A traffic model based on the road surface conditions during adverse weather is presented. The surface of a road is affected by snow, compacted snow, and ice, which affects the traffic behavior. In this paper, a new macroscopic traffic flow model based on the transition velocity distribution is proposed which characterizes traffic alignment under adverse weather conditions. Two examples are considered to illustrate the effect of the transition velocity behavior on traffic velocity and density. Simulation results are presented which show that this model provides a more accurate characterization of traffic flow behavior than the well known Payne-Whitham model. The proposed model can be used to reduce accidents and improve road safety during adverse weather conditions.
Recently power crises are increasing day by day in Pakistan due to shortage of energy resources. The financial position of Pakistan is too weak and not in position to install new power projects for the production of electrical power to meet the demand as per requirement. So every consumer is trying to install the power producing devices to meet the demand inorder to run their institutional laboratories, offices, commercial plants and industrial machines. The generator is also one of the power producer device to meet the consumers demand to supply the electrical power to the load in absence of failure of power supply from utility company. A single large unit is very expensive to run the small loads and consume large amount of fuel, so parallel connection of two small generators is very beneficial to meet the demand as per requirement, result in cost saving, and less fuel consumption. QUEST Campus Larkana has installed two 50KVA generators in parallel to supply the required power to the load in absence of power supply to run their offices, workshops and laboratories, this minimize the cost, and increase the reliability of the system. The MATLAB simulation model is developed to analyze the performance of single unit generator and parallel connected generators.
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