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The existing multi-objective wheel profile optimization methods mainly consist of three sub-modules: (1) wheel profile generation; (2) multi-body dynamics simulation (MBS); (3) an optimization algorithm. For the first module, a comparably conservative RSFT (rotary-scaling fine-tuning) method, which introduces two design variables and an empirical f...
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... Wheel transversal profiles significantly impact vehicle dynamic behavior as worn and damaged profiles can adversely affect vehicle traction and braking operations, while threatening running stability and safety, increasing the risk of derailment [3]. Therefore, there is a strong interest in developing approaches and methodologies for designing optimal slow-wear wheel profiles [4]. ...
Railway infrastructure relies on the dynamic interaction between wheels and rails; thus, assessing wheel wear is a critical aspect of maintenance and safety. This paper focuses on the wheel–rail wear indicator T-gamma ( Tγ ). Amidst its use, it becomes apparent that Tγ , while valuable, fails to provide a comprehensive reflection of the actual material removal and actual contact format, which means that using only Tγ as a target for optimization of profiles is not ideal. In this work, three different freight wagons are evaluated: a meter-gauge and a broad-gauge heavy haul vehicles from South American railways, and a standard-gauge freight vehicle operated in Europe, with different axle loads and dissimilar new wheel/rail profiles. These vehicles are subjected to comprehensive multibody simulations on various tracks. The simulations aimed to elucidate the intricate relationship between different wear indicators: Tγ , wear index, material removal, and maximum wear depth, under diverse curves, non-compensated lateral accelerations ( A nc ), and speeds. Some findings showed a correlation of 0.96 between Tγ and wear depth and 0.82 between wear index and material removed for the outer wheel. From the results, the Tγ is better than the wear index to be used when analyzing wear depth while the wear index is more suited to foresee the material lost. The results also show the low influence of A nc on wear index and Tγ . By considering these factors together, the study aims to improve the understanding of wheel–rail wear by selecting the best wear analysis approaches based on the effectiveness of each parameter.
... It is efficient enough with lower computation effort that many researchers use to study dynamic vehicle responses [15][16][17][18] and wheel-rail contact characteristics. 19,20 The flexible track method further considers the influence of vibrations of the track and structures such as the tunnel, subgrade and bridge, based on the accurate wheel-rail spatial dynamic coupling model. [21][22][23] It can be realized by co-simulation of multi-body dynamic software and finite element software, 24-27 directly establishing vehicle model and realizing wheel-rail contact simulation in FEM software [28][29][30][31] such as ANSYS or ABAQUS, or creating the dynamic equations of vehicle-track (and other structures) coupling system by self-developed program. ...
Globally, rail transit is developing toward higher speeds, larger axle weights, and greater environmental friendliness. The more and more complex wheel–rail interaction will result in the dynamic responses of vehicles, tracks and other structures needing more in-depth theoretical research. However, most existing models for dynamic simulations of the vehicle–track coupling system need to extend the model on both sides of the concerned region to eliminate the boundary effect. To a certain extent, this kind of process method increases the computational effort. To overcome this disadvantage, a hybrid model combined with the analytical method and finite element method was proposed. The moving support system (including transition nodes) was specially established referring to the analytical solution of rail deflection based on the Winkler elastic foundation beam theory to realize the combination of the two methods. Two examples were presented to verify the stability and accuracy of the proposed model. The comparison results show that simulation results of vertical wheel–rail forces and track vibrations are almost consistent with the existing model. Furthermore, the calculation efficiency was discussed and certificated under different long-marshalling trains, with an obvious speedup factor that could be more than 2.5 for 16-marshalling train. The proposed model has a wide application prospect in the vehicle–track coupling analysis of long-marshalling trains, especially for heavy haul railways with hundreds of vehicles.
... The effective measures to reduce the wheel-rail wear are mainly based on five aspects [14]: (1) wheel-rail contact mechanics, (2) vehicle/track design, (3) suspension parameter optimisation, (4) wheel-rail profile optimisation, and (5) track layout optimisation. This paper focuses on the optimisation of rail profiles. ...
... This technical solution can potentially decrease the amount of kinematic running resistance of railway vehicles and enhance their safety during movement, in comparison to traditional TKS wheel designs. Three different designs of the PKS wheel were developed 63,64 , which are depicted in Fig. 2 along with their 3D models. These designs are referred to as Variant 1, Variant 2, and Variant 3. ...
... These models have considered all real allowed movements of individual bodies www.nature.com/scientificreports/ and other specifics of these virtual models 62,63 . The created multibody models of the undercarriage with the TKS wheels and with the PKS wheels are shown in Fig. 3. ...
... An issue of sufficient strength of the PKS wheels is solvable by a proper design and a proper choice of materials for their production. The study, which has been developed for specific input parameters has proven, that the designs of the PKS can withstand the prescribed load acting on the analysed mechanical system 53,63 . ...
Urban railway vehicles are important means of transport in towns and cities due to their high capacity, power source, and low running resistance, which make them efficient for operation. Although these properties are considered advantages, there is still room for improvement in their operational efficiency. The main objective of this article is to investigate the impact of railway wheel design on the level of kinematic running resistance, which is expressed as the amount of mechanical energy losses during the interaction of wheels with rails. This research focuses on simulation computations of two variants of wheel design schemes: the traditional design scheme (TKS) and a perspective design scheme (PKS) characterized by a rotating flange independently of the wheel tread surface. Two undercarriage multibody models have been created, one with TKS and one with PKS, and simulation computations have been performed for running speeds of 10 km/h, 20 km/h, 30 km/h, and 40 km/h on track models in curves with radii of 20, 50, 100, 150, 200, and 250 m. The evaluated indicators affecting the level of mechanical energy losses were creep forces, slip velocities, and average power. The most important findings of this study are that the PKS design scheme resulted in lower values of all assessed parameters.
... results have been shown to be consistent with measured wear results [2,[12][13][14][15][16]. In addition, this method has been widely used in areas such as wheel-rail profile optimization [18][19][20] and wheel-rail life prediction [2,21]. The dynamic model is an important submodel for predicting wheel-rail wear. ...
To investigate the influence of the structural deformation of the wheelset and track on rail wear in the longitudinal and lateral directions, a rail wear prediction model is established that can calculate the three-dimensional distribution of rail wear. The difference between the multi-rigid-body dynamic model and the rigid-flexible coupled dynamic model, which considers the structural flexibility of the wheelset and track, is compared in terms of the three-dimensional distribution of rail wear. The results show that the three-dimensional distributions of rail wear predicted by the two models are relatively similar. There is no obvious difference in the wear band, and the rail wear in the longitudinal direction is almost identical. The cross sections of the worn rail shapes determined by the two models are essentially the same, with a maximum difference of 3.6% in the average value of the wear areas of all cross sections. The track irregularity is the main reason for the uneven distribution of rail wear in the longitudinal direction. The position where the rail wear is more pronounced hardly varies with the evolution of the rail wear. It is recommended to use a multi-rigid-body dynamic model for the prediction of rail wear, which allows both calculation accuracy and efficiency.
... Although the lateral stability of railway vehicles can be strengthened with the help of advanced mechanisms or active suspension systems [3][4][5][6][7][8], the optimisation of conventional passive suspension elements still could be considered as one of the efficient methods. Several studies on improving hunting stability of wheel-rail vehicles based on the optimisation of suspension parameters [9][10][11] and wheel-rail profiles [12][13][14][15] have been carried out. In general, the design optimisation of a mechanical system is multidisciplinary and the task is to find effective trade-off solutions for the complicated and conflicting design criteria [16]. ...
An adequate hunting stability margin is required through the optimisation and matching of bogie suspension parameters for high-speed trains. Moreover, the dynamics design is particularly important for the robust lateral stability to adapt to wheel–rail wear and track deformation. The hunting stability margin of vehicles, as well as the wheel–rail contact state adaptability should be taken into account. In this regard, the robust hunting stability Pareto optimisation of bogie suspension parameters for different wheel–rail wear stages is executed. A method for the centralised optimisation of key bogie suspension parameters based on vehicle lateral robust stability is presented, and the principle of two typical parameters matching for high-speed vehicles is summarised. In addition, in order to make the vehicle automatically adapt to different wheel–rail geometry contact states without any sensors and control systems, a new idea of frequency-dependent stiffness (SDF) of yaw damper is proposed to ensure the lateral stability margin especially in extreme wheel–rail contact states, which is verified through the vehicle linear system stability and ride comfort comparative analysis. Finally, the adaptive stabilisation mechanism of the vehicle with the frequency-dependent stiffness of yaw damper is clarified.
... Then the critical speed, contact stress and rolling diameter satisfy the constraints, which significantly reduces the removal of material. Ye et al. 12 proposed a rotary-scaling fine-tuning(RSFT) method to fine-tune the traditional wheel profile. Based on the Kriging Surrogate Model (KSM), an optimization function representing the relationship between wheel profile and wheel-rail wear is established. ...
According to the characteristics of the metro vehicles running on the same track leading to a similar wheel wear, a clustering method based on k-means is proposed. The weighted wheel flange height of Sh and qR, and wheel flange thickness of Sd are used as clustering parameters. This paper classifies the treads of the wheels to be repaired and obtains a typical worn wheel profile to reprofile the wheels. Under the premise of ensuring the operation safety of vehicles, the wheel profile optimization model is established for a typical worn wheel profile based on the minimum repair volume. The optimized profile is used as the reprofiling template for all wheels in the same classification. Finally, based on the reprofiling standard for the wheel diameter difference between the left and right wheels, the optimization reprofiling of the wheel profile is achieved. The research results show that the proposed optimization strategy base on cluster analysis can significantly reduce the material removal.
... Therefore, to address the drawbacks in related researches, this research proposes an efficient high accuracy modeling scheme for spacecraft reaction wheel using RBFNN. Many researchers have proposed RBFNN as a modeling paradigm in different research areas [9][10][11][12][13][14][15]. For instance, in [9], RBFNN had been used for online modeling and adaptive control of nonlinear systems. ...
... The results proved the effectiveness of the high accuracy modeling capability for RBFNN over multilayer perceptron in modeling dynamic systems. Recently, Yunguang et al. [13][14][15] suggested an optimization module based on radial basis function and particle swarm optimization to develop a wheel profile fine-tuning system. Simulation results have proven that the proposed optimization algorithm can recommend an optimal wheel profile according to train operators' needs. ...
Reaction wheels are crucial actuators in spacecraft attitude control subsystem (ACS). The precise modeling of reaction wheels is of fundamental need in spacecraft ACS for design, analysis, simulation, and fault diagnosis applications. The complex nature of the reaction wheel leads to modeling difficulties utilizing the conventional modeling schemes. Additionally, the absence of reaction wheel providers' parameters is crucial for triggering a new modeling scheme. The Radial Basis Function Neural Network (RBFNN) has an efficient architecture, alluring generalization properties, invulnerability against noise, and amazing training capabilities. This research proposes a promising modeling scheme for the spacecraft reaction wheel utilizing RBFNN and an improved variant of the Quantum Behaved Particle Swarm Optimization (QPSO). The problem of enhancing the network parameters of the RBFNN at the training phase is formed as a nonlinear constrained optimization problem. Thus, it is proposed to efficiently resolve utilizing an enhanced version of QPSO with mutation strategy (EQPSO-2M). The proposed technique is compared with the conventional QPSO algorithm and different variants of PSO algorithms. Evaluation criteria rely upon convergence speed, mean best fitness value, stability, and the number of successful runs that has been utilized to assess the proposed approach. A non-parametric test is utilized to decide the critical contrast between the results of the proposed algorithm compared with different algorithms. The simulation results demonstrated that the training of the proposed RBFNN-based reaction wheel model with enhanced parameters by EQPSO-2M algorithm furnishes a superior prediction accuracy went with effective network architecture.
... Most of the existing railway wheel profile optimization methods involve the purpose of reducing wear, where the accumulated T-gamma ( ) value is often used as an indicator to evaluate the degree of wear, considering a small T-gamma value representing less material loss [1]. This approach, however, faces the following two issues: ...
... To demonstrate the correctness and feasibility of the proposed WCI, simulations are performed for a large number of different wheel profiles. The rotary-scaling fine-tuning (RSFT) method proposed in Ref. [1] is used to produce 95 different wheel profiles. The basic idea of the RSFT method is to introduce two design variables ( 1 , 2 ) and an empirical formula to modify the baseline profile's equivalent conicity and flange thickness. ...
Most of the existing railway wheel profile optimization methods involve the purpose of reducing wear, where the T-gamma value is often treated as an indicator to evaluate the degree of wear, considering a small T-gamma value representing less material loss. A small T-gamma value, however, implies that the wheel-rail contact points are likely to occur in the vicinity of the wheel's nominal rolling circle, and the optimized wheel profile obtained with the target of minimizing the T-gamma value may result in a concentrated distribution of wheel-rail contact points around the nominal rolling circle, accelerating the formation of hollow wear. Using the T-gamma value as the optimization target, therefore, cannot guarantee that the wheel profile still has excellent wear performance during long-term service. Aiming at this issue, an indicator, named wear concentration index (WCI), is developed to assess the degree of wheel material loss and the shape stability of wheel profiles. Numerous simulations demonstrate the feasibility and superiority of the index WCI and indicate that this index can be used as an alternative to the target T-gamma in wheel profile optimization.
... However, owing to the MBS technology, the optimization of wheel profiles has begun to form a systematic research topic. The wheel profile optimization methods proposed in the past two decades have been reviewed in Ref. [7], in which, it has been concluded that the MBS-based wheel profile optimization methods mainly include three sub-modules: (1) candidate profile generation, (2) MBS to obtain the dynamics responses, and (3) optimization algorithm to find the optimal wheel profile. In this section, we briefly introduce the first and third modules. ...
... For wheel profile optimization purposes, some methods have been proposed in the past two decades to generate candidate profiles. These methods with different strategies can be concluded into three categories [7]: (1) moving point method [8], (2) element combination method [11], and (3) scaling method [12]. The moving point method is mainly to discrete the wheel profile into a series of points, then set the points in the non-optimization region as fixed points, and the points in the optimization region as movable points, where the vertical coordinates of the movable points are defined as design variables. ...
... Moreover, the height of the flange of the generated profile is severely altered. Based on the above consideration, this paper introduces an analytical method, the RSFT method that was first proposed in Ref. [7], to efficiently generate a large number of candidate profiles for optimization purposes. ...
With the expansion of urbanization, more and more metro vehicles shuttle on dedicated railway lines, leading to serious wheel wear and reduced passenger comfort, it is therefore of interest to design a wheel profile that matches well with the dedicated lines. This paper presents a wheel profile optimization procedure and consists of a series of steps. Firstly, taking the LM profile, a widely used wheel profile in China metro vehicles, as an example, the rotary-scaling fine-tuning (RSFT) method is introduced to generate a large number of candidate profiles. Secondly, to quickly and reliably establish the relationship between the candidate profiles and the objectives to be optimized obtained by multi-body dynamics simulation (MBS), the radial basis function (RBF) is introduced to reduce the number of MBS runs. Thirdly, the established RBF-based function is treated as the objective function of the particle swarm optimization (PSO) algorithm to develop a wheel profile that simultaneously considers wheel wear and ride comfort for the B-type metro vehicles shuttling on a Beijing metro line. Finally, this paper compares the wheel-rail contact characteristics, critical speed, and simulated long-term wear distribution of the LM profile and the optimized profile named as LMopt. The results show that the LMopt profile, generally, has better performance, demonstrating that the RSFT-RBF-PSO procedure is of engineering significance.
