Accidents involving natural gas leakage and dispersion pose a significant threat to human life and property.This threat is especially relevant at the street intersection at which dense buildings,heavy traffic flow,and...Accidents involving natural gas leakage and dispersion pose a significant threat to human life and property.This threat is especially relevant at the street intersection at which dense buildings,heavy traffic flow,and complex underground pipe networks meet.Scholars have conducted numerous studies on gas leakage and dispersion,but investigations of natural gas leakage and dispersion at the street intersection of a building group are not in-depth.In this paper,we presented a three-dimensional(3D)physical model based on the Computational Fluid Dynamic(CFD)methodology to study the natural gas leakage and dispersion at the street intersection of a building group.We validated the CFD methodology applied in the research based on the data from the field tests and wind tunnel experiments.Then,we simulated and analyzed the pressure,wind,and concentration of natural gas dispersion at the street intersection.The simulation results showed that vortex regions,low-pressure zones,and a building group effect could cause a build-up of natural gas concentration under perpendicular wind direction conditions.In addition,the area of hazardous region tended to increase first and then drop with the dispersion height.In the case of this study,the maximum area of hazardous region is 200 m2 located in the height of 55 m,which is the middle plane in the computational domain.The results in the paper can provide scientific references for the safe operation and emergency-management decisions of municipal gas.展开更多
Privacy preservation is a crucial issue for smart buildings where all kinds of messages, e.g., power usage data, control commands, events, alarms, etc. are transmitted to accomplish the management of power. Without ap...Privacy preservation is a crucial issue for smart buildings where all kinds of messages, e.g., power usage data, control commands, events, alarms, etc. are transmitted to accomplish the management of power. Without appropriate privacy protection schemes, electricity customers are faced with various privacy risks. Meanwhile, the natures of smart grids and smart buildings—such as having limited computation power of smart devices and constraints in communication network capabilities, while requiring being highly reliable—make privacy preservation a challenging task. In this paper, we propose a group key scheme to safeguard multicast privacy with the provisions of availability, fault-tolerance, and efficiency in the context of smart buildings as a part the smart grid. In particular, hybrid architecture accommodating both centralized and contributory modes is constructed in order to achieve both fault-tolerance and efficiency with only one set of group key installed. Key trees are sophisticatedly managed to reduce the number of exponentiation operations. In addition, an individual rekeying scheme is introduced for occasional joining and leaving of member smart meters. Experimental results, on a simulation platform, show that our scheme is able to provide significant performance gains over state-of-the-art methods while effectively preserving the participants’ privacy.展开更多
In order to simplify the three-dimensional building group model, this paper proposes a clustering generalization method based on visual cognitive theory. The method uses road elements to roughly divide scenes, and the...In order to simplify the three-dimensional building group model, this paper proposes a clustering generalization method based on visual cognitive theory. The method uses road elements to roughly divide scenes, and then uses spatial cognitive elements such as direction, area, height and their topological constraints to classify them precisely, so as to make them conform to the urban morphological characteristics. Delaunay triangulation network and boundary tracking synthesis algorithm are used to merge and summarize the models, and the models are stored hierarchically. The proposed algorithm should be verified experimentally with a typical urban complex model. The experimental results show that the efficiency of the method used in this paper is at least 20% higher than that of previous one, and with the growth of test data, the higher efficiency is improved. The classification results conform to human cognitive habits, and the generalization levels of different models can be relatively unified by adaptive control of each threshold in the clustering generalization process.展开更多
基金supported by the Joint Project of Beijing Municipal Education Commission(No.ZX20140289).
文摘Accidents involving natural gas leakage and dispersion pose a significant threat to human life and property.This threat is especially relevant at the street intersection at which dense buildings,heavy traffic flow,and complex underground pipe networks meet.Scholars have conducted numerous studies on gas leakage and dispersion,but investigations of natural gas leakage and dispersion at the street intersection of a building group are not in-depth.In this paper,we presented a three-dimensional(3D)physical model based on the Computational Fluid Dynamic(CFD)methodology to study the natural gas leakage and dispersion at the street intersection of a building group.We validated the CFD methodology applied in the research based on the data from the field tests and wind tunnel experiments.Then,we simulated and analyzed the pressure,wind,and concentration of natural gas dispersion at the street intersection.The simulation results showed that vortex regions,low-pressure zones,and a building group effect could cause a build-up of natural gas concentration under perpendicular wind direction conditions.In addition,the area of hazardous region tended to increase first and then drop with the dispersion height.In the case of this study,the maximum area of hazardous region is 200 m2 located in the height of 55 m,which is the middle plane in the computational domain.The results in the paper can provide scientific references for the safe operation and emergency-management decisions of municipal gas.
文摘Privacy preservation is a crucial issue for smart buildings where all kinds of messages, e.g., power usage data, control commands, events, alarms, etc. are transmitted to accomplish the management of power. Without appropriate privacy protection schemes, electricity customers are faced with various privacy risks. Meanwhile, the natures of smart grids and smart buildings—such as having limited computation power of smart devices and constraints in communication network capabilities, while requiring being highly reliable—make privacy preservation a challenging task. In this paper, we propose a group key scheme to safeguard multicast privacy with the provisions of availability, fault-tolerance, and efficiency in the context of smart buildings as a part the smart grid. In particular, hybrid architecture accommodating both centralized and contributory modes is constructed in order to achieve both fault-tolerance and efficiency with only one set of group key installed. Key trees are sophisticatedly managed to reduce the number of exponentiation operations. In addition, an individual rekeying scheme is introduced for occasional joining and leaving of member smart meters. Experimental results, on a simulation platform, show that our scheme is able to provide significant performance gains over state-of-the-art methods while effectively preserving the participants’ privacy.
文摘In order to simplify the three-dimensional building group model, this paper proposes a clustering generalization method based on visual cognitive theory. The method uses road elements to roughly divide scenes, and then uses spatial cognitive elements such as direction, area, height and their topological constraints to classify them precisely, so as to make them conform to the urban morphological characteristics. Delaunay triangulation network and boundary tracking synthesis algorithm are used to merge and summarize the models, and the models are stored hierarchically. The proposed algorithm should be verified experimentally with a typical urban complex model. The experimental results show that the efficiency of the method used in this paper is at least 20% higher than that of previous one, and with the growth of test data, the higher efficiency is improved. The classification results conform to human cognitive habits, and the generalization levels of different models can be relatively unified by adaptive control of each threshold in the clustering generalization process.
