Identification methods for anomalous stress region in coal roadways based on microseismic information and numerical simulation

It is believed that the microseismicity induced by mining effect and gas gradient disturbance stress is a precursor to the essential characteristics of roadway unstability. In order to effectively identify and evaluate the stability of coal roadways in the process of mine development and extraction, a microseismic monitoring system was deployed for the study of the stress evolution process, damage degree and distribution characteristics in the tailgate and headgate. The mine under study is the 62113 outburst working face of Xin Zhuangzi coalmine in Huainan mining area. The whole process of microfractures initiation,extension, interaction and coalescence mechanisms during the progressive failure processes of the coal rock within the delineated and typical event clusters were investigated by means of a two dimensional realistic failure process analysis code(RFPA2D-Flow). The results show that the microseismic events gradually create different-sized event clusters. The microseismicity of the tailgate is significantly higher than that of the headgate. The study indicates that the greater anomalous stress region matches the area where microfractures continuously develop and finally connect to each other and form a fissure zone.Due to the mine layout and stress concentration, the ruptured area is mainly located on the left shoulder of the tailgate roof. The potential anomalous stress region of the coal roadway obtained by numerical simulation is relatively in good agreement with the trend of spatial macro evolution of coal rock microfractures captured by the microseismic monitoring system. The research results can provide important basis for understanding instability failure mechanism of deep roadway and microseismic activity law in complex geologic conditions, and it ultimately can be used to guide the selection and optimization of reinforcement and protection scheme.

Future changes of cluster high temperature events over China from RegCM4 ensemble under RCP4.5 scenario

Using the daily maximum temperature of the RegCM4 dynamical downscaling from four global climate models under the historical and RCP4.5 simulations,this study firstly identified the cluster high temperature event(CHTE)occurring in China through a simplified objective method,and then projected its change during the 21st century in terms of the CHTE metrics including frequency,duration,extreme intensity,cumulative intensity,maximum influential area,average influential area,and comprehensive intensity.The ensemble projection indicates that all the CHTE metrics tend to increase toward the end of the 21st century on the national scale.Besides,the occurrence of CHTE shows a longer month span during the middle and the end of the 21st century(from April to October)compared to the present(from April to September),accompanied with the peaks of the frequency,duration,and cumulative intensity shifting from the present July ahead to June.Relative to 1986-2005,the projected slight,moderate,and extreme CHTEs increase by 55%,50%,and 50%(58%,43%,and 60%)during 2046-2065(2080-2099),respectively;the projected severe CHTE increases by 11%during 2046-2065 while decreases by 11% during 2080-2099.Spatially,the CHTE frequency,duration,and cumulative intensity are projected to increase in a widespread region.The largest increase appears in southern China for the frequency and in Xinjiang and Southeast China for the duration and cumulative intensity.We further divided China into five sub-regions to examine the regional features of CHTE changes.It is found that in addition to the increase of CHTEs in each single subregion,a pronounced enhancement is also projected for the occurrence of cross-regional CHTEs,particularly for that across more than two subregions.

Distributed Algorithms for Event Reporting in Mobile-Sink WSNs for Internet of Things

Wireless Sensor Networks（WSNs） have many applications, such as climate monitoring systems, fire detection, smart homes, and smart cities. It is expected that WSNs will be integrated into the Internet of Things（IoT）and participate in various tasks. WSNs play an important role monitoring and reporting environment information and collecting surrounding context. In this paper we consider a WSN deployed for an application such as environment monitoring, and a mobile sink which acts as the gateway between the Internet and the WSN. Data gathering is a challenging problem in WSNs and in the IoT because the information has to be available quickly and effectively without delays and redundancies. In this paper we propose several distributed algorithms for composite event detection and reporting to a mobile sink. Once data is collected by the sink, it can be shared using the IoT infrastructure. We analyze the performance of our algorithms using WSNet simulator, which is specially designed for event-based WSNs. We measure various metrics such as average residual energy, percentage of composite events processed successfully at the sink, and the average number of hops to reach the sink.