Computational Methods in Engineering

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Articulated liquid cargo vehicles transporting inflammable fuels and dangerous chemical products require special consideration when traveling on urban roads or cruising at highway speeds. The road safety and handling of these kinds of vehicles may be adversely affected when negotiating sharp turns or travelling on slippery roads, which may result in either lateral instabilities or complete rollover of these tanker vehicles. Moreover, directional instabilities in these kinds of vehicle may also introduce an excessive yaw swing or may initiate the jack- knifing of the articulated tanker trucks. In order to overcome the instabilities of these tanker vehicles, installation of lateral baffles in the form of separating walls in the tanker were considered. The static roll and yaw plane models of these vehicles including lateral translation of the liquid inside the tank were developed. Using the static roll model, the rollover threshold of the vehicle is analyzed and the effect of these separating walls on the stability of the vehicle is studied. The yaw plane model is then used to predict the transient response and stability of the tanker vehicle under various road maneuvers. The governing differential equations were solved numerically to obtain the simulation results and optimum values of the parameters. Keywords: Tanker, Vehicle, Stability, vehicle dynamic, rollover, lateral baffles

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In this paper, a robust optimization method is developed to solve the Satellite Launch Vehicle (SLV) trajectory design problem in the presence of uncertainties using a powerful Particle Swarm Optimization (PSO) algorithm. Given the uncertainties such as uncertainties in the actual values ​​of aerodynamic coefficients, engine thrust, and mass in the ascent phase of a SLV, it is important to achieve an optimal trajectory that is robust to these uncertainties; because it improves the flight performance, reduces the workload of the guidance-control system, and increases the reliability of the satellite. For this purpose, first the optimization problem is considered by using the criterion of minimizing the flight time of the SLV as a cost function, and three-dimensional equations of motion as constraints governing the problem. Then, by adding the mean parameters and the standard deviation of uncertainties in the cost function, a robust optimizer model is developed and the algorithm is used to numerically optimize the model. Monte Carlo's perspective has also been used to analyze the results of uncertainties and their continuous feedback to the optimization model. Finally, the optimal trajectory is obtained that is robust to the uncertainties. The resulting simulation results show the accuracy of this claim.