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Simulation, analysis and optimal design of fuel tank of a locomotive

机译:机车油箱的仿真分析与优化设计。

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In this paper, fuel tank of the locomotive ER 24 has been studied. Firstly the behavior of fuel and air during the braking time has been investigated by using a two-phase model. Then, the distribution of pressure on the surface of baffles caused by sloshing has been extracted. Also, the fuel tank has been modeled and analyzed using Finite Element Method (FEM) considering loading conditions suggested by the DIN EN 12663 standard and real boundary conditions. In each loading condition, high stressed areas have been identified. By comparing the distribution of pressure caused by sloshing phenomena and suggested loading conditions, optimization of the tank has been taken into consideration. Moreover, internal baffles have been investigated and by modifying their geometric properties, search of the design space has been done to reach the optimal tank. Then, in order to reduce the mass and manufacturing cost of the fuel tank, Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ) and Artificial Neural Networks (ANNs) have been employed. It is shown that compared to the primary design, the optimized fuel tank not only provides the safety conditions, but also reduces mass and manufacturing cost by %39 and %73, respectively.
机译:在本文中,对ER 24型机车的燃油箱进行了研究。首先,通过使用两相模型研究了制动期间燃料和空气的行为。然后,提取了由晃动引起的挡板表面上的压力分布。此外,考虑到DIN EN 12663标准建议的负载条件和实际边界条件,已使用有限元方法(FEM)对燃油箱进行了建模和分析。在每种加载条件下,都已确定了高应力区域。通过比较由晃荡现象和建议的装载条件引起的压力分布,已考虑了储罐的优化。此外,已经对内部挡板进行了研究,并通过修改其几何特性来进行设计空间的搜索,以达到最佳罐体。然后,为了减少燃料箱的重量和制造成本,已采用非支配排序遗传算法(NSGA-Ⅱ)和人工神经网络(ANN)。结果表明,与主要设计相比,优化的燃油箱不仅提供了安全条件,而且质量和制造成本分别降低了39%和73%。

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