fixed-point excitations. It is concluded that the excitation effect shows a rapidly rising trend at 10 to 90 times stacking,a slowly rising trend at 100 to 150 times stacking,a rapidly rising trend at 160 to 240 times stacking,and a slowly rising trend at 250 to 300 times stacking. As the number of stacking increases,the propagation distance and the number of recording stations also increase gradually.展开更多
This paper studies the parameter identification problem of chaotic systems. Adaptive identification laws are pro- posed to estimate the parameters of uncertain chaotic systems. It proves that the asymptotical identifi...This paper studies the parameter identification problem of chaotic systems. Adaptive identification laws are pro- posed to estimate the parameters of uncertain chaotic systems. It proves that the asymptotical identification is ensured by a persistently exciting condition. Additionally, the method can be applied to identify the uncertain parameters with any number. Numerical simulations are given to validate the theoretical analysis.展开更多
Slope stability prediction plays a significant role in landslide disaster prevention and mitigation.This paper’s reduced error pruning(REP)tree and random tree(RT)models are developed for slope stability evaluation a...Slope stability prediction plays a significant role in landslide disaster prevention and mitigation.This paper’s reduced error pruning(REP)tree and random tree(RT)models are developed for slope stability evaluation and meeting the high precision and rapidity requirements in slope engineering.The data set of this study includes five parameters,namely slope height,slope angle,cohesion,internal friction angle,and peak ground acceleration.The available data is split into two categories:training(75%)and test(25%)sets.The output of the RT and REP tree models is evaluated using performance measures including accuracy(Acc),Matthews correlation coefficient(Mcc),precision(Prec),recall(Rec),and F-score.The applications of the aforementionedmethods for predicting slope stability are compared to one another and recently established soft computing models in the literature.The analysis of the Acc together with Mcc,and F-score for the slope stability in the test set demonstrates that the RT achieved a better prediction performance with(Acc=97.1429%,Mcc=0.935,F-score for stable class=0.979 and for unstable case F-score=0.935)succeeded by the REP tree model with(Acc=95.4286%,Mcc=0.896,F-score stable class=0.967 and for unstable class F-score=0.923)for the slope stability dataset The analysis of performance measures for the slope stability dataset reveals that the RT model attains comparatively better and reliable results and thus should be encouraged in further research.展开更多
文摘This paper presents a concise summary of recent studies on the long-term variations of haze in NorthChina and on the environmental and dynamic conditions for severe persistent haze events. Resultsindicate that haze days have an obviously rising trend over the past 50 years in North China. Theoccurrence frequency of persistent haze events has a similar rising trend due to the continuous riseof winter temperatures, decrease of surface wind speeds, and aggravation of atmospheric stability. InNorth China, when severe persistent haze events occur, anomalous southwesterly winds prevail in thelower troposphere, providing sufficient moisture for the formation of haze. Moreover, North China ismainly controlled by a deep downdraft in the mid-lower troposphere, which contributes to reducing thethickness of the planetary boundary layer, obviously reducing the atmospheric capacity for pollutants.This atmospheric circulation and sinking motion provide favorable conditions for the formation andmaintenance of haze in North China.
基金National Natural Science Foundation of China Under Grant No.50579008Joint Research Fund for Overseas Chinese, Hong Kong and Macao Young Scholars Under Grant No.50429802+1 种基金Program for New Century Excellent Talents in University by State Education Commission Under Grant No.NCET-04-0323a research grant from the Hong Kong Polytechnic University
文摘A new method is proposed to assess the condition of structures under unknown support excitation by simultaneously detecting local damage and identifying the support excitation from several structural dynamic responses. The support excitation acting on a structure is modeled by orthogonal polynomial approximations, and the sensitivities of structural dynamic response with respect to its physical parameters and orthogonal coefficients are derived. The identification equation is based on Taylor＇s first order approximation, and is solved with the damped least-squares method in an iterative procedure. A fifteen-story shear building model and a five-story three-dimensional steel frame structure are studied to validate the proposed method. Numerical simulations with noisy measured accelerations show that the proposed method can accurately detect local damage and identify unknown support excitation from only several responses of the structure. This method provides a new approach for detecting structural damage and updating models with unknown input and incomplete measured output information.
基金sponsored by the National Natural Science Foundation of China(41474071)the Special Fund for Earthquake Scientific Research in the Public Welfare of CEA(2015419015)
文摘Through manual pickup of seismic phases,the number of recording stations,the farthest observation distance of station and received energy are determined,then optimal operating condition processing software is developed to evaluate the excitation effect of operating conditions. The optimal operating conditions in the Mianhuatan Reservoir are determined using this software. They are: optimal water depth 25 m,airgun array sink depth 9m and airgun array size 7m × 7m. At the same time,accumulative stacking results for every 10 times are analyzed for 300 fixed-point excitations. It is concluded that the excitation effect shows a rapidly rising trend at 10 to 90 times stacking,a slowly rising trend at 100 to 150 times stacking,a rapidly rising trend at 160 to 240 times stacking,and a slowly rising trend at 250 to 300 times stacking. As the number of stacking increases,the propagation distance and the number of recording stations also increase gradually.
基金Project supported in part by National Natural Science Foundation of China (Grant Nos. 11047114 and 60974081)in part by the Key Project of Chinese Ministry of Education (Grant No. 210141)
文摘This paper studies the parameter identification problem of chaotic systems. Adaptive identification laws are pro- posed to estimate the parameters of uncertain chaotic systems. It proves that the asymptotical identification is ensured by a persistently exciting condition. Additionally, the method can be applied to identify the uncertain parameters with any number. Numerical simulations are given to validate the theoretical analysis.
基金supported by the National Key Research and Development Plan of China under Grant No.2021YFB2600703.
文摘Slope stability prediction plays a significant role in landslide disaster prevention and mitigation.This paper’s reduced error pruning(REP)tree and random tree(RT)models are developed for slope stability evaluation and meeting the high precision and rapidity requirements in slope engineering.The data set of this study includes five parameters,namely slope height,slope angle,cohesion,internal friction angle,and peak ground acceleration.The available data is split into two categories:training(75%)and test(25%)sets.The output of the RT and REP tree models is evaluated using performance measures including accuracy(Acc),Matthews correlation coefficient(Mcc),precision(Prec),recall(Rec),and F-score.The applications of the aforementionedmethods for predicting slope stability are compared to one another and recently established soft computing models in the literature.The analysis of the Acc together with Mcc,and F-score for the slope stability in the test set demonstrates that the RT achieved a better prediction performance with(Acc=97.1429%,Mcc=0.935,F-score for stable class=0.979 and for unstable case F-score=0.935)succeeded by the REP tree model with(Acc=95.4286%,Mcc=0.896,F-score stable class=0.967 and for unstable class F-score=0.923)for the slope stability dataset The analysis of performance measures for the slope stability dataset reveals that the RT model attains comparatively better and reliable results and thus should be encouraged in further research.
