Tunnel misalignment gentle device design method and system based on aerodynamic effect evaluation

By constructing an aerodynamic effect assessment model and using neural network prediction, a tunnel misalignment smoothing device was designed, which solved the aerodynamic effect problem caused by tunnel misalignment and improved the comfort and safety inside the tunnel.

CN122241801APending Publication Date: 2026-06-19SOUTHWEST JIAOTONG UNIV +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SOUTHWEST JIAOTONG UNIV
Filing Date
2026-02-06
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

Existing technologies cannot effectively address the local aerodynamic effects caused by tunnel misalignment, leading to increased aerodynamic pressure fluctuations and transient loads when trains pass through, affecting passenger comfort and driving safety.

Method used

By constructing an aerodynamic effect assessment model, using neural networks to learn nonlinear mapping relationships, and combining actual tunnel parameters to predict aerodynamic response, assess comfort and structural impacts, and inversely determine the parameters for designing tunnel misalignment and smoothing devices.

Benefits of technology

The precise design of the tunnel misalignment smoothing device was achieved, which effectively solved the aerodynamic effect problem caused by local geometric distortion, and improved passenger comfort and driving safety.

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Abstract

This invention provides a design method and system for a tunnel leveling device based on aerodynamic effect assessment, relating to the field of computer technology. The method includes: acquiring a sample dataset; performing aerodynamic effect simulation within the tunnel based on the sample dataset, obtaining aerodynamic effect baseline data corresponding to each set of sample parameters by calculating the train load characteristics and the response results of the flow field and stress field within the tunnel; constructing a surrogate model based on the aerodynamic effect baseline data to obtain an aerodynamic effect prediction model; acquiring the actual parameters of the target tunnel and inputting these parameters into the aerodynamic effect prediction model to obtain aerodynamic response prediction results; assessing the aerodynamic effect impact based on the prediction results to obtain performance target parameters; and performing parameter inversion of the leveling device based on the performance target parameters to obtain the design parameters of the tunnel leveling device.
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