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• W4384993124 abstract "Understanding the contribution of piston effect and train-induced airflow to the ventilation of underground subway stations is essential to design efficient ventilation systems. To this aim, numerical models using computational fluid dynamics (CFD) have been used to recreate existing stations with a number of simplifying assumptions. However, the large variety of station configurations as well as types of sources influencing the airflow makes the generalization to other cases difficult. This study intends to predict numerically the train-induced wind affecting the climate of subway stations perceived on the platforms, and a comparison of these numerical predictions with field tests in an actual station is provided and extensively discussed. A simplified geometry of a station, where the ventilation is mainly realized by the piston effect caused by the train movement, is used to implement a scenario of a train passing through the station, with dynamic meshing techniques, and background wind is included in one configuration. Experimental measurements at 9 locations along the station's platform, repeated in order to improve statistical accuracy and the reproducibility of the results, provide data that can be compared with the corresponding numerical simulation. Numerical to experimental comparison is based on quantification of the peaks due to ingoing and outgoing trains through parameters like peak value, skewness and kurtosis. It is found that the main features of the airflow are well captured by the model, but the differences observed also highlight the challenges of simulating the as-build environment. Several non-dimensional metrics proposed in this paper can be used for comparison with other papers, so that a validated numerical model can be a relevant tool to calculate different velocity scenarios for trains and within different station architectures, supporting the design of ventilation systems to improve the comfort and safety of passengers." @default.
• W4384993124 created "2023-07-22" @default.
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• W4384993124 date "2023-10-01" @default.
• W4384993124 modified "2023-10-14" @default.
• W4384993124 title "CFD model for airflow in a subway station compared to on-site measurements: The challenges of as-built environment" @default.
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• W4384993124 doi "https://doi.org/10.1016/j.tust.2023.105248" @default.
• W4384993124 hasPublicationYear "2023" @default.
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