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Physics-informed neural networks (PINNs) have become a new tendency in flow simulation, because of their self-advantage of integrating both physical and monitored information of fields in solving the Navier–Stokes equation and its variants. In view of the strengths of PINN, this study aims to investigate the impact of spatially embedded data distribution on the flow field results around the train in the crosswind environment reconstructed by PINN.

PINN can integrate data residuals with physical residuals into the loss function to train its parameters, allowing it to approximate the solution of the governing equations. In addition, with the aid of labelled training data, PINN can also incorporate the real site information of the flow field in model training. In light of this, the PINN model is adopted to reconstruct a two-dimensional time-averaged flow field around a train under crosswinds in the spatial domain with the aid of sparse flow field data, and the prediction results are compared with the reference results obtained from numerical modelling.

The prediction results from PINN results demonstrated a low discrepancy with those obtained from numerical simulations. The results of this study indicate that a threshold of the spatial embedded data density exists, in both the near wall and far wall areas on the train’s leeward side, as well as the near train surface area. In other words, a negative effect on the PINN reconstruction accuracy will emerge if the spatial embedded data density exceeds or slips below the threshold. Also, the optimum arrangement of the spatial embedded data in reconstructing the flow field of the train in crosswinds is obtained in this work.

In this work, a strategy of reconstructing the time-averaged flow field of the train under crosswind conditions is proposed based on the physics-informed data-driven method, which enhances the scope of neural network applications. In addition, for the flow field reconstruction, the effect of spatial embedded data arrangement in PINN is compared to improve its accuracy.

The deviant behavior (DB) of construction workers has always been a troubling event in project management. Although scholars continue to search for the main causes of this behavior to curb it at the source, the authors know less about the role and contribution of the team. This study aims to uncover the mechanisms and conditions under which collective moral judgment focus on self (CMJS) effectively enhances DB.

Adopting Chinese construction enterprises as samples, a hierarchical linear model (HLM) is used to test the results of the hypothesis. Moderated mediating effects are used to analyze the potential mechanisms and boundary conditions of DB.

The results of the HLM analysis show that CMJS could directly and significantly induce DB, and moral disengagement (MD) plays a mediator role in this association. In addition, the positive relationship between MD and DB is stronger when performance-avoidance goal orientation (PaGO) or overqualification (Overq) is higher.

The conditions and mechanisms that influence DB are not unique. Future study could examine the explanatory and weighting mechanisms of DB from other perspectives or to construct a framework and summarize the factors that may influence DB.

This study provides a rich theoretical basis for the prevention and correction of construction workers' DB in Chinese construction firms from the perspective of CMJS. In addition, objective moral judgments contribute to guiding employees' moral cognitive processes and positive work.

This study extends existing research on DB and advances the practical outcomes of construction project governance. It not only illustrates that CMJS has a direct impact on DB but also clarifies the mechanisms and conditions that predispose to the generation of DB, filling the research gap on construction workers' DB from cross-level mechanisms and also enriching the theoretical system for preventing this behavior.

In the context of Industry 4.0, intelligent construction technologies (ICT) represented by information technology and networking will undoubtedly provide new impetus to the development of the prefabricated building supply chain (PBSC), but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies. Therefore, this paper aims to reveal the interactions between stakeholders and clarify the critical risk nodes and interactions in information sharing of PBSC (IS-PBSC), and propose targeted risk mitigation strategies.

Firstly, this paper creatively delineates the risks and critical stakeholders of IS-PBSC. Secondly, Data is collected through questionnaires to understand the degree of risks impact. Thirdly, with the help of NetMiner 4 software, social network analysis is conducted and IS-PBSC risk network is established to reveal critical risk nodes and interactions. Finally, further targeted discussion of critical risk nodes, the effectiveness and reasonableness of the risk mitigation strategies are proposed and verified through NetMiner 4 software simulation.

The results show that the critical risks cover the entire process of information sharing, with the lack of information management norms and other information assurance-related risks accounting for the largest proportion. In addition, the government dominates in risk control, followed by other stakeholders. The implementation of risk mitigation strategies is effective, with the overall network density reduced by 41.15% and network cohesion reduced by 24%.

In the context of Industry 4.0, ICT represented by information technology and networking will undoubtedly provide new impetus to the development of the PBSC, but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies.

Based on the results of risk network visualization analysis, this paper proposes an ICT-based IS-PBSC mechanism that promotes the development of the integration of ICT and PBSC while safeguarding the benefits of various stakeholders.

This study aims to investigate the influence mechanism of brazing and aging on the strengthening and corrosion behavior of novel multilayer sheets (AA4045/AA7072/AA3003M/AA4045).

Polarization curve tests, immersion experiments and transmission electron microscopy analysis were used to study the corrosion behavior and tensile properties of the sheets before and after brazing and aging.

The strength of the sheet is weakened after brazing due to brittle eutectic phases, and recovered after aging due to enhanced precipitation strengthening in the AA7072 interlayer. The core of nonbrazed sheets cannot be protected due to the significant galvanic coupling effect between the intermetallic particles and the substrate. Brazing and aging treatments promote the redissolved of second phased and limit corrosion along the eutectic region in the clad, allowing the core to be protected.

AA7xxx alloy was added to conventional brazed sheets to form a novel Al alloy composite sheet with AA4xxx/AA7xxx/AA3xxx structure. The strengthening and corrosion mechanism of the sheet was proposed. The added interlayer can sacrificially protect the core from corrosion and improves strength after aging treatment.

Prefabricated construction is an innovative technique for decreasing carbon emissions in the construction industry. However, as the investors of housing projects, a majority of developers are unwilling to adopt prefabricated housing in practice. To promote prefabricated housing, this study aims to develop an integrated framework of fuzzy-decision making trial and evaluation laboratory (fuzzy-DEMATEL) and system dynamics (SD) to understand the underlying influencing mechanism of developers' willingness.

Through literature review, a total of 17 influencing factors were identified. Then, the interrelationships among the factors were evaluated by 10 experienced professionals, and the impacts given and received by each factor were further analyzed through fuzzy-DEMATEL. Based on the technology acceptance model (TAM), a SD model was developed to explore the influencing mechanism.

The major cause factors were identified, including mandatory implementation policies, economic incentive policies, environmental protection policies, component standardization and developers' economic strength. This group of factors was expected to be given priority attention in the case of limited resources. On the other hand, the results indicated that economic incentive policies and mandatory implementation policies could affect the developers' willingness via perceived usefulness, while the others mainly influenced perceived ease of use.

Little research has focused on the interrelationships among the influencing factors of developers' willingness to adopt prefabricated housing. This study contributed to understanding the mechanism of developers' willingness from a systematic view and providing the priority of influencing factors. Several strategies were proposed to improve the practical implementation of prefabricated housing development.

The quality liability of prefabricated components (PCs) is a major issue among key stakeholders. The blockchain-based quality tracking systems are supposed to support a more transparent and trusting quality control process. However, many factors affect the stakeholders' willingness toward the adoption of such quality tracking systems. The purpose of this research is to investigate the key factors that influence the stakeholders' adoption decisions toward the application of the quality tracking system in PCs and develop coping strategies.

An evolutionary game model is established that includes the manufacturer, constructor and developer. Four scenarios of equilibriums and the game's evolutionary stable strategies are analyzed, and the corresponding stability conditions are then obtained. Based on the tripartite game model, two representative projects are used as case studies to simulate how different factors affect the stakeholders' decisions.

First, trade-offs between cost and benefits were the most prominent factor in the adoption decision-making. Second, the advancement of technologies would compensate for their immaturity. Third, subsidy and penalty provision of the developer and high-level trust both incentivize the stakeholders to adopt the quality tracking systems.

This research investigates the influence of technology, environment and participant related factors on the adoption decisions of the quality tracking system for PCs and discovered that technology maturity and advancement played an essential role. It is expected that the research findings would be of value to policy makers and project management personnel for better quality control of prefabricated construction.

This study aims to explore the innovative governance structures enabled by blockchain-based decentralized autonomous organizations (DAOs) in the context of international business (IB). As nonhierarchical entities managed through collective voting and peer-to-peer interactions, DAOs challenge traditional assumptions of multinational corporation (MNC) governance.

The authors perform a literature review, which combines qualitative content analysis of both academic papers on DAO and whitepapers with quantitative analysis of bibliometrics using VosViewer.

The findings highlight DAOs’ ability to generate new research questions and offer a foundation for future studies on decentralized governance in IB. Through a bibliometric analysis of 73 papers from Web of Science and qualitative content analysis, the authors identify four primary research streams in the DAO literature. A deep dive into financial DAOs, or DeFi DAOs, reveals insights into their governance mechanisms and implications for the studies in the field of IB.

Research on DAOs is in its early stages, and the practice in IB is nascent. As the regulatory, economic and technological landscape for DAOs changes, more research will be needed on the governance mechanisms and their sustainability.

This paper advances the field by providing a multilevel analysis of DAOs’ potential impact on IB, considering macro (country), meso (MNC/DPE) and micro (multicultural team and individual) levels.

The use of additive manufacturing in many branches of industry is increasing significantly because of its many advantages, such as being able to produce complex parts that cannot be produced by classical methods, using fewer materials, easing the supply chain with on-site production, being able to produce with all kinds of materials and producing lighter parts. The binder jetting technique, one of the additive manufacturing methods researched within the scope of this work, is predicted to be the additive manufacturing method that will grow the most in the next decade, according to many economic reports. Although additive manufacturing methods have many advantages, they can be slower than classical manufacturing methods regarding production speed. For this reason, this study aims to increase the manufacturing speed in the binder jetting method.

Adaptive slicing and variable binder amount algorithm (VBAA) were used to increase manufacturing speed in binder jetting. Taguchi method was used to optimize the layer thickness and saturation ratio in VBAA. According to the Taguchi experimental design, 27 samples were produced in nine different conditions, three replicates each. The width of the samples in their raw form was measured. Afterward, the samples were sintered at 1,500 °C for 2 h. After sintering, surface roughness and density tests were performed. Therefore, the methods used have been proven to be successful. In addition, measurement possibilities with image processing were investigated to make surface roughness measurements more accessible and more economical.

As a result of the tests, the optimum printing condition was decided to be 180–250 µm for layer thickness and 50% for saturation. A separate test sample was then designed to implement adaptive slicing. This test sample was produced in three pieces: adaptive (180–250 µm), thin layer (180 µm) and thick layer (250 µm) with the determined parameters. The roughness values of the adaptive sliced sample and the thin layer sample were similar and better than the thick layer sample. A similar result was obtained using 12.31% fewer layers in the adaptive sample than in the thin layer sample.

The use of adaptive slicing in binder jetting has become more efficient. In this way, it will increase the use of adaptive slicing in binder jetting. In addition, a cheap and straightforward image processing method has been developed to calculate the surface roughness of the parts.

The purpose of this paper is to study the anodic dissolution processes of alloy 690 in NaCl + Na₂S₂O₃ solutions by using digital holography.

The digital holography technique was used to in situ observe the dynamic processes occurring at the electrode|electrolyte interface during the anodic dissolution of alloy 690 in NaCl + Na₂S₂O₃ solutions, both in the presence and absence of a magnetic field (MF).

In 3.5% NaCl + 0.01 M Na₂S₂O₃ solutions, MF inhibited intergranular corrosion (IGC) because it increased the defects in the oxide film and facilitated the uniform adsorption of low concentration of S on these defects due to its stirring effects, which resulted in a weakened adsorption of S at the grain boundaries. Conversely, in 3.5% NaCl + 0.1 M Na₂S₂O₃ solutions, MF promoted IGC by increasing the number of defects in the oxide film, with lots of S species preferentially adsorbing at the grain boundaries. The resultant salt films formed more readily, inhibiting the formation of the oxide film at the grain boundaries.

Through the use of digital holography, it was possible to in situ observe the initiation of IGC at a single grain boundary and its progression to adjacent grain boundaries, regardless of the presence or absence of MF.

This paper aims to characterize the surface film formed on Alloys 800 and 690 in chloride and thiosulfate-containing solution at 300°C.

Alloy 800 and 690 were immersed in chloride and thiosulfate-containing solution at 300°C up to five days, and then the surface film was analyzed by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM) and energy dispersive X-ray spectrometers (EDX).

Through static immersion experiments in a high-temperature and high-pressure water environment, the alloy samples covered by surface film after five days of immersion were obtained. The morphology of the surface film was characterized at both horizontal and cross-sectional scales using SEM and focused ion beam-TEM techniques. It was observed that due to the influence of the quartz lining, the surface film primarily exhibited a bilayered structure. The first layer contained a significant amount of SiO₂, with a higher content of metal hydroxides compared to metal oxides. The second layer was predominantly composed of Fe, Ni and Cr, with a higher content of metal oxides compared to metal hydroxides.

The results showed that the materials of the lining of the autoclave could significantly influence the film composition of the tested material, which should be paid attention when analyzing the corrosion mechanism at high temperature.