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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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This study aims to understand how different levels of streamer channels influence luxury brand sales in live streaming commerce. This study also seeks to understand the conditions under which luxury brands may benefit more from different level streamer channels.

Panel data were collected from 17 international luxury brands on the Douyin live streaming platform in an 18 week period from August to December 2020 and analyzed by using a two-way fixed effects model.

The authors compared different mega-, macro- and micro-streamer channels within live streaming commerce and found that the densities of mega- and macro-streamer channels had significant positive impacts on luxury brand sales in live streaming commerce. Moreover, the effects of the density of streamer channel on luxury brand sales were moderated by such variables as product line breadth, product line depth, product type (star/non-star) and product price (high/low). The authors found that product line breadth and depth could reduce the positive impact of the densities of mega- and macro-streamer channels on luxury brand sales. For star products and high-priced products, the relationship between the density of mega-streamer channel and luxury brand sales was more likely to be observed than for non-star products and low-priced products. The relationship between the density of macro-streamer channel and luxury brand sales was more likely to be observed in low-priced products than in high-priced products.

The findings make important contributions to the literature in that the authors expand the influencer-brand fit theory by proposing a new model of effects of the densities of mega-, macro- and micro-streamer channels on sales performance across different luxury products to improve our understanding of the fit among influencers, brands and products. This helps luxury brands make basic decisions of “who sells” and “sells what” when engaging in live streaming commerce.

In the daily energy dispatch process in a power system, accurate short-term electricity load forecasting is a very important tool used by spot market players. It is a critical requirement for optimal generator unit commitment, economic dispatch, system security and stability assessment, contingency and ancillary services management, reserve setting, demand side management, system maintenance and financial planning in power systems. The purpose of this study is to present an improved grey Verhulst electricity load forecasting model.

To test the effectiveness of the proposed model for short-term load forecast, studies made use of Kenya’s load demand data for the period from January 2014 to June 2019.

The convectional grey Verhulst forecasting model yielded a mean absolute percentage error of 7.82 per cent, whereas the improved model yielded much better results with an error of 2.96 per cent.

In the daily energy dispatch process in a power system, accurate short-term load forecasting is a very important tool used by spot market players. It is a critical ingredient for optimal generator unit commitment, economic dispatch, system security and stability assessment, contingency and ancillary services management, reserve setting, demand side management, system maintenance and financial planning in power systems. The fact that the model uses actual Kenya’s utility data confirms its usefulness in the practical world for both economic planning and policy matters.

In terms of generation and transmission investments, proper load forecasting will enable utilities to make economically viable decisions. It forms a critical cog of the strategic plans for power utilities and other market players to avoid a situation of heavy stranded investment that adversely impact the final electricity prices and the other extreme scenario of expensive power shortages.

This research combined the use of natural logarithm and the exponential weighted moving average to improve the forecast accuracy of the grey Verhulst forecasting model.

Detecting the orientation of cracks is a major challenge in the development of eddy current nondestructive testing probes. Eddy current-based techniques are limited in their ability to detect cracks that are not perpendicular to induced current flows. This study aims to investigate the application of the rotating electromagnetic field method to detect arbitrary orientation defects in conductive nonferrous parts. This method significantly improves the detection of cracks of any orientation.

A new rotating uniform eddy current (RUEC) probe is presented. Two exciting pairs consisting of similar square-shaped coils are arranged orthogonally at the same lifting point, thus avoiding further adjustment of the excitation system to generate a rotating electromagnetic field, eliminating any need for mechanical rotation and focusing this field with high density. A circular detection coil serving as a receiver is mounted in the middle of the excitation system.

A simulation model of the rotating electromagnetic field system is performed to determine the rules and characteristics of the electromagnetic signal distribution in the defect area. Referring to the experimental results aimed to detect artificial cracks at arbitrary angles in underwater structures using the rotating alternating current field measurement (RACFM) system in Li et al. (2016), the model proposed in this paper is validated.

CEDRAT FLUX 3D simulation results showed that the proposed probe can detect cracks with any orientation, maintaining the same sensitivity, which demonstrates its effectiveness. Furthermore, the proposed RUEC probe, associated with the exploitation procedure, allows us to provide a full characterization of the crack, namely, its length, depth and orientation in a one-pass scan, by analyzing the magnetic induction signal.