Optimization of the target profile for asymmetrical rail grinding in sharp-radius curves for high-speed railways

Zeng, Wei; Yang, Yueting; Qiu, Wensheng; Xie, Huan; Xie, Suchao

doi:10.1177/1687814016687196

Cited by 8 publications

(3 citation statements)

References 11 publications

(13 reference statements)

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“…Both the NSGA-II genetic algorithm [13,32] and the AMGA algorithm [33] exhibit robust global exploration capabilities, allowing for simultaneous comparison of multiple individuals and demonstrating potential parallelism. Moreover, they possess strong scalability, facilitating easy improvements [34]. Therefore, the two major genetic algorithms for the multi-objective optimization of train dynamic performance are both reliable.…”

Section: Multi-objective Optimization 61 Theoretical Analysismentioning

confidence: 99%

Multi-Objective Optimization of Bogie Stability for Minimum Radius Curve of Battery Track Engineering Vehicle

Shen,

Zhao,

Wang

et al. 2024

Applied Sciences

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A battery track engineering vehicle faces challenges such as derailment and other safety concerns when navigating an R20m minimum radius curve, primarily owing to its low vertical and horizontal stabilities. To address these issues, a methodology integrating genetic optimization algorithms with a rigid and flexible coupled multi-body dynamics simulation is proposed to optimize the primary suspensions of the bogie of the vehicle. Initially, a multi-objective optimization model combining rigid and flexible coupled multi-body dynamics of battery track engineering vehicles with a genetic optimization algorithm was formulated. Subsequently, the optimal Latin hypercube design was applied to analyze the sensitivity of vertical and horizontal stability to various suspension parameters. Finally, a non-dominated sorting genetic algorithm (NSGA-II) and an archive-based micro genetic algorithm (AMGA) were applied to optimize the primary suspensions to enhance stability. Consequently, a set of optimal suspension parameter combinations was obtained. A notable enhancement was observed in the lateral stability of the optimized battery track engineering vehicles by 23.33% and in the vertical stability by 3.5% when traversing the R20m minimum radius curve, thereby establishing a theoretical foundation for further improving the running safety of railway vehicles and resolving the shortcomings of less research on the smallest radius curve.

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Section: Multi-objective Optimization 61 Theoretical Analysismentioning

confidence: 99%

Multi-Objective Optimization of Bogie Stability for Minimum Radius Curve of Battery Track Engineering Vehicle

Shen,

Zhao,

Wang

et al. 2024

Applied Sciences

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“…8. There are also known methods [1][2][3] of dynamic simulation of rolling stock with the analysis of wheel/rail stresses. The above-mentioned methods and approaches for rail head profile restoration by grinding are based on the repetition of an initial rail profile.…”

Section: Analysis Of Rail Grinding Profilesmentioning

confidence: 99%

Estimating influence of rail profile shape on lateral wear of rail and wheel after grinding of 60E1 and R65 rails

Ivanovs

Gavrilovs

Бойко

et al. 2020

19th International Scientific Conference Engineering for Rural Development Proceedings

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The problem of lateral wear intensity for rails and wheels has not been resolved at the present, despite many studies in this area. This article aims to provide evidence of the influence of rail head profile after grinding on the lateral wear of interacting surfaces of rail and wheel in curves and straight sections of 1520 mm track for Latvian Railways. The article suggests the method of creation of asymmetric repair profiles for rail grinding taking into account the shape of wear for wheel profile. For this purpose, statistical data were collected on the most typical form of wear for wheel profiles of railcars on the Latvian Railway. Asymmetrical profiles for rail grinding have been developed and the basic primary grinding angles for straight and curved sections of the track have been defined by means of geometric modeling. As a result, the contact points of rolling surface of wheels were shifted to the centre of the curve. The difference in wheel radii reached 5.6 mm in one wheel pair, and the fitting of wheel pairs was improved by 4 times. At the final stage of the study, the corrective profiles for grinding the rail head were developed utilizing SolidWorks Simulation, taking into account the most typical wear of the wheel profile, which increased the contact areas and as a result reduced the stresses up to 18 % on the outer rail in the curve with a radius of 800 m. As a result, for the outer rail, part of the load shifts from the wear zone of the wheel flange to the root of the wheel flange. For safety reasons, the stability coefficient of a worn wheel profile for the Latvian Railways with a flange angle of 66.8º was calculated in accordance with the rolling mode along developed asymmetric rail profiles. The calculated wheel stability reserve against derailing has a significant reserve. As an alternative to grinding, it was proposed to reduce the tilting of the outer rail and increase the tilting of the inner rail in curves.

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“…There have been a number of studies on this aspect, taking the w/r contact performance 6,7 or rail's service life as the optimization objective, 8 using different optimization algorithms to obtain the optimal grinding profile based on w/r contact theory. For instance, in order to improve the w/r contact performance and the curve negotiation ability, Zeng et al 2,9 proposed a new optimization method based on the Kriging surrogate model and the genetic algorithm to optimize the target profiles of the asymmetrical rail grinding in sharp-radius curves and the rail grinding in straight line for high-speed railway. Xiao and Liu 10 regarded the railhead silhouettes in differential rail cants as the rail grinding target profiles and obtained an optimal rail grinding target profile, while the equivalent conicity, contact stress, and grinding amount were taken as the evaluation indices.…”

Section: Introductionmentioning

confidence: 99%

A novel prediction method for rail grinding profile based on an interval segmentation approach and accurate area integral with cubic NURBS

Xie

Chen

Zeng

et al. 2014

Advances in Mechanical Engineering

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Rail grinding profile prediction in different grinding patterns is important to improve the grinding quality for the rail grinding operation site. However, because of high-dimensional and strong nonlinearity between grinding amount and grinding parameters, the prediction error and computational cost is relatively high. As a result, the accuracy and efficiency of conventional methods cannot be guaranteed. In this article, an accurate and efficient rail grinding profile prediction method is proposed, in which an interval segmentation approach is proposed to improve the prediction efficiency based on the geometric characteristic of a rail profile. Then, the accurate area integral approach with cubic NURBS is used as the grinding area calculation approach to improve the prediction accuracy. Finally, the normal length index is introduced to evaluate the prediction accuracy. The accuracy and stability of the proposed method are verified by comparing a conventional approach based on a practical experiment. The results demonstrate that the proposed method can predict the rail grinding profile in any grinding pattern with high accuracy and efficiency. Meanwhile, its prediction stability basically agrees with the conventional approach.

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Optimization of the target profile for asymmetrical rail grinding in sharp-radius curves for high-speed railways

Cited by 8 publications

References 11 publications

Multi-Objective Optimization of Bogie Stability for Minimum Radius Curve of Battery Track Engineering Vehicle

Multi-Objective Optimization of Bogie Stability for Minimum Radius Curve of Battery Track Engineering Vehicle

Estimating influence of rail profile shape on lateral wear of rail and wheel after grinding of 60E1 and R65 rails

A novel prediction method for rail grinding profile based on an interval segmentation approach and accurate area integral with cubic NURBS

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