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The purpose of this study is to investigate the characteristic and function of oxide film formed on grinding wheel in electrolytic in-process dressing (ELID) precision grinding and improve the quality of ELID grinding.

Dynamic film forming experiments were carried out with a simulation device close to the actual processing conditions. Then, the ELID grinding experiments of bearing rings were performed using grinding wheels with good film forming effect. The experiment was designed by quadratic regression general rotation combination method. The influence of grinding depth, electrolytic voltage, duty cycle and grinding wheel linear speed on grinding effect is analyzed.

A mathematical model for the formation rate of oxide film was established. The experiments show that the composition of grinding wheel and grinding fluid, as well as the electrical parameters, influence the film forming effect. Thus, the oxide film plays an important role in ELID grinding.

This study provides a reference for the design and selection of grinding wheel and grinding fluid and the setting of process parameters in ELID grinding.

The low-temperature sintering of silica glass combined with additive manufacturing (AM) technology has brought a revolutionary change in glass manufacturing. This study aims to carry out in an attempt to achieve precious manufacturing of silicate glassy matrix through the method of slurry extrusion.

A low-cost slurry extrusion modelling technology is used to extrude silicate glassy matrix inks, composed of silicate glass powder with different amounts of additives. Extrudability of the inks, their printability window and the featuring curves of silicate glassy matrix are investigated. In addition, the properties of the low-temperature sintering green part as a functional part are explored and evaluated from morphology, hardness and colour.

The results showed that the particle size was mainly distributed from 1.4 µm to 5.3 µm, showing better slurry stability and print continuity. The parameters were set to 8 mm/s, 80% and 0.4 mm, respectively, to achieve better forming of three-dimensional (3D) samples. Besides, the organic binder removal step was concentrated on 200°C–300°C and 590°C–650°C was the fusion bonding temperature of the powder. The hardness values of 10 test samples ranged from 588 HL to 613 HL, which met the requirements of hard stones with super-strong mechanical strength. In addition, the mutual penetration of elements caused by temperature changes may lead to a colourful appearance.

The custom continuous AM technology enables the fabrication of a glass matrix with 3D structural features. The precise positioning technology of the glass matrix is expected to be applied more widely in functional parts.

Traditional simulation research of geological and similar engineering models, such as landslides or other natural disaster scenarios, usually focuses on the change of stress and the state of the model before and after destruction. However, the transition of the inner change is usually invisible. To optimize and make models more intelligent, this paper aims to propose a perceptible design to detect the internal temperature change transformed by other energy versions like stress or torsion.

In this paper, micron diamond particles were embedded in 3D printed geopolymers as a potential thermal sensor material to detect the inner heat change. The authors use synthetic micron diamond powder to reinforced the anti-corrosion properties and thermal conductivity of geopolymer and apply this novel geopolymer slurry in the direct ink writing (DIW) technique.

As a result, the addition of micron diamond powder can greatly influence the rheology of geopolymer slurry and make the geopolymer slurry extrudable and suitable for DIW by reducing the slope of the viscosity of this inorganic colloid. The heat transfer coefficient of the micron diamond (15 Wt.%)/geopolymer was 50% higher than the pure geopolymer, which could be detected by the infrared thermal imager. Besides, the addition of diamond particles also increased the porous rates of geopolymer.

In conclusion, DIW slurry deposition of micron diamond-embedded geopolymer (MDG) composites could be used to manufacture the multi-functional geological model for thermal imaging and defect detection, which need the characteristic of lightweight, isolation, heat transfer and wave absorption.

The study aims to explore the composition and microstructure of clay functionally graded materials under the process of double-gradient direct ink writing (DIW).

The investigation focused specifically on the pore characteristics of barite-kaolin clay composite after three-dimensional (3D) printing and sintering as well as its bionic application in geophysical model.

The model with pore and material variations brought about spatial and nonlinear mechanical properties. Moreover, the vertical gradient and connected pores in the upper kaolin part simulated the natural phenomenon of the landslide model (take Chinese Majiagou landslides as an example). Both the thermal debinding behavior and the kaolin powder particles characteristics [large pore volume (0.019 cm³g^–1) and pore size (29.20 nm)] were attributed to the interconnection channels.

Hence, the macroscopic and microscopic pores achieved by dual-gradient DIW process make it possible to control the permeability and details of properties, precisely in the geological model.

The purpose of this paper is to investigate the effects of surface texture with roughness orientation considered on tribological properties under a mixed lubrication state numerically and experimentally.

Based on the average Reynolds equation and asperity contact model, the impacts of surface texture parameters and roughness orientation on lubrication properties have been calculated using finite difference method. Tin–bronze samples with various prescribed surface texture geometric parameters and roughness orientation were fabricated by laser surface texturing technique, and the tribology performance of the textured surface was studied experimentally.

The effects of surface geometric parameters and roughness orientation parameters have been discerned. The experimental observations are in good agreement with the numerical prediction, which suggests that the numerical scheme adopted in this work is suitable in capturing the surface texture and roughness effect under mixed lubrication state.

By meticulously controlling the surface roughness and surface texture geometric characteristics based on the laser surface texturing process, samples with prescribed surface texture parameters and roughness orientation consistent with that in theoretical studies were fabricated and the theoretical model and results were verified experimentally.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

Aero-engine components endure combined high and low cycle fatigue (CCF) loading during service, which has attracted more research attention in recent years. This study aims to construct a new framework for the prediction of probabilistic fatigue life and reliability evaluation of an aero-engine turbine shaft under CCF loading if considering the material uncertainty.

To study the CCF failure of the aero-engine turbine shaft, a CCF test is carried out. An improved damage accumulation model is first introduced to predict the CCF life and present high prediction accuracy in the CCF loading situation based on the test. Then, the probabilistic fatigue life of the turbine shaft is predicted based on the finite element analysis and Monte Carlo analysis, where the material uncertainty is taken into account. At last, the reliability evaluation of the turbine shaft is conducted by stress-strength interference models based on an improved damage accumulation model.

The results indicate that predictions agree well with the tested data. The improved damage accumulation model can accurately predict the CCF life because of interaction damage between low cycle fatigue loading and high cycle fatigue loading. As a result, a framework is available for accurate probabilistic fatigue life prediction and reliability evaluation.

The proposed framework and the presented testing in this study show high efficiency on probabilistic CCF fatigue life prediction and can provide technical support for fatigue optimization of the turbine shaft.

The novelty of this work is that CCF loading and material uncertainty are considered in probabilistic fatigue life prediction.

For ball screw feed system, a sudden start or stop has a great influence on the transmission stiffness, so the axial stiffness mutation of feed system will occur. The purpose of this paper is to study the influence of acceleration on the transmission stiffness and dynamic characteristics of the ball screw feed system.

Taking the ball screw feed system as a research object, on the basis of the Hertz contact theory and the mixed element method, axial stiffness model and dynamic model are established. And the system stability was analyzed by the time history diagram and Phase-plane portrait diagram. The feed system was analyzed theoretically and experimentally, the experimental results are in good agreement with the model results.

Lead screw lead angle, preload, load and start acceleration affected ball-screw pair, bearing and transmission stiffness. And the load, nut contact stiffness, bearing contact stiffness, preload have a large effect on the transmission stiffness. The results show that a certain acceleration value will make the axial stiffness abrupt change.

This research provides a useful theoretical support for ensuring a good dynamic for the ball screw feed system.

The purpose of this paper is to explore the changes of the scale of urban tourists in mainland China under the impact of COVID-19 and, specifically, the following questions: how did the scale of domestic tourists change nationwide and in the seven geographic regions? What are the differences in the changes among the seven geographic regions? What are the changes in the hot spot areas and spatial clustering of domestic tourists across the country?

Using the data of domestic tourist arrivals in 337 cities in mainland China from 2018 to 2021, this research analyzes the absolute differences and relative differences in the scale of domestic tourists nationwide and in seven geographic divisions with the help of indicators such as range analysis, standard deviation, coefficient of variation and Herfindahl–Hirschman Index and explores the changes in the hot spot areas and spatial concentration degree of the spatial scale of domestic tourists nationwide under the influence of the epidemic using kernel density analysis and spatial auto-correlation analysis.

The absolute differences in all seven geographical divisions continue to increase during 2018–2021. The domestic tourism in southwest China is extremely uneven. Absolute differences in the northwest and northeast regions are relatively small, and the development in attracting domestic tourists is more balanced. Relative differences in southwest China are comparatively large, with the trend of uneven development being obvious. The northeast, northwest and eastern regions of China are small, and the development is more balanced. The popularity of domestic tourism in the Beijing–Tianjin–Hebei region, as well as the Yangtze River Delta region, continues to decline and then pick up in 2021. The inland southwest region became a new domestic tourism hot spot in 2021. The size of domestic tourists from 2018 to 2021 in mainland China cities shows a significant positive spatial correlation, and there is a spatial agglomeration phenomenon, but some regional agglomeration types change from 2018 to 2021.

The impact of the epidemic on the number and spatial scale of domestic tourism in China has been clarified, which makes up for the comparison of domestic tourism changes before and after the epidemic. A clear understanding of the changes in the number and spatial scale of domestic tourists in different regions after the epidemic is conducive to the development of domestic tourism revitalization strategies in accordance with the actual situation of each province and promotes the internal circulation of Chinese tourism.

This paper tries to clarify the quantitative scale of domestic tourism in different regions after the epidemic, which is conducive to the development of domestic tourism revitalization strategies in cities in different regions according to regional characteristics and the actual situation of each province and to promote the healthy operation of the internal circulation of tourism in China. This paper also tries to show the changes of domestic tourism market hot spots, agglomeration conditions changes before and after the outbreak and the clarity of tourists’ preference space changes.

Scale of domestic tourists; Absolute difference; Relative difference; Spatial hot spot distribution; Spatial agglomeration change

本文旨在探寻疫情影响下中国大陆城市游客规模演化规律, 具体而言, 疫情影响下, 全国及七大地理分区的国内游客量规模变化如何？七大地理地区的变化有何差异？以及疫情影响下, 全国国内游客空间规模的热点区域和空间集聚程度有何变化？

利用2018-2021年中国大陆337各城市的国内游客量数据, 借助极差、标准差、变异系数、赫芬达尔指等指标分析全国及七大地理分区国内游客规模的绝对差异和相对差异; 借助核密度分析、空间自相关分析等ArcGIS分析工具, 探寻疫情影响下全国国内游客空间规模的热点区域和空间集聚程度的变化情况。

①绝对差异方面, 七大地理分区的绝对差异均持续增大。西南地区的游客量的绝对差异巨大, 国内游发展极不均衡。西北地区、东北地区绝对差异相对较小, 在吸引国内游客方面发展较为均衡。②相对差异方面, 西南地区的国内游发展相对差异较大, 发展不均衡趋势明显; 东北地区、西北地区、华东地区的国内游发展相对差异较小, 发展较为均衡。③热点区域变化方面, 京津冀地区、长三角地区的国内旅游热度持续下降, 在2021年有所回升; 内陆西南地区在2021年成为新的国内游热点区域。④2018年至2021年城市国内游客量规模均呈现出显著的空间正相关的关系, 存在着空间集聚现象, 但部分区域集聚类型在2018到2021年间发生变化。

①理论意义：明晰了疫情对中国国内旅游人次的数量规模和空间规模的影响, 弥补了当前疫情前后国内旅游业变化对比的研究; 阐明了疫情前后中国城市国内游客空间格局的变化, 拓展了研究情景, 丰富了中国旅游业时空变化的相关研究。②实践意义：明晰了疫后不同地区国内旅游人次的数量规模和空间规模变化情况, 以及国内旅游市场热点变化和游客空间偏好变化, 有利于各地区城市对症下药, 制定符合各省份实际情况的国内旅游业振兴策略, 促进中国旅游业内循环。

In this paper, the C80 special coal gondola car was taken as the subject, and the load test data of the car body at the center plate, side bearing and coupler measured on the dedicated line were broken down to generate the random load component spectrums of the car body under five working conditions, namely expansion, bouncing, rolling, torsion and pitching according to the typical motion attitude of the car body.

On the basis of processing the measured load data, the random load component spectrums were equivalently converted into sinusoidal load component spectrums for bench test based on the principle of pseudo-damage equivalence of load. Relying on the fatigue and vibration test bench of the whole railway wagon, by taking each sinusoidal load component spectrum as the simulation target, the time waveform replication (TWR) iteration technology was adopted to create the drive signal of each loading actuator required for the fatigue test of car body on the bench, and the drive signal was corrected based on the equivalence principle of measured stress fatigue damage to obtain the fatigue test loads of car body under various typical working conditions.

The fatigue test results on the test bench were substantially close to the measured test results on the line. According to the results, the relative error between the fatigue damage of the car body on the test bench and the measured damage on the line was within the range of −16.03%–27.14%.

The bench test results basically reproduced the fatigue damage of the key parts of the car body on the line.