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The openings on aircraft structures can be modeled from an aerodynamical point of view as lid-driven cavities (LDC). This paper aims to show the primary verification and validation (V&V) process in computational fluid dynamics (CFD, and to investigate the influences of numerical settings on the efficiency and accuracy for solving the LDC problem.

To dig into the details of CFD approaches, this paper outlines the design, implementation, V&V and results of an efficient explicit algorithm. The parametric study is performed thoroughly focusing on various iteration methods, grid density discretization terms and Reynolds number effects.

This study parameterized the numerical implementation which provides empirical insights into how computational accuracy and efficiency are affected by changing numerical settings. At a low Reynolds number (not over 1,000), the time-derivative preconditioning is necessary, and k = 0.1 can be the optimal value to guarantee the efficiency, as well as the stability. A larger artificial viscosity (c = 1/16) would relieve the calculating oscillation issue but proportionally increase the discretization error. Furthermore, the iteration method and the mesh quality are two key factors that affect the convergence efficiency, thus need to be selected “wisely”.

The study shows how numerical implementation can enhance an accurate and efficient solution. This workflow can be used to determine the best parameter settings whenever CFD researchers applying this LDC problem as a complementary design tool for testing newly developed solvers.

The studied LDC problem is representative of CFD analysis in real aircraft structures. These numerical simulations provide a cost-effective and convenient tool to understand the parameter sensitivity, solution receptivity and physics of the CFD process.

The purpose of this paper is to suggest an implicit integration method for updating the constitutive relationships in the newly proposed anisotropic egg-shaped elastoplastic (AESE) model and to apply it in ABAQUS.

The implicit integration algorithm based on the Newton–Raphson method and the closest point projection scheme containing an elastic predictor and plastic corrector are implemented in the AESE model. Then, the integration code for this model is incorporated into the commercial finite element software ABAQUS through the user material subroutine (UMAT) interface to simulate undrained monotonic triaxial tests for various saturated soft clays under different consolidation conditions.

The comparison between the simulated results from ABAQUS and the experimental results demonstrates the satisfactory performance of this implicit integration algorithm in terms of effectiveness and robustness and the ability of the proposed model to predict the characteristics of soft clay.

The rotational hardening rule in the AESE model together with the implicit integration algorithm cannot be considered.

The singularity problem existing in most elastoplastic models is eliminated by the closed, smooth and flexible anisotropic egg-shaped yield surface form in the AESE model. In addition, this notion leads to an efficient implicit integration algorithm for updating the highly nonlinear constitutive equations for unsaturated soft clay.

Project-based organizations (PBOs) face challenges to enhance employee work engagement because of dynamic and constant role configuration. Accordingly, this study aims to explore how ethical leadership enhances employee work engagement from a sensemaking perspective.

This study used a questionnaire-based quantitative research design to collect data from 194 full-time employees in PBOs. The data were analyzed via partial least squares-structural equation modeling (PLS-SEM) technique to test hypotheses.

The findings show a positive relationship between ethical leadership and work engagement. Additionally, the relationship between ethical leadership and work engagement is mediated by two sensemaking mechanisms, i.e. goal commitment and prosocial.

This study deepens the understanding of how ethical leadership enhances work engagement in PBOs by providing two sensemaking mechanisms. By exploring the sensemaking process through which ethical leaders help employees construct identity, the findings contribute to the current literature on how ethical leadership enhances work engagement in PBOs.

As online learning is the embryonic form of education in the metaverse, it is extremely important to explore the behavioral preferences of users. The aim is to explore the impact of interactive features on continuous use in online learning and to further explore what kind of interaction mode should be constructed for different types of students to obtain the best educational experience.

The study developed an empirical model and used a real-world dataset to test hypotheses. Specifically, the interaction in online learning is analyzed from different dimensions, including the interaction intensity of multiple subjects, the immersion of interactive technology, the timeliness of interactive feedback, and the fun in interaction.

The authors found that the intensity of interaction, immersion, timeliness of feedback and fun in the interaction all had significant positive effects on continuous use. Among them, the most important is the interaction between teachers and students. With the growth of user grades, the role of parents in the interaction is getting smaller and smaller, and the fun in the interaction is gradually becoming unnecessary. For high school students, gamified interactions can even have a negative impact. In addition, from the perspective of gender, males prefer immersive interaction, while females pay more attention to themselves and have negative feedback on fees.

The authors deepened the interaction and summarized the impact of different interactive features on continuous use in online learning platforms. The authors focused on the impact of the immersive experience brought by the application of interactive technology, which can confirm the user behavior preferences of online learning in the context of the metaverse. The research also provides a reference for online learning institutions to set up course interaction modes and targeted marketing programs.

With the advent of the era of Big Data, the scale of knowledge graph (KG) in various domains is growing rapidly, which holds huge amount of knowledge surely benefiting the question answering (QA) research. However, the KG, which is always constituted of entities and relations, is structurally inconsistent with the natural language query. Thus, the QA system based on KG is still faced with difficulties. The purpose of this paper is to propose a method to answer the domain-specific questions based on KG, providing conveniences for the information query over domain KG.

The authors propose a method FactQA to answer the factual questions about specific domain. A series of logical rules are designed to transform the factual questions into the triples, in order to solve the structural inconsistency between the user’s question and the domain knowledge. Then, the query expansion strategies and filtering strategies are proposed from two levels (i.e. words and triples in the question). For matching the question with domain knowledge, not only the similarity values between the words in the question and the resources in the domain knowledge but also the tag information of these words is considered. And the tag information is obtained by parsing the question using Stanford CoreNLP. In this paper, the KG in metallic materials domain is used to illustrate the FactQA method.

The designed logical rules have time stability for transforming the factual questions into the triples. Additionally, after filtering the synonym expansion results of the words in the question, the expansion quality of the triple representation of the question is improved. The tag information of the words in the question is considered in the process of data matching, which could help to filter out the wrong matches.

Although the FactQA is proposed for domain-specific QA, it can also be applied to any other domain besides metallic materials domain. For a question that cannot be answered, FactQA would generate a new related question to answer, providing as much as possible the user with the information they probably need. The FactQA could facilitate the user’s information query based on the emerging KG.

This paper aims to present a method to improve the sensitive and low probabilities of false alarm of a manipulator in a human–robot interaction environment, which can improve the performance of the system owing to non-linear uncertainty in the model of the robot controller.

A novel collision detection method based on adaptive residual estimation is proposed, promoting the detection accuracy of the collision of the manipulator during operation. First, a general momentum residual estimator is designed to incorporate the non-linear factors of the manipulator (e.g. joint friction, speed and acceleration) into the residual-related uncertainty of the model. Second, model parameters are estimated through gradient correction. The residual filter is used to determine the dynamic threshold, resulting in higher detection accuracy. Finally, the performance of the residual estimation scheme is evaluated by comparing the dynamic threshold with residual in real-time experiments where a single Universal Robot 5 robot end–effector collides with the obstacle.

Experimental results demonstrate that the collision detection system can improve sensitivity and lead to low probabilities of false alarm of non-linear uncertainty in the model.

The method proposed in this article can be applied to industry and human–robot interaction area.

An adaptive collision detection method is proposed in this paper to address non-linear uncertainties of the model in industrial application.

Wine tourism is gaining increasing popularity among Chinese tourists, making it necessary to thoroughly examine tourist behavior. While online reviews posted by wine tourists have been extensively studied from the perspectives of destinations and wineries, the perspective of the tourists themselves has been overlooked. To address this gap, this study aims to identify significant attributes intrinsic to the tourism experiences of Chinese wine tourists by adopting a text-mining approach from a tourist-centric perspective.

The authors use topic modeling to extract these attributes, calculate topic intensity to understand tourists’ attention distribution across these attributes and conduct topical sentiment analysis to evaluate tourists’ satisfaction levels with each attribute. The authors perform importance-performance analyses (IPAs) using topic intensity and sentiment scores. Furthermore, the authors conduct semistructured in-depth interviews with Chinese wine tourists to gain insights into the underlying reasons behind the key findings.

The study identifies eleven attributes for domestic wine tourists and seven attributes for outbound wine tourists. From the reviews of both domestic and outbound tourists, three common attributes have been identified: “scenic view”, “wine tasting and purchase” and “wine knowledge”.

According to the results of the IPAs, there is a pressing need for enhancements in the wine tasting and purchasing experience at domestic wine attractions. Additionally, managers of domestic wine attractions should continue to prioritize the positive aspects of the family trip experience and scenic views. On the other hand, for outbound wine attractions, it is crucial for managers to maintain their efforts in providing opportunities for wine knowledge acquisition, ensuring scenic views and upholding the reputation of wine regions.

First, this study breaks new ground by adopting a tourist-centric perspective to extract significant attributes from real wine tourism reviews. Second, the authors conduct a comparative analysis between Chinese wine tourists who travel domestically and those who travel abroad. The third novel aspect of this study is the application of IPA based on textual review data in the context of wine tourism. Fourth, by integrating topic modeling with qualitative interviews, the authors use a mixed-method approach to gain deeper insights into the experiences of Chinese wine tourists.

The purpose of this paper is to examine the effect of regulatory reform on the asset allocation and capitalization of Chinese banks from 2002 to 2007, a period following China's entry into the World Trade Organization (WTO).

The evidence rejects a hypothesis that the four categories of banks operating in China – the Big Four, Majority State, Majority Private, and Majority Foreign banks have converged toward common targets. Supplemental analysis indicates that domestic banks, but not foreign banks, adjust equally to their targets.

The paper concludes that, although Chinese banking remained segmented during this unique transitional period, a more uniform pattern has emerged for those Chinese banks that are domestically owned.

The authors employ a methodology that is explicitly designed to determine if banks have converged toward common approaches to asset allocation and capitalization, which has not been studies previously.

In order to obtain functionalized core-shell nanoparticles (CSNPs) as excellent toughening agents for epoxy resins. The paper aims to discuss these issues.

Functionalized CSNPs containing epoxy groups on the surface were synthesized by emulsion polymerization with butyl acrylate as the core and methyl methacrylate copolymerizing with glycidyl methacrylate (GMA) as the shell. CSNPs were used as toughening agents for epoxy resins and their chemical structure was characterized by FT-IR. The morphology of modified epoxy networks (MEPN) was analyzed by SEM and TEM. Both the mechanical properties and thermodynamic properties were studied.

The results show that nearly spherical CSNPs with the particle size of 50-100 nm are obtained. A certain amount of CSNPs are uniformly dispersed in epoxy resins by the grinding method and the MEPN shows the ductile fracture feature. The miscibility between CSNPs and epoxy matrix increases with the increase of GMA concentration which makes more bonds form between them. Epoxy resins toughened with 10 wt% CSNPs containing 10 wt% GMA show the best mechanical properties and the increase in tensile strength and impact strength of the MEPN is 13.5 and 59.7 percent, respectively, over the unmodified epoxy networks. And the improvement in impact strength is not accompanied with loss of thermal resistance.

The MEPN can be used as high-performance materials such as adhesives, sealants and matrixes of composites.

The functionalized CSNPs are novel and it can greatly increase the toughness of epoxy resins without loss of thermal resistance.

The authors investigated the impacts of differentiated transformational leadership (TFL), including team-focused TFL and individual-focused TFL, on team creativity through the mediating effect of team conflict, consisting of task conflict and relationship conflict.

The authors designed and conducted a close-to-reality experiment, enrolling 180 students and six professors from a large Chinese university. Student participants worked on a real marketing project and professor participants imitated the behaviors of transformational leaders. Using the computed values of team-focused TFL, individual-focused TFL, team creativity, task conflict and relationship conflict, the authors assessed the relationship among differentiated TFL, team creativity and team conflict.

Team-focused TFL has a significantly positive impact on team creativity through the mediating effect of task conflict, whereas individual-focused TFL has a significantly negative impact on team creativity through the mediating effect of relationship conflict.

From a new perspective of team conflict, the authors revealed the “black box” of the differentiated TFL–team creativity relationship. Moreover, other determinants were well controlled in the experiment, and thus, the authors effectively clarified the intervening mechanism of differentiated TFL on team creativity through the mediating effect of team conflict.