Determining the service life of a gondola car with an increased floor body safety factor
研究提出一种敞车底板优化设计，通过结构优化、概率建模和有限元分析，在不增加重量和成本的前提下，将等效应力降低最多91.6%，安全系数提高最多12.9倍，使用寿命延长1.22至2.07倍。
This study presents a newly optimized design for the gondola car body floor aimed at reducing mechanical wear and significantly extending service life without increasing structural weight or material costs. The scientific novelty of this study lies in the integration of structural optimization, probabilistic modeling, and finite element analysis to enhance the service life and reliability of the gondola car body floor while maintaining material and weight constraints. The study proposes a new mathematical model, which is built on the basis of reliability theory taking into account the physical and mechanical characteristics of the material and the load - it allows for accurate prediction of the service life of the gondola car based on the wear of the body floor structure. The study also introduces the concept of an operational safety factor, which accounts for variability in load and material strength, providing a more realistic measure of structural performance under real-world conditions. Using a combination of finite element analysis, statistical modeling, and a novel reliability-based mathematical approach, the mechanical behavior of the redesigned floor was evaluated under dynamic load conditions. The analysis demonstrated that the proposed floor geometry reduced equivalent stresses by up to 91.6% and improved the safety factor by up to 12.9 times compared to traditional designs. Statistical models, including normal and Weibull distributions, confirmed the extended durability of the redesigned gondola car body, with service life improvements ranging from 1.22 to 2.07 times. Notably, the use of cost-effective plain carbon steel was maintained, ensuring practical applicability. These results validate the effectiveness of structural optimization in enhancing the performance, reliability, and economic viability of freight rail vehicles.