Droplet transmission is a critical pathway for the spread of respiratory infectious viruses. A thorough understanding of the mechanisms of droplet dispersion within subway carriages is crucial to curb the widespread transmission of the virus. This study utilizes computational fluid dynamics (CFD) to establish a full-scale numerical model of a subway carriage. The numerical model and droplet evaporation behavior are validated using experimental data and literature. The impact of primary parameters such as the initial droplet size, release velocity, release position, relative humidity, and passenger density on the droplet diffusion and probability of infection for passengers is investigated. The results indicate that large droplets (100 μm) are deposited on the carriage floor before complete evaporation, while tiny droplets (10 μm) evaporate rapidly, leading to a longer suspension time in the air within the carriage. The infected passenger’s position influences the ventilation system’s efficiency in removing the droplets; removal takes significantly longer when the infected passenger is closer to the carriage end. Additionally, a low relative humidity (35%) and high passenger density (4 p/m²) result in more droplets being trapped by passengers’ bodies. The infection probability for passengers depends on the initial size and quantity of droplets trapped by their bodies. Maintaining higher relative humidity levels and limiting the passenger numbers within the subway carriage can reduce the number of droplets captured by passengers’ bodies, thus helping to reduce the infection probability of fellow passengers.

It is a challenge to efficiently and accurately predict train dynamic responses during complex collisions. In this paper, a novel numerical simplification method for high-speed rail vehicles during complex impact configurations is proposed. The central section of high-speed rail vehicles is a sandwich corrugated hollow double-shell structure. Starting with a baseline detailed finite element (FE) model of a high-speed train, the central section was first simplified as a solid single-shell structure. A parametric study with various simplification thickness ratios of the simplified FE rail vehicle model in different longitudinal rigid-wall collisions and lateral rigid-cylinder impacts was then performed using LS-DYNA. Furthermore, a correlation and analysis (CORA) objective rating method was used to evaluate the related responses between the simplified and detailed baseline FE rail vehicle models. The results demonstrate that the simplified FE model could effectively predict the rail vehicle impact responses. The displacement and impact force time histories of the simplified vehicle model with a thickness ratio of 0.38 matched closely with the results of the baseline detailed FE model under both longitudinal and lateral impacts (total combined CORA rating score: 93%). The rail vehicle impact deformations of the simplified vehicle model were similar to those of the baseline detailed model. The application of the simplified vehicle FE model substantially reduced the computational time (approximately 55% reduction). This work provides a solid basis for efficiently exploring train impact responses in complex collisions, and will be especially useful for train occupant injury assessment.

The large scale and long calculation times are unavoidable problems in modeling honeycomb structures with large sizes and dense cells. The cell magnification equivalent is the main method to solve those problems. This study finds that honeycomb structures with the same thickness-to-length ratios have the same mechanical properties and energy absorption characteristics. The improved equivalent finite element models of honeycomb structures with the same thickness-to-length ratios were established and validated by experiments. Based on the validated finite element model of the equivalent honeycomb structures, the out-of-plane compression behaviors of honeycomb structures were analyzed by LS-DYNA software. The results show that the performance of honeycomb structures is not equivalent before and after cell magnification. Thus, the cell magnification results were further subjected to CORA (correlation analysis) to determine the magnification time and prove the accuracy of the cell magnification time through drop-weight impact tests. In addition, a first-order decay exponential function (ExpDec1) for predicting cell magnification time was obtained by analyzing the relationship between the cell wall length and the cell magnification time.