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Considering the randomness of physical parameters of structural material, dynamic characteristic topology optimization mathematical model based on reliability of planar continuum structures is built in this paper. In which topology information variables of the structure are taken as design variables, minimizing the mean value of total structural weight as objective function and satisfying the reliability requirement of structural dynamic characteristic as constraints. In the process of optimization, the ESO method based on probability is adopted as solution strategy. At the same time, distribution function method is utilized to convert the reliability constraints into conventional constraints formally. A square thin plate with four sides fixed is used as an example to demonstrate the rationality and validity of the presented model.

In order to make the aperture of spatial deployable antenna larger, this paper proposed the study on a spatial annular tensegrity structure with 100 m large scale, which could be one of the ideal solutions to improve the dimension of the antenna. This study is aiming to figure out the dynamic characteristic of ultra-large annular tensegrity and address the problem of insufficient rigidity with local modes that many ring truss-type deployable antenna structures have faced.

This work is carried out based on the nonlinear dynamic modelling when fully considering the effect of bending and torsion deformation of beams, as well as the pretension of cables. Additionally, the structural stability analysis based on the proposed stability criterion is also presented to evaluate the tensegrity configuration with different distribution of cable groups.

This research results verify that the modified structure with radial ribs could eliminate the effect of the local vibration mode on stiffness and is suitable to meet the requirements of the annular tensegrity structure. Additionally, the calculation results demonstrate that the structural configuration of annular tensegrity with 36 groups of cables which share the nodes with radial ribs is more appropriate to enhance the stiffness and structural stability.

A new large annular tensegrity structure with radial ribs and tensioned cables is proposed. Based on the proposed structural configuration, the positive definiteness of the tangent stiffness matrix is carried out as the criterion of stability and the composition of the analytical expression of the tangent stiffness matrix is analyzed. Four levels of tensegrity structure stability have been carried out and the influence of the structural parameters on the stability and the rigidity has been analyzed. A scaled-down prototype is developed to verify the feasibility of the design of the hoop-column-rib configuration by the deployment and dynamic experiment.

The purpose of this paper is to present a method for evaluating the structural dynamic characteristics of a flying probe tester.

The dynamic characteristics of a flying probe tester framework were analyzed based on a finite element analysis method. First, modal analysis was carried out to characterize the modal parameters of the structure. Second, the harmonic response was analyzed according to the modal analysis and the response curve of the structural system was studied. Finally, transient analysis was conducted to obtain the transient response of the structures at the beginning of the vibration.

The natural frequency and the response frequency of a natural granite structure was the highest and the transient vibration displacement amplitude was the smallest compared with cast iron and artificial stone structures.

A comprehensive understanding of the dynamic characteristics of the framework of a flying probe tester with three different materials has been achieved. The results of the analyses provide a reference for the framework design of a flying probe tester.

In the era of mobile internet, the social Q&A community has built a large-scale and complex knowledge label network through its internal knowledge units, and the scale and structure of the network have changed over time. By analysing the structural characteristics and evolution rules of knowledge label networks, the main purpose of this study is to understand the internal mechanisms of the replacement of old and new knowledge and the expansion of knowledge element boundaries, so as to explore the realization path of knowledge management in the new era from the perspective of complex networks.

This paper uses distributed crawlers to capture 419,349 samples from the Zhihu platform. Each sample contains 33 characteristic dimensions, and the natural year is used as the sliding window to divide the whole. In this study, the global knowledge label network and 11 local knowledge label networks are first constructed. Then, the degree distribution analysis and central node exploration of the knowledge label network are carried out using the complex network method. Finally, the average shortest path and average clustering coefficient of the network are analysed by the time series method, and the ARIMA model is used to predict the evolution of the correlation coefficient.

The research results show that the dissimilation degree of the degree distribution of the knowledge label network has gradually decreased from 2011 to 2021, and the attention of users in the knowledge community has shown a trend of distraction and diversification over time. With the expansion of the scale of the knowledge label network and the transformation to an information network, the network sparsity is becoming more and more obvious, and the knowledge granularity of the Q&A community is being refined and diversified. The prediction of the correlation coefficient of the knowledge label network by the ARIMA model shows that the connection between the labels is lacking diversity and the opinion strengthening phenomenon tends to strengthen, which is more likely to form the “echo chamber effect”, resulting in mutual isolation and even opposition between different circles. The Q&A community is about to enter a mature stage, and the corresponding status of each label has been finalized. The future development trend of label networks will be reflected in the substitution between labels, and the specific structure will not change significantly.

The Q&A community model is the trend in Web 2.0 community development. This study proves the effectiveness of complex networks and time series prediction methods in knowledge label network mining in the Q&A community.

The purpose of this paper is to design a glass handling robot and conduct a finite element analysis and structural optimization to solve the automation handling problem of large-scale glass production line and aiming at the phenomenon that the vibration of robot manipulator may result in breakage of glass products, especially the fragile chemical or medical glassware. Making modal analysis for the robot is to determine its natural frequencies and vibration modes and lay a foundation for the transient analysis to study the vibration shock response of the robot during its start-up and emergency stop operation.

First, a 3D model of the robot is established according to the requirements of the production field and a finite element model is built on the basis of the 3D model. Then the modal and transient analyses of the robot are carried out according to the fact that the maximum vibration impact of the robot usually appears at the start and emergency stop.

The structure of the robot is improved according to the results of finite element analysis. The dynamic analysis results show that the improved robot’s ability to resist deformation under the impact of vibration shock is enhanced, and the robot can operate smoothly and meet the requirements of design in industrial environments.

The research results avoided the damage caused by the vibration and improved the service life of the robot, providing a foundation for the structural design and mass production of the glass handling robot.

It is essential to understand the structural dynamic behavior of electrical machines to predict their acoustic and vibrational behavior. Stacking technology, which is used to manufacture soft magnetic cores, has a strong influence on the material properties. The purpose of this paper is therefore to research the influence of the stacking technologies welding and bonding with bake varnish on the modal properties of iron cores.

A finite element simulation model is developed based on homogenization of the stator core. Eigenfrequencies, modeshapes and modal damping ratios are extracted from measurements and are used to validate the simulation model.

Modal characteristics depend on the participation of certain material layers at a certain mode. Higher amount of shear deformation results in higher modal damping. Bonded stacks exhibit lower shear stiffness and higher damping ratios.

This research paper provides insights to the modal characteristics of iron cores used in electric machine and compares the influence of stacking technologies.

This chapter discusses the emerging network science approach to the study of complex adaptive systems and applies tools derived from statistical physics to the analysis of tourism destinations. The authors provide a brief history of network science and the characteristics of a network as well as different models such as small world and scale free networks, and dynamic properties such as resilience and information diffusion. The Italian resort island of Elba is used as a case study allowing comparison of the communication network of tourist organizations and the virtual network formed by the websites of these organizations. The study compares the parameters of these networks to networks from the literature and to randomly created networks. The analyses include computer simulations to assess the dynamic properties of these networks. The results indicate that the Elba tourism network has a low degree of collaboration between members. These findings provide a quantitative measure of network performance. In general, the application of network science to the study of social systems offers opportunities for better management of tourism destinations and complex social systems.

The research on social media-based academic communication has made great progress with the development of the mobile Internet era, and while a large number of research results have emerged, clarifying the topology of the knowledge label network (KLN) in this field and showing the development of its knowledge labels and related concepts is one of the issues that must be faced. This study aims to discuss the aforementioned issue.

From a bibliometric perspective, 5,217 research papers in this field from CNKI from 2011 to 2021 are selected, and the title and abstract of each paper are subjected to subword processing and topic model analysis, and the extended labels are obtained by taking the merged set with the original keywords, so as to construct a conceptually expanded KLN. At the same time, appropriate time window slicing is performed to observe the temporal evolution of the network topology. Specifically, the basic network topological parameters and the complex modal structure are analyzed empirically to explore the evolution pattern and inner mechanism of the KLN in this domain. In addition, the ARIMA time series prediction model is used to further predict and compare the changing trend of network structure among different disciplines, so as to compare the differences among different disciplines.

The results show that the degree sequence distribution of the KLN is power-law distributed during the growth process, and it performs better in the mature stage of network development, and the network shows more stable scale-free characteristics. At the same time, the network has the characteristics of “short path and high clustering” throughout the time series, which is a typical small-world network. The KLN consists of a small number of hub nodes occupying the core position of the network, while a large number of label nodes are distributed at the periphery of the network and formed around these hub nodes, and its knowledge expansion pattern has a certain retrospective nature. More knowledge label nodes expand from the center to the periphery and have a gradual and stable trend. In addition, there are certain differences between different disciplines, and the research direction or topic of library and information science (LIS) is more refined and deeper than that of journalism and media and computer science. The LIS discipline has shown better development momentum in this field.

KLN is constructed by using extended labels and empirically analyzed by using network frontier conceptual motifs, which reflects the innovation of the study to a certain extent. In future research, the influence of larger-scale network motifs on the structural features and evolutionary mechanisms of KLNs will be further explored.

In recent years, network science has become a dynamic and promising discipline. This study aims to provide a brief summary of the subject and the application to the tourism domain.

This paper is based on a non-exhaustive survey of the literature.

The state-of-the-art of network science in tourism is explored and discussed, together with possible future developments.

This paper uses a limited set of works, those deemed the most significant to sketch the situation. The choice might be subjective, but the overall picture is clear. Given what accomplished so far, the methods of network science seem interesting both for their theoretical and practical outcomes. In essence, they provide a better and more objective view on the structural and dynamic characteristics of the tourism phenomenon and of the different tourism systems and components.

This paper critically reflects on the state of network science and its application to the tourism domain. Even without claiming to be complete, this paper takes a general perspective approach rather than examining single topics or issues.

The social responsibility of a tourism destination results from the combined efforts of the single stakeholders. This needs coordination and harmonization that cannot be achieved without a deep understanding of the structural and dynamic characteristics of the destination. A tourism destination is a complex dynamic system and requires specific methods to be analyzed and understood in order to better tailor governance actions for steering it along an evolutionary growth path, respectful of the social responsibility towards the community. Many methodological recommendations exist that allow to assess these features, and some have been successfully applied to tourism destinations. This paper aims to explore a new proposal: the visibility graph algorithm (VGA), which is able to provide the required level of information in a fast and simple way.

VGA is a technique to map a time series into a network. The method and its implementation are relatively simple and straightforward. The mapping allows examining the system's properties by using network analytic methods. An example is worked out using data from two destinations: Italy as a country and the island of Elba, one of its most popular areas.

The complexity properties of the two destinations are examined and found in agreement with those obtained by using more complicated approaches, thus strengthening the reliability of the method.

This paper provides a new method to examine a tourism destination using a readily available set of data and a simple algorithm. The contribution of this work is mainly methodological. The technique provides insights into the complex structure and dynamics of a tourism destination. This has important implications for those interested in enriching the toolsets used to study a destination from a complex system perspective.