Search results

The purpose of this paper is to investigate the effects of different surface structures, dimensional parameters and cavitation models on the lubrication characteristics of water-lubricated journal bearings.

In this paper, the coupling iteration method of ANSYS and MATLAB is established to calculate the journal orbits of water-lubricated bearing, and the differences between the journal orbits of the smoothed and the textured water-lubricated bearings are compared and analyzed, and the effects of different bearing materials, L/D ratios and clearance ratios on the lubrication performance of water-lubricated bearings are investigated. The effects of different cavitation models on the static equilibrium position and whirling trajectory of water-lubricated bearings are compared.

The results show that when the surface texture is distributed in the upper bearing or the bearing elastic modulus decreases, the bearing stability increases. Considering shear cavitation and noncondensing gas, the rotor journal orbits amplitude decreases at high speed with low clearance ratio. A water film test rig for water-lubricated bearings is built to measure the full-circle water film pressure of water-lubricated journal bearings, and the experimental results are compared with the simulation results, which are in good agreement.

The findings provide a theoretical basis for optimizing the structure of water-lubricated bearings.

As the global emphasis on environmental consciousness intensifies, many corporations claim to be environmentally responsible. However, some merely partake in “greenwashing” – a facade of eco-responsibility. Such deceptive behavior is especially prevalent in Chinese heavy-pollution industries. To counter these deceptive practices, this study aims to use machine learning (ML) techniques to develop predictive models against corporate greenwashing, thus facilitating the sustainable development of corporations.

This study develops effective predictive models for greenwashing by integrating multifaceted data sets, which include corporate external, organizational and managerial characteristics, and using a range of ML algorithms, namely, linear regression, random forest, K-nearest neighbors, support vector machines and artificial neural network.

The proposed predictive models register an improvement of over 20% in prediction accuracy compared to the benchmark value, furnishing stakeholders with a robust tool to challenge corporate greenwashing behaviors. Further analysis of feature importance, industry-specific predictions and real-world validation enhances the model’s interpretability and its practical applications across different domains.

This research introduces an innovative ML-based model designed to predict greenwashing activities within Chinese heavy-pollution sectors. It holds potential for application in other emerging economies, serving as a practical tool for both academics and practitioners.

The findings offer insights for crafting informed, data-driven policies to curb greenwashing and promote corporate responsibility, transparency and sustainable development.

While prior research mainly concentrated on the factors influencing greenwashing behavior, this study takes a proactive approach. It aims to forecast the extent of corporate greenwashing by using a range of multi-dimensional variables, thus providing enhanced value to stakeholders. To the best of the authors’ knowledge, this is the first study introducing ML-based models designed to predict a company’s level of greenwashing.

Stakeholder interests are complex, sensitive and highly uncertain and may influence the development of net zero carbon building (NZCB). However, this study aims to conduct a systematic literature review to explore the stakeholder interests towards achieving NZCB.

A total of 62 articles were identified from the Scopus database and thoroughly reviewed to extract relevant information on stakeholders' interest towards achieving NZCB.

A total of 28 stakeholder interests influencing the development of NZCB were identified from the literature and were classified into six major groups according to their uniqueness (economic, social, environmental, technological, political, regulatory and legal).

The findings of this study provide insight into the specific stakeholder interests towards achieving NZCB. Thus, the findings of this study could serve as a guide for future research, policy formulation and implementation to expedite the practice of building towards net zero carbon (NZC). Empirical studies are suggested in future studies to test and consolidate the theoretical claims of this study.

This paper undertakes a comprehensive systematic review of studies on stakeholder interests towards achieving NZCB, which is the least investigated in the literature.

Given the current friction and wear challenges faced by automobile parts and bearings, this study aims to identify a novel texture for creating anti-friction and wear-resistant surfaces. This includes detailing the preparation process with the objective of mitigating friction and wear in working conditions.

Femtosecond laser technology was used to create a mango-shaped texture on the surface of GCr15 bearing steel. The optimized processing technology of the texture surface was obtained through adjusting the laser scanning speed. The tribological behavior of the laser-textured surface was investigated using a reciprocating tribometer.

The friction coefficient of the mango-shaped texture surface is 25% lower than that of the conventional surface, this can be attributed to the reduced contact area between the friction ball and the micro-textured surface, leading to stress concentration at the extrusion edge and a larger stress distribution area on the contact part of the ball and disk compared to the conventional surface and the function of the micro-texture in storing wear chips during the sliding process, thereby reducing secondary wear.

The mango-shaped textured surface in this study demonstrates effective solutions for some of the friction and wear issues, offering significant benefits for equipment operation under light load conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0127/

Prefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.

This study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.

Results show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.

This study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.

The world is reeling from the effects of climate change with increased extreme precipitation. Flooding is amongst the most recurring and devastating natural hazards, impacting human lives and causing severe economic damage. This paper aims to conduct a systematic review to critically analyse the most reported and emerging flood disaster resilience indicators.

A total of 35 papers were selected through a systematic process using both Web of Science and Scopus databases. The selected literature was subjected to a thorough thematic content analysis.

From the review, 77 emerging flood disaster resilience assessment indicators were identified. Furthermore, based on the individual meanings and relationships of the derived indicators, they were further categorized into six groups, namely, physical, institutional, social, psychological, ecology and economic. More also, it was identified that most of the selected publications have used objective resilience measurement approaches as opposed to subjective resilience measurement approaches.

The generated list of flood disaster resilience indicators will provide insights into the capacities which can be improved to enhance the overall resilience to flood disasters in communities.

This study aims to examine the performance implications of blockchain implementation in the supply chain and explore how blockchain functions and supply chain processes of blockchain implementation moderate the effect on firm performance.

Using 220 blockchain implementations announced between January 2015 and December 2022, we use the event study methodology to estimate the effects of blockchain implementation on the firm value. Regression analyses are conducted to examine the moderating effects of blockchain functions and supply chain processes.

First, there is a positive and statistically significant relationship between blockchain implementation in the supply chain and firm value. Second, we find that abnormal returns from blockchain implementation are higher when used with blockchain’s contract automation function and applied in downstream processes, supporting the moderation effects.

The study provides empirical evidence on the effects of the blockchain implementation on firm performance, taking into account the complexity of blockchain functions and supply chain processes. It enriches the current understanding of how blockchain implementation in the supply chain contributes to firm value.

This paper takes the manufacturing cluster supply chain as the research object and explores the evaluation and enhancement strategy of manufacturing cluster supply chain synergy. The purpose of this study was to (1) analyze the mechanism of manufacturing cluster supply chain synergy; (2) construct manufacturing cluster supply chain synergy evaluation model; (3) algorithm realization of manufacturing cluster supply chain synergy evaluation and (4) propose manufacturing cluster-based supply chain synergy enhancement strategy.

Breaking through the limitations of traditional manufacturing cluster supply chain synergy evaluation, we take horizontal synergy and vertical synergy as coupled synergy subsystems, use the complex system synergy model to explore the horizontal synergy between core enterprises and cluster enterprises and the vertical synergy of supply chain enterprises and use the coupling coordination model to construct the coupled synergy evaluation model of manufacturing cluster supply chain, which is an innovation of the evaluation perspective of previous cluster supply chain synergy and also an enrichment and supplementation of the evaluation methodology. This is not only the innovation of the evaluation perspective but also the enrichment and supplementation of the evaluation method.

Using Python software to conduct empirical analysis on the evaluation model, the research shows that the horizontal and vertical synergies of the manufacturing cluster supply chain interact with each other and jointly affect the coupling synergy. On this basis, targeted strategies are proposed to enhance the synergy of the manufacturing cluster supply chain.

This study takes manufacturers, suppliers and sellers in the three-level supply chain as the research object and does not consider the synergistic evaluation between distributors and consumers in the supply chain, which can be further explored in this direction in the future.

Advanced manufacturing clusters, as the main force of manufacturing development, and the synergistic development of supply chain are one of the important driving forces for the high-quality development of China’s manufacturing industry. As a new type of network organization coupling industrial clusters and supply chains, cluster supply chain is conducive not only to improving the competitiveness of cluster supply chains but also to upgrading cluster supply chains through horizontal synergy within the cluster and vertical synergy in the supply chain.

Research can help accelerate the transformation and upgrading of clustered supply chains in the manufacturing industry, promote high-quality development of the manufacturing industry and accelerate the rise of the global value chain position of the manufacturing industry.

(1) Innovation of research perspective. Starting from two perspectives of horizontal synergy and vertical synergy, we take a core enterprise in the cluster supply chain as the starting point, horizontally explore the main enterprises of the cluster as the research object of horizontal synergy, vertically explore the upstream and downstream enterprises of the supply chain as the research object of vertical synergy and explore the coupling synergy of cluster supply chain as two subsystems, which provides new perspectives of evaluation of the degree of synergy and synergy evaluation. (2) Innovation of research content. Nine manufacturing clusters are selected as research samples, and through data collection and model analysis, it is verified that the evaluation model and implementation algorithm designed in this paper have strong practicability, which not only provides methodological reference for the evaluation of manufacturing cluster-type supply chain synergy but also reduces the loss caused by the instability of clusters and supply chains and then provides a theoretical basis for improving the overall performance of cluster-type supply chains.

The purpose of this paper is to achieve optimal climbing control of the gas-insulated switchgear (GIS) robot, as the authors know that the GIS inspection robot is a kind of artificial intelligent mobile equipment which auxiliary or even substitute human labor drive on the inner wall of the gas-insulated metal enclosed switchgear. The GIS equipment fault inspection and maintenance can be realized through the robot manipulator on the mobile platform and the camera carried on the fuselage, and it is a kind of intelligent equipment for operation. To realize the inspection and operation of the GIS equipment pipeline without blind spots, the robot is required to be able to travel on any wall inside the pipeline, especially the top of the pipeline and both right and left sides of the pipeline, which requires the flexible climbing of the GIS inspection robot. The robot device has a certain adsorption function to ensure that the robot is fully attached to the wall surface. At the same time, the robot manipulator can be used for collision-free obstacle avoidance operation planning in the narrow operation space inside the GIS equipment.

The above two technologies are the key that the robot completes the GIS equipment inspections. Based on this, this paper focuses on modeling and analysis of the chassis adsorption characteristics for the GIS inspection robot. At the same time, the Denavit Hartenberg (D-H) coordinate model of the robot arm system has been established, and the kinematics forward and inverse solutions of the robot manipulator system have been derived.

The reachable working space point cloud diagram of the robot manipulator in MATLAB has been obtained based on the kinematics analysis, and the operation trajectory planning of the robot manipulator using the robot toolbox has been obtained. The simulation results show that the robot manipulator system can realize the movement without collision and obstacle avoidance. The space can cover the entire GIS pipeline so as to achieve no blind area operation.

Finally, the GIS inspection robot physical prototype system has been developed through system integration design, and the inspection, maintenance operation experiment has been carried out in the actual GIS equipment. The entire robot system can complete the GIS equipment inspection operation soundly and improve the operation efficiency. The research in this paper has important theoretical significance and practical application value for the optimization design and practical research of the GIS inspection robot system.

With the rise in international construction projects, addressing the psychological health concerns of expatriate construction professionals (EXCPs) has become of paramount importance. Therefore, this study aims to identify and evaluate effective intervention measures to promote optimal psychological health and well-being in overseas working environments.

Intervention measures were identified through a comprehensive literature review. Subsequently, using a case study of Chinese international contractors, data were collected via a quantitative survey administered to EXCPs holding managerial positions in international construction projects. Fuzzy synthetic evaluation was employed to analyze the data.

The findings identified 23 intervention measures and 4 constructs, among them, measures focused on enhancing organizational justice and training practices offer the greatest potential for enhancing the psychological health and well-being during international assignments. Furthermore, the analysis showed that the overall criticality of the intervention measures to the international contractors is significant, suggesting that if put into practice, the psychological health and well-being of EXCPs can be significantly enhanced.

While prior research has explored intervention measures suitable for construction professionals working on domestic projects, little attention has been paid to EXCPs in the context of international construction projects. This study offers an initial exploration of the most crucial intervention measures and provides a valuable resource for policymakers and practitioners seeking to establish a psychologically healthy working environment for international construction projects.