Search

A facile and economical approach was developed for the large-scale production of powdered core-shell structured PTFE/Al (CS-PA) energetic materials through ultrasonic-assisted mixing. The low-cost micrometer-sized PTFE and Al particles were used as starting materials. Under high-power ultrasonic waves, the PTFE powder was dispersed into nano-to sub-micrometer-sized particles and then encapsulated the Al microparticles to form the core-shell structure. The heat of combustion, burning rate, and pressurization rate of the powdered CS-PA were measured. The thermal-initiated reaction behavior was further evaluated using thermogravimetry-differential scanning calorimetry. Subsequently, the bulk CS-PA with a uniform microstructure was obtained via cold isostatic pressing of the powdered CS-PA followed by vacuum sintering. For the bulk CS-PA, the quasi-static compression behavior was characterized, and the impact-initiated reaction processes were conducted using the Split Hopkinson Pressure Bar (SHPB) and evaluated by a high-speed camera. Compared to physically mixed PTFE/Al materials, the powdered and bulk CS-PA demonstrated enhanced thermal- and impact-initiated reaction characteristics respectively, proving the effectiveness of our approach for constructing core-shell structures.

We study the overload control problem of application server in the next generation electric communication network in this paper. We introduce an energy efficiency overload control algorithm based on simulated annealing. Firstly, by considering the overload control and energy efficiency, we construct the relations function between the input rate control and energy efficiency using rate allocation. Then, we construct the optimal overload control model of energy efficiency by regarding this relation function as objective function and overload control as constraint conditions. Thirdly, we use simulated annealing algorithm to solve this model, and then obtain the optimal solution during the iterative process. The simulation results show that our algorithm is feasible and effective.

In this literature, we explore the solution of network traffic recovery in smart grid. Taking account of dimensionality of network traffic in smart grid, we propose a novel reconstruction model via network tomography. In our algorithm, we use the low-dimension nature of traffic matrix and the greedy adaptive dictionary algorithm to convert the network tomography into the problem of sparse reconstruction at first. Then we solve network traffic by an iterative greedy algorithm. Simulation results indicate that proposed algorithm exhibits noticeably improvement in estimation error comparing with previous work.

In this paper, we address the problem of real-time network traffic monitoring in the communication network of smart grid. And we propose an effective distributed network traffic monitoring approach. In our algorithm, instead of measuring all the origin-destination pairs, we just need to measure partial origin-destination pairs that flows our communication network. From the measured origin-destination pairs, we can obtain all the origin-destination pairs via our recovery algorithm. Finally, we validate the properties of our method by real network data.

This paper studies the overload control problem of the Parlay gateway in next-generation electric power communication network. First, this paper analyses the effectiveness and fairness of the overload control of the Parlay gateway. And then taking the energy efficiency of the electric power communication network as target, we establish the optimization model of energy efficiency overload control. Thirdly, we put forward an energy efficiency overload control algorithm based on the ant colony algorithm. Simulation results show that our algorithm is feasible and effective.

This paper studies the problem of QoS graded optimization in the next generation electric power communication network and proposes an energy-efficient QoS graded optimization method based on artificial fish swarm algorithm. Firstly, this paper discusses the networks model of the QoS graded optimization and describes the networks model using delay and packet loss ratio in time-variant network. Secondly, we set up the model of networks throughput and energy consumption using the characteristics of delay and packet loss ratio in time-variant network. Finally, simulation results show that our approach is effective.

With the rapid development of the information and communication technology (ICT) and the considerable increasing of the network business, the energy consumption of the network equipments improves continually. Thus building the technology of the next generation electric power communication network based on energy efficiency has become the research focus of the current electric power communication field. This paper researches the problem of the QoS graded optimization in the next generation electric power communication network. First of all, we discuss the network model of the networks QoS graded optimization, and analyze the delay and the packet loss ratio in time-variant networks. Secondly, we introduce the mathematical description of the throughput capacity and the energy consumption in time-variant networks and build the optimizing model of the energy efficiency which describes the networks QoS classification through considering the QoS constraints such as the networks delay and packet loss ratio etc. Thirdly, we propose using Genetic Algorithm to solve the model and find the QoS classes which make the networks reach the maximum energy efficiency through iterative optimization. Finally, the simulation results indicate the method proposed in this paper is available.

This paper theoretically analyzes the atmospheric influences on Ultraviolet (UV) communication, in which the main considerations include atmospheric absorption and atmospheric scattering. Through the establishment of mathematical model, this paper describes the atmospheric transmittance with different wavelengths. Finally, the atmospheric transmittance is simulated under different visibilities, rainfall and paths. The results show that the atmospheric transmittance will be different with different wavelengths, visibilities and rainfall. The atmospheric transmittance in horizontal path is larger than that in the vertical path. This research provides a theoretical guidance on the using of UV communication for the information transmission in power grid.

Mobile Ad hoc Network (MANET) is an effective method to solve the bottleneck of information collection and wireless transmission in Smart Grid. The particularity of MANET determines the importance of routing protocols. In order to improve the performance of MANET routing protocol, in this paper we evaluate the routing protocol, i.e., Ad hoc On demand Distance Vector (AODV), from several perspectives that did not draw attention in previous works. Furthermore, we also compare AODV with the routing protocol Dynamic source Routing (DSR). The simulation shows that AODV outperforms DSR in generally, and the former is suitable for larger MANET network. The simulation results in this paper not only provide effective evidence for further optimized routing protocols and the current protocols, but also provide feasible solution for Smart Grid to collect and transmission data by using MANET technology.

The rapid growth of data service promotes the construction of the electric power telecommunication in smart grids. With the objective of energy savings, we determine the optimal location of the data center with the minimal energy cost within all possible positions. An Integer Linear Program (ILP) is formulated and we also propose the corresponding algorithms, mainly including Green Optical Bypass Energy Saving Grooming Algorithm (GOBEGA) and Green Non-Bypass Energy Saving Grooming Algorithm (GNBEGA). Simulation results demonstrate that the proposed algorithms have the good performance of energy savings, and GOBEGA has the lower energy cost compared with GNBEGA.

Due to the heterogeneity and the nature of distributed control, the existing electric power data communication network based on Synchronous Digital Hierarchy (SDH) has been unable to meet the requirements of dynamic resource allocation and fine-grained traffic monitoring. The OpenFlow-based Software Defined Network (SDN) allows operators dynamically control and monitor the whole network using the software running on the operating system of the centralized controller (e.g., NOX controller). Thus, in this paper, we propose the SDN-based fault-tolerant solution for the electric power data communication network. The feasibility and efficiency of the proposed solution are verified, and the performances of the dynamic end-to-end path restoration, such as the CPU utilization of NOX and end-to-end delay, are quantitatively evaluated in our experimental platform. The experimental results indicate that the dynamic end-to-end path restoration can be achieved within tens of milliseconds by using our SDN-based solution.

This paper analysis overload control characteristics of the application server in the next generation electric communication network, as well as the application server overload detection requirements, propose an energy efficiency overload control algorithm based on particle swarm. First of all, we consider the problem of overload control and network efficiency at the same time, based on rate allocation algorithm, construct the control input rate and energy efficiency model, on which the energy efficiency optimization overload control model is built. After that, the particle swarm optimization is used to solve the model, where the optimal solution is obtained by the iterative process. Finally, the simulation results show that the proposed algorithm is feasible and effective. Index Terms - NGN, electric communication, application server, energy efficiency, overload control.