A five-dimensional digital twin model of bogie frame with a new approach for accumulation fatigue damage

The fatigue failure of the rail vehicle bogie frame is primarily attributed to nonlinear fatigue damage under complex loading conditions. As one of the key technologies for promoting digitization in the field of rail transport, the related studies focusing on nonlinear fatigue damage assessment of the bogie frame based on a digital twin are being developed. In response to this case, a five-dimensional digital twin model of the bogie frame with a new approach for accumulation fatigue damage is established. To enhance the accuracy of the fatigue damage assessment in the digital twin model, an improved Manson–Halford nonlinear cumulative analytical model is presented based on the analogy between the decomposition of organic matter in ecology and the degradation of mechanical properties of materials. Additionally, to boost the efficiency of mapping between the physical entity and the virtual entity based on physical programming and particle swarm optimization. The proposed digital twin model uniquely merges data-driven and mechanics-driven methodologies, offering a robust solution for the structural design and durability optimization of the bogie frame.