Method for constructing longitudinal evolution model of in-service ballastless seamless turnout considering resistance update

By using the finite element method and parametric modeling, combined with resistance curve drift analysis, and dynamically updating resistance parameters, the problem of insufficient accuracy in the service status modeling of seamless turnouts is solved. This achieves high-precision longitudinal evolution model reconstruction and long-term stability, supporting intelligent maintenance decisions throughout the entire life cycle of seamless turnouts.

CN121257237BActive Publication Date: 2026-03-27SOUTHWEST JIAOTONG UNIV
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Patent Information

Application Number
CN202511833526.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-12-08
Publication Date
2026-03-27
Estimated Expiration
2045-12-08

AI Technical Summary

Technical Problem

Existing seamless turnout modeling theories fail to fully consider the influence of longitudinal residual stress and residual deformation of rails during service, resulting in limited mapping accuracy of digital twin models. Furthermore, there is a lack of dynamic updating methods for resistance parameters in multi-load step simulation calculations, affecting the scientific nature of safety assessments and maintenance decisions.

Method used

By employing the finite element method and parametric modeling, and combining historical data on rail displacement and fastener resistance, resistance parameters are dynamically updated through resistance curve drift analysis and equivalent processing. This constructs a longitudinal evolution model for ballastless seamless turnouts, supporting multi-load step iterative calculations and nonlinear solutions, thereby achieving high-precision reconstruction of service status.

Benefits of technology

It achieves high-precision restoration of the longitudinal service state of ballastless seamless turnouts, with longitudinal displacement error controlled within 2×mm and maximum longitudinal force error of 0.02kN, ensuring the stability and reliability of the model under long-term cyclic loads, supporting the deep integration of digital twin technology, and reducing operation and maintenance costs.

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Abstract

The application provides a method for constructing a longitudinal evolution model of an in-service ballastless seamless turnout considering resistance updating, and belongs to the technical field of rail transit. The method comprises the following steps: step 1, parameterized modeling of the seamless turnout; step 2, construction of boundary conditions and equilibrium equations; step 3, resistance curve drift analysis and equivalent processing; step 4, dynamic updating of resistance parameters; and step 5, nonlinear solving and model construction. The application can extend the modeling theory of the ballastless seamless turnout from the design reference state to the service state. Compared with the traditional method, the application also supports dynamic updating of resistance parameters in multi-load step iteration calculation, and can more accurately simulate the longitudinal creeping behavior of the ballastless seamless turnout. The application can be combined with digital twin technology to provide theoretical support for the service state reconstruction, model correction and safety evaluation of the seamless turnout.
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