AiHua Zhu, AiHua Zhu, Chaochao Ma, Jianwei Yang, Xin Hou, Hongxiao Li and Peiwen Sun
Considering that a meet between high-speed trains can generate aerodynamic loads, this study aims to investigate the effect of high-speed train meet on wheel wear at different…
Abstract
Purpose
Considering that a meet between high-speed trains can generate aerodynamic loads, this study aims to investigate the effect of high-speed train meet on wheel wear at different speeds to provide a more accurate wheel wear model and a new idea for reducing wheel wear.
Design/methodology/approach
The train speed was set at 250, 300, 350 and 400 km/h separately, and a vehicle system dynamics model was constructed using the parameters of an actual high-speed train on a line. The aerodynamic forces arising from constant-speed train meet were then applied as additional excitation. Semi-Hertzian theory and Kalker’s simplified theory were used to solve the wheel/rail contact problems. The wheel wear was calculated using Archard wear model. The effect of train meet on wheel wear was analyzed for the whole train, different cars and different axles.
Findings
According to the results, all wheels show a wear increase in the case of one train meet, compared to the case of no train meet. At 250, 300, 350 and 400 km/h, the total wheel wear increases by 4.45%, 4.91%, 7.57% and 5.71%, respectively, over the entire operational period. The change in speed has a greater impact on wheel wear increase in the head and tail cars than in the middle car. Moreover, the average wear increase in front-axle wheels is 1.04–2.09 times that in rear-axle wheels on the same bogie.
Practical implications
The results will help to analyze wheel wear more accurately and provide theoretical guidance for wheel repair and maintenance from the perspective of high-speed train meet.
Originality/value
At present, there is a lot of focus on the impact of high-speed train meet on the dynamic performance of vehicles. However, little research is available on the influence of train meet on wheel wear. In this study, a vehicle dynamics model was constructed and the aerodynamic forces generated during high-speed train meet were applied as additional excitation. The effect of train meet on wheel wear was analyzed for the whole train, different cars and different axles. The proposed method can provide a more accurate basis for wear prediction and wheel repair.
Details
Keywords
Peiwen Sun, Jianwei Yang, AiHua Zhu, Zhongshuo Hu, Jinhai Wang, Fu Liu and Xiaohui Wang
The CL60 steel wheels of subway vehicles operating on specific lines require frequent refurbishment due to rapid wear and tear. Considering this issue, MoS2-based and…
Abstract
Purpose
The CL60 steel wheels of subway vehicles operating on specific lines require frequent refurbishment due to rapid wear and tear. Considering this issue, MoS2-based and graphite-based solid lubricants are used to reduce the wear rate of subway wheels and extend their service life.
Design/methodology/approach
Under laboratory conditions, the effect of MoS2-based and graphite-based solid lubricants on the friction and wear performance of subway wheels and rails was evaluated using a modified GPM-60 wear testing machine.
Findings
Under laboratory conditions, MoS2-based solid lubricants have the best effect in reducing wheel/rail wear, compared to the control group without lubrication, at 2 × 105 revolutions, the total wheel-rail wear decreased by 95.07%. However, when three types of solid lubricants are used separately, the hardness evolution of the wheel-rail contact surface exhibits different characteristics.
Practical implications
The research results provide important support for improving the lifespan of wheel and rail, extending the service cycle of wheel and rail, reducing the operating costs of subway systems, improving the safety of subway systems and providing wear reduction maintenance for other high wear mechanical components.
Originality/value
The experiment was conducted through the design and modification of a GPM-60 testing machine for wear testing. The experiment simulated the wheel-rail contact situation under actual subway operation and evaluated the effects of three different solid lubricants, MoS2-based and graphite-based, on the wear performance and surface hardening evolution of subway wheel-rail.
Details
Keywords
Xie Yidong, Sun Peiweni, Li Qiang, Fu Caozheng, AiHua Zhu, Jianwei Yang and Chaochao Ma
The CL60 steel wheels of metro vehicles running on a specific line need frequent reprofiling due to rapid wear. Considering this problem, a new material for metro wheels was…
Abstract
Purpose
The CL60 steel wheels of metro vehicles running on a specific line need frequent reprofiling due to rapid wear. Considering this problem, a new material for metro wheels was designed. The friction and wear properties of the new material were studied, to reduce the wear rate and extend the service life of metro wheels.
Design/methodology/approach
Wheel specimens made of the two steel materials were tested using a GPM-60 wear tester under laboratory conditions. A field test was conducted on a specific metro line to track the wear in wheels made of the new material and CL60 steel wheels.
Findings
Under the laboratory conditions, the wear loss in the new material was 24.44% lower than that in CL60 steel. The field test revealed that compared to CL60 steel wheels, the new CL60 steel wheels showed a 19.42% decrease in tread wear on average. The field measurements for the wheels made of the new material are consistent with the results of laboratory simulation, suggesting relatively high wear resistance of the new material.
Practical implications
The results of the study can provide guidance on how to properly select steel material for metro wheels to avoid rapid wear and frequent reprofiling and reduce operating costs.
Originality/value
A new material for metro wheels was designed and developed by optimizing the content of Cr, Si, Mn, V and other elements. This material proved to have better wear resistance in both laboratory and field testing.
Details
Keywords
AiHua Zhu, Shang Yang, Jianwei Yang, Dongping Long and Xin Li
Metro wheels running on different lines can undergo wear at different positions. This paper aims to investigate the effects of wheel wear at two typical positions, i.e. wheel…
Abstract
Purpose
Metro wheels running on different lines can undergo wear at different positions. This paper aims to investigate the effects of wheel wear at two typical positions, i.e. wheel flange and tread, on the dynamic performance of metro vehicles and analyzes the differences, with an aim of providing theoretical support on wheel reprofiling for different metro lines.
Design/methodology/approach
Wheel profile data were measured on two actual metro lines, denoted A and B. It was observed that wheel wear on Lines A and B was concentrated on flanges and treads, respectively. A metro vehicle dynamics model was built using multibody dynamics software SIMPACK. Then it was applied to analyze the differences in effects of wheel wear at different positions on vehicle dynamic performance (VDP) for various speeds (50, 60 and 70 km/h) and line conditions (straight line, R1000m, R600m and R300m curves). Critical speed and vibration acceleration were used as indicators of VDP during linear motion (on straight track), while VDP during curvilinear motion (on curved track) was evaluated in terms of wheel/rail lateral force, wheel/rail vertical force, derailment coefficient and wheel unloading rate.
Findings
First, compared to wheel profile with tread wear, wheel profile with flange wear showed better performance during linear motion. When the distance traveled reached 8 × 104 and 14 × 104 km, the vehicle’s critical speed was 12.2 and 21.6% higher, respectively. The corresponding vertical and lateral vibration accelerations were 59.7 and 74.8% lower. Second, compared to wheel profile with flange wear, that with tread wear showed better performance during curvilinear motion, with smaller wheel/rail lateral force, derailment coefficient and wheel unloading rate. When the vehicle speed was 50, 60 and 70 km/h, the maximum difference in the three indicators between the two wheel profiles was 40.2, 44.7 and 23.1%, respectively. For R1000m, R600m and R300m curves, the corresponding maximum difference was 45.7, 69.0 and 44.4%, respectively.
Practical implications
The results of the study can provide a guidance and theoretical support on wheel reprofiling for different metro lines. On lines with large proportions of curved sections, metro vehicles are more prone to wheel flange wear and have poorer dynamic performance during curvilinear motion. Therefore, more attention should be paid to flange lubrication and maintenance for such lines. On lines with higher proportions of straight sections, metro vehicles are more prone to tread wear and have poorer performance on straight sections. So, tread maintenance and service requires more attention for such lines.
Originality/value
Existing research has focused primarily on the effects of wheel wear on VDP, but fails to consider the differences in the effects of wheel wear at different positions on VDP. In actual metro operation, the position of wheel wear can vary significantly between lines. Based on measured positions of wheel wear, this paper examines the differences in the effects of wheel wear at two typical positions, i.e. tread and flange, on VDP in detail.
Details
Keywords
AiHua Zhu, Si Yang, Qiang Li, JianWei Yang, Xi Li and YiDong Xie
The purpose of this paper is to study the wear evolution of metro wheels under the conditions of different track sequences, track composition and vehicle load and then to predict…
Abstract
Purpose
The purpose of this paper is to study the wear evolution of metro wheels under the conditions of different track sequences, track composition and vehicle load and then to predict wheel wear and to guide its maintenance.
Methodology
By using the SIMPACK and MATLAB software, numerical simulation analysis of metro wheel wear is carried out based on Hertz theory, the FASTSIM algorithm and the Archard model. First of all, the vehicle dynamics model is established to calculate the motion relationship and external forces of wheel-rail in the SIMPACK software. Then, the normal force of wheel-rail is solved based on Hertz theory, and the tangential force of wheel-rail is calculated based on the FASTSIM algorithm through the MATLAB software. Next, in the MATLAB software, the wheel wear is calculated based on the Archard model, and a new wheel profile is obtained. Finally, the new wheel profile is re-input into the vehicle system dynamics model in the SIMPACK software to carry out cyclic calculation of wear.
Findings
The results show that the setting order of different curves has an obvious influence on wear when the proportion of the straight track and the curve is fixed. With the increase in running mileage, the severe wear zone is shifted from tread to flange root under the condition of the sequence-type track, but the wheel wear distribution is basically stable for the unit-type track, and their wear growth rates become closer. In the tracks with different straight-curved ratio, the more proportion the curved tracks occupy, the closer the severe wear zone is shifted to flange root. At the same time, an increase in weight of the vehicle load will aggravate the wheel wear, but it will not change the distribution of wheel wear. Compared with the measured data of one city B type metro in China, the numerical simulation results of wheel wear are nearly the same with the measured data.
Practical implications
These results will be helpful for metro tracks planning and can predict the trend of wheel wear, which has significant importance for the vehicle to do the repair operation. At the same time, the security risks of the vehicle are decreased economically and effectively.
Originality/value
At present, many scholars have studied the influence of metro tracks on wheel wear, but mainly focused on a straight line or a certain radius curve and neglected the influence of track sequence and track composition. This study is the first to examine the influence of track sequence on metro wheel wear by comparing the sequence-type track and unit-type track. The results show that the track sequence has a great influence on the wear distribution. At the same time, the influence of track composition on wheel wear is studied by comparing different straight-curve ratio tracks; therefore, wheel wear can be predicted integrally under different track conditions.
Details
Keywords
AiHua Zhu, Caozheng Fu, JianWei Yang, Qiang Li, Jiao Zhang, Hongxiao Li and Kaiqi Zhang
This study aims to investigate the effect of time-varying passenger flow on the wheel wear of metro vehicles to provide a more accurate model for predicting wheel wear and a new…
Abstract
Purpose
This study aims to investigate the effect of time-varying passenger flow on the wheel wear of metro vehicles to provide a more accurate model for predicting wheel wear and a new idea for reducing wheel wear.
Design/methodology/approach
Sectional passage flow data were collected from an operational metro line. A wheel wear simulation based on time-varying passenger flow was performed via the SIMPACK software to obtain the worn wheel profile and wear distribution. The simulation involves the following models: vehicle system dynamics model, wheel-track rolling contact model, wheel wear model and variable load application model. Later, the simulation results were compared with those obtained under the traditional constant load condition and the measured wear data.
Findings
For different distances traveled by the metro vehicle, the simulated wheel profile and wear distribution under the variable load remained closer to the measurements than those obtained under the constant load. As the distance traveled increased, the depth and position of maximum wear and wear growth rate under the variable load tended to approach the corresponding measured values. In contrast, the simulation results under the constant load differed greatly from the measured values. This suggests that the model accuracy under the variable load was significantly improved and the simulation results can offer a more accurate basis for wear prediction.
Practical implications
These results will help to predict wheel wear more accurately and provide a new idea for simulating wheel wear of metro vehicles. At the same time, measures for reducing wheel wear were discussed from the perspective of passenger flow changes.
Originality/value
Existing research on the wheel wear of metro vehicles is mainly based on the constant load condition, which is quite different from the variable load condition where the passenger flow in real vehicles varies over time. A method of simulating wheel wear based on time-varying load is proposed in this paper. The proposed method shows a great improvement in simulation accuracy compared to traditional methods and can provide a more accurate basis for wear prediction and wheel repair.
Details
Keywords
Yihua Xiao, Huanghuang Dong, Haifei Zhan and Aihua Zhu
Metal plates are usually used as protective shields of engineering structures, which probably undergo multiple projectile impacts resulting from gunshot and blast. Though a large…
Abstract
Purpose
Metal plates are usually used as protective shields of engineering structures, which probably undergo multiple projectile impacts resulting from gunshot and blast. Though a large number of studies have been conducted on the performance of metal plates under a single projectile impact, few studies have explored their performance under multiple projectile impacts. This paper aims to explore the performance of Weldox 460 E steel plates against multiple projectile impacts through numerical simulation.
Design/methodology/approach
A three-dimensional coupled finite element (FE) and smoothed particle hydrodynamics (SPH) model was developed to simulate the perforation of a 12-mm-thick Weldox 460 E steel plate by an ogival projectile. The model was verified by existing experimental data. Then, it was extended to investigate the same target plate subjected to impacts with multiple projectiles. Simultaneous impacts with different number of projectiles, as well as sequential impacts with two projectiles, were considered.
Findings
Effects of spacing between projectiles on residual velocity of projectile, ballistic limit and failure mode of target were revealed for simultaneous impacts. Effects of spacing and axial distance between projectiles on residual velocity of projectile were explored for sequential impacts.
Originality/value
This work developed an advanced FE–SPH model to simulate perforation of steel plates by multiple projectiles, and revealed the effects of multiple impacts on ballistic performance of steel plates. It provides guidance for the design of protective structures/shields in various engineering applications.
Details
Keywords
Yakub Kayode Saheed, Usman Ahmad Baba and Mustafa Ayobami Raji
Purpose: This chapter aims to examine machine learning (ML) models for predicting credit card fraud (CCF).Need for the study: With the advance of technology, the world is…
Abstract
Purpose: This chapter aims to examine machine learning (ML) models for predicting credit card fraud (CCF).
Need for the study: With the advance of technology, the world is increasingly relying on credit cards rather than cash in daily life. This creates a slew of new opportunities for fraudulent individuals to abuse these cards. As of December 2020, global card losses reached $28.65billion, up 2.9% from $27.85 billion in 2018, according to the Nilson 2019 research. To safeguard the safety of credit card users, the credit card issuer should include a service that protects customers from potential risks. CCF has become a severe threat as internet buying has grown. To this goal, various studies in the field of automatic and real-time fraud detection are required. Due to their advantageous properties, the most recent ones employ a variety of ML algorithms and techniques to construct a well-fitting model to detect fraudulent transactions. When it comes to recognising credit card risk is huge and high-dimensional data, feature selection (FS) is critical for improving classification accuracy and fraud detection.
Methodology/design/approach: The objectives of this chapter are to construct a new model for credit card fraud detection (CCFD) based on principal component analysis (PCA) for FS and using supervised ML techniques such as K-nearest neighbour (KNN), ridge classifier, gradient boosting, quadratic discriminant analysis, AdaBoost, and random forest for classification of fraudulent and legitimate transactions. When compared to earlier experiments, the suggested approach demonstrates a high capacity for detecting fraudulent transactions. To be more precise, our model’s resilience is constructed by integrating the power of PCA for determining the most useful predictive features. The experimental analysis was performed on German credit card and Taiwan credit card data sets.
Findings: The experimental findings revealed that the KNN achieved an accuracy of 96.29%, recall of 100%, and precision of 96.29%, which is the best performing model on the German data set. While the ridge classifier was the best performing model on Taiwan Credit data with an accuracy of 81.75%, recall of 34.89, and precision of 66.61%.
Practical implications: The poor performance of the models on the Taiwan data revealed that it is an imbalanced credit card data set. The comparison of our proposed models with state-of-the-art credit card ML models showed that our results were competitive.
Details
Keywords
The impact of specific investments to performance has mixed arguments. This paper aims to clarify how and under what conditions specific investments made by manufacturer tailored…
Abstract
Purpose
The impact of specific investments to performance has mixed arguments. This paper aims to clarify how and under what conditions specific investments made by manufacturer tailored to supplier affect the new product development (NPD) performance of the manufacturer itself.
Design/methodology/approach
This study develops a moderated mediation model, testing the roles of supplier involvement and information technology (IT) implementation by regression and bootstrap analyses from 378 NPD projects.
Findings
The results show both physical and human specific investments positively affect NPD performance. IT implementation strengthens the mediated role of supplier involvement, i.e. the mediator role of supplier involvement between specific investments and NPD performance link is significantly weaker while IT implementation is lower.
Originality/value
The findings contribute to identify IT implementation and supplier involvement as two important constructs, together demonstrating how and when specific investments affect NPD performance.
Details
Keywords
Ning Liu, Linyu Zhou, LiPing Xu and Shuwei Xiang
As the cost of completing a transaction, the green merger and acquisition (M&A) premium paid on mergers can influence whether the acquisition creates value or not. However…
Abstract
Purpose
As the cost of completing a transaction, the green merger and acquisition (M&A) premium paid on mergers can influence whether the acquisition creates value or not. However, studies linking M&A premiums to firm value have had mixed results, even fewer studies have examined the effect of green M&A premiums on bidders’ firm value. The purpose of this paper is to investigate whether and how green M&A premiums affect firm value in the context of China’s heavy polluters.
Design/methodology/approach
Using 323 deals between 2008 and 2019 among China’s heavy polluters, this paper estimates with correlation analysis and multiple regression analysis.
Findings
Green M&A premiums are negatively associated with firm value. The results are more significant when firms adopt symbolic rather than substantive corporate social responsibility (CSR) strategies. Robustness and endogeneity tests corroborate the findings. The negative relation is stronger when acquiring firms have low governmental subsidy and environmental regulation, when firms have overconfident management, when firms are state-owned and when green M&A occurs locally or among provinces in the same region. This study also analyzes agency cost as an intermediary in the relationship between green M&A premium and firm value, which lends support to the agency-view hypothesis.
Originality/value
This study provides systemic evidence that green M&A premiums damage firm value through agency cost channel and the choice of CSR strategies from the perspective of acquirers. These findings enrich the literature on both the economic consequences of green M&A premiums and the determinants of firm value and provide a plausible explanation for mixed findings on the relationship between green M&A premiums and firm value.