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For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.

The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.

By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.

Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.

This paper aims to present the design and fabrication of a rotary magnetostrictive energy generator, using to harvest the rotation energy of human knee joint.

A rotary magnetostrictive energy generator is presented in this paper. The harvester consists of six movable flat Terfenol-D rods, surround by the picked-up coils respective, and alternate permanent magnet (PM) array fixed in the upper cover of the stator. The harvester rotates like as a stepper motor, which has rotary electromagnetic power generating effect and impacted magnetostrictive power generating effect in its rotation. Modeling and simulation are used to validate the concept. A prototype of harvester is fabricated and subjected to the experimental characterization.

The size of proposed structure is control as 77 cm³, and its mass is about 0.21 kg. Huge induced voltage generated in the short-time impact situation, and that induced voltage in the harvester can up to 18.6 V at 0.32 s stepper rotation. Also, the presented harvester has good harvesting effects at low frequency human walking situation, which is suitable to be used for future researches of wearable knee joint applications.

A new concept of magnetostrictive harvester is presneted, which will be benefit for the application of human knee joint wearable. Also, this concept will give us more idea for collection of human movement energy.

The purpose of this paper is to propose an efficient method for detection and modification of erroneous branch parameters in real time power system simulators. The aim of the proposed method is to minimize the sum of squared errors (SSE) due to mismatches between simulation results and corresponding field measurements. Assuming that the network configuration is known, a limited number of erroneous branch parameters will be detected and corrected in an optimization procedure.

Proposing a novel formulation that utilizes network voltages and last modified admittance matrix of the simulation model, suspected branch parameters are identified. These parameters are more likely to be responsible for large values of SSE. Utilizing a Gauss-Newton (GN) optimization method, detected parameters will be modified in order to minimize the value of SSE. Required sensitivities in optimization procedure will be calculated numerically by the real time simulator. In addition, by implementing an efficient orthogonalization method, the more effective parameter will be selected among a set of correlated parameters to avoid singularity problems.

Unlike state estimation-based methods, the proposed method does not need the mathematical functions of measurements to simulation model parameters. The method can enhance other parameter estimation methods that are based on state estimation. Simulation results demonstrate the high efficiency of the proposed optimization method.

Incorrect branch parameter detection and correction procedures are investigated in real time simulators.