Search results

The purpose of this paper is to analyze the variation of temperature field, pressure field and deformation of hydrostatic thrust bearing under different working conditions, so as to provide a theoretical basis for improving accuracy and reliability.

In this study, the double rectangular hydrostatic bearing of type Q1-224 was selected as the research object, and the simulation was carried out according to different working conditions, and the obtained data were summarized regularly.

It is found that the overall temperature of hydrostatic bearing increases with the increase of speed and load, and the increase in load will result in a larger pressure distribution which first increases and then decreases with the speed. The deformation trend of the deformation field is found, and it is found that the force deformation is larger than the thermal deformation at low rotational speed, and the thermal deformation is larger than the force deformation at high rotational speed.

In this study, the fluid-structure coupling method of conjugate heat transfer is applied to study the whole hydrostatic bearing. Most of the previous studies only studied the oil film and considered the influence of the convective heat transfer between the hydrostatic bearing and the air in heat transfer, which is rarely seen in the previous research literature.

The purpose of this paper is to investigate relationships of urban seismic resilience assessment indicators.

To achieve this aim, construction of the urban seismic resilience assessment indicators system was conducted and 20 indicators covering five dimensions, namely building and lifeline infrastructure, environment, society, economy and institution were identified. Following this, this study used evidence fusion theory and intuitionistic fuzzy sets to process the information from experts then developed the fuzzy total interpretive structure model.

A total of 20 urban seismic resilience assessment indicators are reconstructed into a hierarchical and visual system structure including five levels. Indicators in the bottom level including debris flow risk, landslide risk, earthquake experience and demographic characteristics are fundamental indicators that significantly impact other indicators. Indicators in the top level including open space, gas system and public security are direct indicators influenced more by other indicators. Other indicators are in middle levels. Results of MICMAC analysis visually categorize these indicators into independent indicators, linkage indicators, autonomous indicators and dependent indicators according to driving power and dependence.

This paper attempts to explore relationships of urban seismic resilience assessment indicators with the interpretive structural model method. Additionally, Fuzzy total interpretive structure model is developed combined with evidence fusion theory and intuitionistic fuzzy sets, which is the extension of total interpretive structure model. Research results can assist the analytic network process method in assessing urban seismic resilience in future research.

Massively multiplayer online role-playing games (MMORPGs) create quasi-real social systems in which players can interact with one another, and quasi-real economic systems where players can consume and trade in-game items with virtual currency. The in-game currency price, an important indicator of a virtual economy, is highly contingent on players’ behavioral interaction in MMORPGs. The purpose of this paper is to adopt a network perspective to examine how topological characteristics of social networks in an MMORPG, namely, network externalities, density, and closure, would exert impacts on the in-game currency price.

Players’ behavioral data were collected from a popular MMORPG in China on a weekly basis for 52 weeks. With a time series analytical approach, the empirical model for the price function of in-game currency was estimated with vector autoregression.

The results show that the number of core avatars and network density are positively associated with in-game currency price, while network closure has a negative effect on in-game currency price. However, in-game currency price is found to have no significant relationship with the trade volume of the currency.

This study fills in an important research gap by investigating factors influencing the in-game currency price of MMORPGs from a network perspective, which contributes to the existing literature of network effects and advances our understanding about how players’ interaction will influence the dynamics of a virtual economy. The findings could offer useful insights for online game companies to better understand their players’ social interaction and consumption behavior.

Young construction project management practitioners (CPMPs) have unique, complex, and notable occupational mental health problems. However, there were few studies about the intervention for occupational mental health of CPMPs, and traditional intervention modes often failed to achieve significant effects. Therefore, this study aims to propose a new and effective intervention method.

Job crafting intervention was used to design an intervention experiment. A total of 72 CPMPs participated in a 10-week randomized controlled trial in China. Descriptive statistics and repeated measures analysis of variance were used to verify the effectiveness of job crafting intervention (JCI) on job crafting behaviors, job burnout, and work engagement with consideration of the impact of time.

Results showed that the intervention increased social resources, thus effectively reducing job burnout and promoting work engagement. Time also had a significant impact on cynicism, dedication, and social resources.

The authors should promote the habit of job crafting in CPMPs. Furthermore, in order to facilitate their job crafting, the authors should increase structural and social resources for them, and the authors can also encourage them to undertake challenging demands to increase their self-efficacy and the sense of achievement.

The authors bring into light a new psychological intervention approach among CPMPs, which integrates the advantages of the guidance in traditional organized intervention methods and the proactivity in individual spontaneous job crafting. The authors verify the efficacy of the JCI among CPMPs and help propose countermeasures and suggestions to improve the occupational mental health of CPMPs.

Besides ensuring traditional project objectives, expatriate construction professionals (EXCPs) working on international projects face challenges adapting to unfamiliar environments with varying construction standards, work practices and cultural values. This puts them at a high risk of job burnout. Thus, this study aims to investigate the antecedents and outcomes of EXCPs' job burnout in the international construction industry.

Based on the Job demands-resource model (JD-R), a theoretical framework was developed. Industry-specific stressors and expatriate management practices were identified using a literature review and interviews. The authors then used a questionnaire survey to collect data from Chinese EXCPs. Exploratory factor analysis, confirmatory factor analysis and structural equation modeling were then utilized to test hypotheses.

The findings indicate that early-career EXCPs experience the most severe levels of job burnout. The paths analysis proved the direct and indirect mitigating effects of expatriate management practices on job burnout, and EXCP's job burnout was associated with poor job performance and decreased intention to stay in the international assignment.

While prior research has explored job burnout among construction professionals working on domestic projects, little attention has been given to EXCPs and their unique challenges. This study aims to fill this critical gap in the literature by offering a unique perspective on the antecedents and outcomes of job burnout among EXCPs in international contexts and presents a significant contribution to understanding and addressing occupational health issues faced by EXCPs.

The purpose of this paper is to handle the problem of the radial disturbance caused by rotor mass unbalance and load change in a bearingless induction motor (BIM).

The active disturbance rejection controller (ADRC) is used to replace the traditional PI controller, and a cubic interpolation method is used to fit the nonlinear function of ADRC, so as to improve the control performance. Meanwhile, a disturbance observer is applied to the suspension system, and the observed disturbance acceleration is compensated to the suspension system in the form of current; thus, the suppression of the rotor radial disturbance is realized.

The proposed method can effectively suppress the radial disturbance of the rotor, meliorate the suspension performance of the motor and enhance the anti-interference ability of the system. Besides, it has excellent dynamic and static performance.

A radial disturbance control strategy of the BIM based on improved ADRC is proposed is to suppress the radial disturbance of the rotor. The improved ADRC is to enhance the control performance of the system, and the disturbance observer is designed to observe and compensate the disturbance.

The purpose of the control method proposed in this paper is to address the problem of the poor anti-interference of the suspension winding current in the traditional bearingless induction motor (BL-IM) direct suspension force control process.

A model predictive direct suspension force control of a BL-IM based on sliding mode observer is proposed in this paper. The model predictive control (MPC) is introduced to the traditional direct suspension force control to improve the anti-interference of the suspension current. A sliding mode flux linkage observer is designed and applied to the MPC system, which reduces the error of the parameter observation and improves the robustness of the system. The strategy is designed and implemented in the MATLAB/Simulink and the two-level AC speed regulation platform.

The simulation and experimental results show that the performance of the BL-IM under the control method proposed in this paper is better than that under the traditional direct suspension force control, and the suspension performance of the motor and the anti-interference of the control system are improved.

This study helps to improve the suspension performance of the motor and the anti-interference of the control system.

The floating ring generates elastic deformation as the film pressure for high-speed floating ring bearings (FRBs). The purpose of this study is to investigate the influence of ring elastic deformation on the performance of a hydrodynamic/hydrostatic FRB, including floating ring equilibrium and minimum film thickness.

The finite element method and finite difference method are used to solve thermohydrodynamic (THD) lubrication models, including the Reynolds equation, energy equation and temperature–viscosity equation. The deformation matrix method is applied to solve the elastic deformation equation, and then the deformation distribution, floating ring equilibrium and minimum film thickness are investigated. The maximum pressure is compared with the published article to verify the mathematical models.

The deformation value increases with the growth of shaft speed; owing to elastic deformation on the film reaction force and friction moment, the ring achieves equilibrium at a new position, and the inner eccentricity increases while the ring-shaft speed ratio declines. The minimum film thickness declines with the growth of inlet temperature, and the outer film tends to rupture considering elastic deformation at a higher temperature.

The floating ring elastic deformation is coupled with the THD lubrication equations to study ring deformation on the hydrodynamic/hydrostatic FRB lubrication mechanism. The elastic deformation of floating ring should be considered to improve analysis accuracy for FRBs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0139/

This paper aims to propose a deep learning model that can be used to expand the number of samples. In the process of manufacturing and assembling electronic components on the printed circuit board in the surface mount technology production line, it is relatively easy to collect non-defective samples, but it is difficult to collect defective samples within a certain period of time. Therefore, the number of non-defective components is much greater than the number of defective components. In the process of training the defect detection method of electronic components based on deep learning, a large number of defective and non-defective samples need to be input at the same time.

To obtain enough electronic components samples required for training, a method based on the generative adversarial network (GAN) to generate training samples is proposed, and then the generated samples and real samples are used to train the convolutional neural networks (CNN) together to obtain the best detection results.

The experimental results show that the defect recognition method using GAN and CNN can not only expand the sample images of the electronic components required for the training model but also accurately classify the defect types.

To solve the problem of unbalanced sample types in component inspection, a GAN-based method is proposed to generate different types of training component samples and then the generated samples and real samples are used to train the CNN together to obtain the best detection results.

The purpose of this paper is to compare the combustion characteristics, including the combustion pressure, heat release rate (HRR), coefficient of variation (COV) of indicated mean effective pressure (IMEP), flame development period and combustion duration, of aviation kerosene fuel, namely, rocket propellant 3 (RP-3), and gasoline on a two-stoke spark ignition engine.

This paper is an experimental investigation using a bench test to reflect the combustion performance of two-stroke spark ignition unmanned aerial vehicle (UAV) engine on gasoline and RP-3 fuel.

Under low load conditions, the combustion performance and HRR of burning RP-3 fuel were shown to be worse than those of gasoline. Under high load conditions, the average IMEP and the COV of IMEP of burning RP-3 fuel were close to those of gasoline. The difference in the flame development period between gasoline and RP-3 fuel was similar.

Gasoline fuel has a low flash point, high-saturated vapour pressure and relatively high volatility and is a potential hazard near a naked flame at room temperature, which can create significant security risks for its storage, transport and use. Adopting a low volatility single RP-3 fuel of covering all vehicles and equipment to minimize the number of different devices with the use of a various fuels and improve the application safeties.

Most two-stroke spark ignition UAV engines continue to combust gasoline. A kerosene-based fuel operation can be applied to achieve a single-fuel policy.