ABSTRACT

Railway bogies of the Y25 family are the most common type of freight bogies used in Europe. However, this family of bogies presents poor curving performance and a derailment history. Although numerical simulations are a powerful tool to study railway dynamics, derailment scenarios involve complex operational and vehicle conditions that increase the multivariate aspect of the problem. Thus, simulating all possible scenario variants is unfeasible from the computational perspective due to time and computational constraints. This paper proposes an approach based on a Response Surface Methodology to study the combined influence of uncertain parameters on the derailment potential of a railway vehicle. The potential of this approach is demonstrated using a real derailment as a case study. A set of scenarios is identified using a Design of Experiments approach, and is simulated on a commercial software. The response functions of the quantities used to assess derailment are generated, and the conditions that maximise the derailment potential are identified. The results reveal a combination of asymmetric loading, excessive speed, and Lenoir link failure may cause extreme wheel unloading in the study developed. This work reveals the advantages of a Response Surface Methodology to identify the conditions that maximise the derailment potential.

摘要

Y25 系列的铁路转向架是欧洲最常用的货运转向架。然而，该系列转向架的弯道性能较差，且有脱轨历史。尽管数值模拟是研究铁路动力学的有力工具，但脱轨场景涉及复杂的操作和车辆条件，从而增加了问题的多变量方面。因此，由于时间和计算限制，从计算角度模拟所有可能的场景变体是不可行的。本文提出了一种基于响应面方法的方法来研究不确定参数对铁路车辆脱轨潜力的综合影响。以真实的脱轨作为案例研究证明了这种方法的潜力。使用实验设计方法识别一组场景，并在商业软件上进行模拟。生成用于评估脱轨的量的响应函数，并确定使脱轨潜力最大化的条件。结果表明，不对称加载、超速和 Lenoir 连杆故障的组合可能会导致研究中的极端车轮卸载。这项工作揭示了响应面方法在确定最大化脱轨潜力的条件方面的优势。和 Lenoir 连杆故障可能会导致在研究中出现的极端车轮卸载。这项工作揭示了响应面方法在确定最大化脱轨潜力的条件方面的优势。和 Lenoir 连杆故障可能会导致在研究中出现的极端车轮卸载。这项工作揭示了响应面方法在确定最大化脱轨潜力的条件方面的优势。