Applied Mechanics and Materials Vols. 55-57

Abstract: The concept of introducing self-healing capabilities in polymer materials and systems has been based on mimicking biological self-healing materials and systems, for example, materials like proteins have phenomenal capabilities in self-healing damaged biological structures. This work has been extended to investigate self-healing capabilities of fibre reinforced epoxy composites. Microencapsulated epoxy and mercaptan healing agents were incorporated into a glass fibre reinforced epoxy matrix to produce a polymer composite capable of self-healing. The specimens containing the microencapsulated epoxy and mercaptan healing agents did gain excellent strength and achieved a healing efficiency up to 140%.

Abstract: So far the research of product intelligent design model focused on product function. Referring to the three principles, generality, practicability and reusability we stress that modeling for behavior meets more requirement of intelligent design model. Corresponding to product behavior we suggest the concept of behavior flow. Based on the concept we suggest the framework of product intelligent design model and adopt hybrid Petri net to describe and formulize the model of behavior flow. At last according to such theory we build a model for engine behavior to demonstrate the suggestions and methods.

Abstract: This paper involves a study of a real-time system for monitoring the security of commercial vehicles in road networks. Embedded in the security monitoring system is a commercial vehicle tracking and incident detection algorithm which relies on a combination of vehicle telemetry data obtained from Global Positioning Systems and on-board sensors to continuously monitor the route choice and car-following behavior of the driver. The performance of this algorithm has been tested in a microscopic simulation model, on a set of hypothetical scenarios, which included deviations from the approved routes, forced to travel at unreasonably low speeds, or even stopped at unexpected places in the network. The initial results indicate that the proposed system has good potential in detecting abnormal driving behaviors, with 100% detection rate, 6.0 seconds of mean detection time, and less than 1% false alarm rate.

Abstract: The cushioning characteristics of honeycomb paperboards with rhombic core were investigated and compared with the conventional hexagonal honeycomb paperboards. The compressing tests under low-velocity impact loads were performed to analyze stresses and deformation behaviors of specimens based on stress-strain curves and cushioning coefficient-strain curves. The results show that, compared of the hexagonal core, the rhombic core structure is able to decrease the rigidity and improve the initial cushioning properties of honeycomb paperboard. It is more benefit for packaging fragile items.

Abstract: Energy consumption is a critical problem in operation of wireless sensor networks. For the sake of avoiding the data abundance and balancing the energy consumption in wireless sensor networks, this paper makes a research on network nodes Optimization in wireless sensor network based on ant colony algorithm and WIA-PA protocol stack. The novel design improved on hardware and software to control consumption of the energy and used transition probability of ant colony algorithm from one node to the other to calculate and determine the optimal path of network node in traversal of these locations. The results of the examples show that this method has lower energy consumption, computational briefness and higher positioning accuracy; it can not easily run into the local optimum, and also be applied to other tracking of complex network systems.

Abstract: Fault diagnosis has been the research hotspot in the industry fields, but, with the gradual complication in modern industry equipments and systems, it is more hard to quickly diagnose complicated or exceptional faults. For overcoming the diagnosis weakness of traditional fault diagnosis methods in the rotating machinery, this paper presents a hybrid method that combines the wavelet with neural networks theory. Both the blindness of framework designs for BP neural networks and the problem of nonlinear optimizations were solved and this method was used in rotating machinery fault diagnosis. The research shows that this method is feasible and effective and can be applied to the other rotating machinery fault diagnosis.

Abstract: Accident reconstruction model of lifting crane was founded based on FEA, investigation date and expertise. It simulated the lifting conditions and the change of loading was to be found out. The accident scene would be reconstructed in tine and space domain. It would greatly increase the analysis precision of accident and could provide a scientific foundation for accident judgments.

Abstract: A method combined ant colony algorithm with particle swarm optimization algorithm was designed for solving multi-objective flexible job shop scheduling problem in this paper. In the combined algorithm the start position of ants was marked by particles optimum position obtained by particle swarm optimization algorithm. Then the traditional ant colony algorithm was improved and was used to search the global optimum scheduling. The combined algorithm was validated by practical instances. The results obtained have shown the proposed approach is feasible and effective for the multi-objective flexible job shop scheduling problem.

Abstract: The mid-long term electric load forecasting provide essential data for the grid planning, it is helpful to optimize the planning of the power system. According to such features in mid-long term forecasting as small samples, poor information, uncertainty and nonlinearity, we can use the verhulst model in the grey system to do the forecasting. But in thinking of the differences of the sampling and the variations of the original sequence, the verhulst can’t do the forecasting exactly. So, through the method of doing equal-interval quantization and reforming the background value to the original sequence, we have established the improved verhulst model. The improved model is applied to the electric load prediction of one district and the accuracy of the min-long term load forecasting can be enhanced by our model.

Abstract: In this paper, we numerically investigate the chaotic behaviors of a new fractional-order system. We find that chaotic behaviors exist in the fractional-order system with order less than 3. The lowest order we find to have chaos is 2.4 in such system. In addition, we numerically simulate the continuances of the chaotic behaviors in the fractional-order system with orders from 2.7 to 3. Our investigations are validated through numerical simulations.