Qinzhen Fang^1,2, Dongliang Peng^1,2, Lu Zeng^1,2,*, Zixuan Jiang^1,2

Journal on Artificial Intelligence, Vol.7, pp. 469-484, 2025, DOI:10.32604/jai.2025.073016 - 06 November 2025

Abstract To address the issues of small target miss detection, false positives in complex scenarios, and insufficient real-time performance in maglev train foreign object intrusion detection, this paper proposes a multi-module fusion improvement algorithm, YOLO11-FADA (Fusion of Augmented Features and Dynamic Attention), based on YOLO11. The model achieves collaborative optimization through three key modules: The Local Feature Augmentation Module (LFAM) enhances small target features and mitigates feature loss during down-sampling through multi-scale feature parallel extraction and attention fusion. The Dynamically Tuned Self-Attention (DTSA) module introduces learnable parameters to adjust attention weights dynamically, and, in combination with More >

Yan Li¹, Bailong Sun², Tian Li^2,*, Weihua Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1957-1970, 2025, DOI:10.32604/cmes.2025.069159 - 31 August 2025

Abstract High-speed maglev trains represent a key direction for the future development of rail transportation. As operating speeds increase, they face increasingly severe aerodynamic challenges. The streamlined aerodynamic shape of a maglev train is a critical factor influencing its aerodynamic performance, and optimizing its length plays a significant role in improving the overall aerodynamic characteristics of the train. In this study, a numerical simulation model of a high-speed maglev train was established based on computational fluid dynamics (CFD) to investigate the effects of streamline length on the aerodynamic performance of the train operating on an open… More >

Bailong Sun¹, Tian Li^1,*, Deng Qin¹, Yan Li²

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.2, pp. 371-385, 2025, DOI:10.32604/fdmp.2024.055519 - 06 March 2025

Abstract High-speed maglev trains (HSMTs) can run at high running speeds due to their unique design. The pressure waves that these trains generate while passing each other are therefore very intense, and can even have safety implications. In order to reduce the transient impact of such waves, the standard k-ε turbulence model is used in this work to assess the effect of railway spacing on the aerodynamic loads, pressure and surrounding flow field of 600 km/h maglev trains passing each other in open air. The sliding mesh technique is used to determine the relative motion between the More >

Lanxi Zhang¹, Yuming Peng¹, Yudong Wu^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.1, pp. 205-220, 2025, DOI:10.32604/fdmp.2024.056516 - 24 January 2025

Abstract The challenge of aerodynamic noise is a key obstacle in the advancement of low-pressure tube ultra-high-speed maglev transportation, demanding urgent resolution. This study utilizes a broadband noise source model to perform a quantitative analysis of the aerodynamic noise produced by ultra-high-speed maglev trains operating in low-pressure environments. Initially, an external flow field calculation model for the ultra-high-speed maglev train is presented. Subsequently, numerical simulations based on the broadband noise source model are used to examine the noise characteristics. The impact of the train speed and pressure level on noise generation is investigated accordingly. Subsequently, a… More >

Zun-Di Huang¹, Zhen-Bin Zhou^1,2,3, Ning Chang¹, Zheng-Wei Chen^2,3,*, Su-Mei Wang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 975-996, 2024, DOI:10.32604/cmes.2024.047664 - 16 April 2024

Abstract The safety and stability of high-speed maglev trains traveling on viaducts in crosswinds critically depend on their aerodynamic characteristics. Therefore, this paper uses an improved delayed detached eddy simulation (IDDES) method to investigate the aerodynamic features of high-speed maglev trains with different marshaling lengths under crosswinds. The effects of marshaling lengths (varying from 3-car to 8-car groups) on the train’s aerodynamic performance, surface pressure, and the flow field surrounding the train were investigated using the three-dimensional unsteady compressible Navier-Stokes (N-S) equations. The results showed that the marshaling lengths had minimal influence on the aerodynamic performance… More > Graphic Abstract