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This paper aims to present a new friction-stir-weld robot for large-scale complex surface structures, which has high stiffness and good flexibility.

The robot system is designed according to manufacturability of large aluminum products in aeronautic and astronautic area. The kinematic model of the robot is established, and a welding trajectory planning method is also developed and verified by experiments.

Experimental results show that the robot system can meet the requirements of friction stir welding (FSW) for large-scale complex surface structures.

Compared with other heavy robotic arm and machine tool welding devices, this robot has better working quality and capability, which can greatly improve the manufacturability for large-scale complex surface structures.

The friction-stir-weld robot system is a novel solution for welding large-scale complex surface structures. Its major advantages are the high stiffness, good flexibility and high precision of the robot body, which can meet the requirements of FSW. Besides, a welding trajectory planning method based on iterative closest point (ICP) algorithm is used for welding trajectory.

The purpose of this paper is to analyze the network path and internal mechanism of risks’ cross-contagion between shadow banks and design strategies for preventing risk infection between shadow banks.

Using the complex network theory, analyze the mechanism of risks’ cross-contagion between shadow banks from the credit network, business relationship network (BRN) and social network (SN); the cross-contagion mechanism using the structural equation model on the basis of China’s shadow banks is tested; based on the three risk infection paths, the prevention and control strategies for risk infection using the mathematical models of epidemic diseases are designed.

There are three network risk contagion paths between shadow banks. One, the credit network, risks are infected crossly mainly through debt and equity relationships; two, the BRN, risks are infected crossly mainly through business network and macro policy transmission; three, investor SN, risks are infected crossly mainly through individual SN and fractal relationships. The following three strategies for preventing risk’s cross-contagion between shadow banks: one, the in advance preventing strategy is more effective than the ex post control strategy; two, increasing the risk management coefficient; three, reducing the number of risk-infected submarkets.

The research of this study, especially the strategies for preventing the risks’ cross-contagion, could provide theoretical and practical guidance for regulatory authorities in formulating risk supervision measures.

3D steady heat conduction analysis considering heat source is conducted on the fundamental of the fast multipole method (FMM)-accelerated line integration boundary element method (LIBEM).

Due to considering the heat source, domain integral is generated in the traditional heat conduction boundary integral equation (BIE), which will counteract the well-known merit of the BEM, namely, boundary-only discretization. To avoid volume discretization, the enhanced BEM, the LIBEM with dimension reduction property is introduced to transfer the domain integral into line integrals. Besides, owing to the unsatisfactory performance of the LIBEM when it comes to large-scale structures requiring massive computation, the FMM-accelerated LIBEM (FM-LIBEM) is proposed to improve the computation efficiency further.

Assuming N and M are the numbers of nodes and integral lines, respectively, the FM-LIBEM can reduce the time complexity from O(NM) to about O(N+ M), and a full discussion and verification of the advantage are done based on numerical examples under heat conduction.

(1) The LIBEM is applied to 3D heat conduction analysis with heat source. (2) The domain integrals can be transformed into boundary integrals with straight line integrals by the LIM. (3) A FM-LIBEM is proposed and can reduce the time complexity from O(NM) to O(N+ M). (4) The FM-LIBEM with high computational efficiency is exerted to solve 3D heat conduction analysis with heat source in massive computation successfully.

The purpose of this paper is to enhance the feasibility of the edge-based smoothed triangular (EST) element, some modifications are made in this study.

First, an efficient strategy based on graph theory is proposed to construct the edge system. Second, the stress is smoothed in global coordinate system based on edge instead of strain, which makes the theory of EST more rigorous and can be easily extended to the situation of multi elements sharing the same edge. Third, the singular degree of freedoms (DOFs) of the nodes linked by edges are restrained in edge local coordinate system, which makes the global stiffness matrix non-singular and can be decomposed successfully.

First, an efficient edge constructing strategy can make EST element more standout. Second, some modifications should be made to EST element to extend it to the situation with multi elements sharing the same edge, so that EST element can deal with the geometrical models with this kind of features. Third, the way to restrain the singular DOFs of EST element must be different from normal isoparametric triangle element, because the stiffness matrix of the smoothing domain is not computed in local coordinate system.

The modified EST element performs stably in engineering analysis including large scale problems and the situation with multi elements sharing the same edge, and the efficiency of edge system constructing is no longer the bottleneck.

This study aims to analyze the dynamic monitoring of deformation damage of steel structure buildings in long-term use. Although the steel structure building has the advantage of high structural strength, it will be deformed after being affected by factors such as corrosion and impact during long-term use, and which will affect building safety, especially the public building facilities. The dynamic monitoring of its security is an indispensable means.

This paper briefly introduced the principle of building information modeling (BIM)-based steel structure building information monitoring and the dynamic information monitoring system based on this principle. Then the monitoring system was used to analyze an operational steel structure suspension bridge in Xinxiang City, Henan Province, China, and compared it with the monitoring system based on back propagation (BP) neural network.

The results showed that the fitting degree of the dynamic deformation displacement data processed by BIM-based monitoring system was higher than that processed by BP-based monitoring system. Based on the comprehensive comparison of the dynamic data of all monitoring points, the BIM-based monitoring system had higher accuracy of deformation displacement monitoring and reliability of structural safety evaluation.

In summary, the BIM-based steel structure building monitoring system can effectively monitor the dynamic information of steel structure information.

This study aims to investigate the influence of contractual flexibility on different types of conflict, determine if contractual flexibility is significantly correlated with project success between contracting parties, verify the mediating effect of project conflicts on the relationship between contractual flexibility and project success and examine the relationship between different types of conflicts and project success in megaprojects.

A theoretical model was developed and a structured questionnaire survey was conducted with 468 professionals. The structural equation modeling technique was used to analyze the data.

The results showed that both types of contractual flexibility – term and process flexibility – were correlated with and significantly positively affected project success, and term flexibility was found to have a greater influence. The introduction of project conflicts significantly weakened the relationship between contractual flexibility and project success, verifying the partial mediating effect of conflicts. All types of project conflicts play a destructive role in achieving project success; relationship conflict had the largest negative effect. Contractual flexibility affects two paths with respect to project success: the direct path (contractual flexibility → project success) and the indirect path (contractual flexibility → conflict → project success). The direct effect of contractual flexibility on project success is positive; the corresponding indirect effect is negative. The direct effect is greater than the corresponding indirect effect.

Different types of conflicts may mutually transform to extent certain degree. However, this study did not address the potential influence of conflict transformation on project success. The results implied that more emphasis should be placed on contractual terms, particularly on developing flexible terms in the contractual document, when implementing megaprojects. Meanwhile, this study reveals the effects of conflicts on project success in megaprojects, which provides a useful reference for project stakeholders to avoid the negative effect of conflicts.

This study provides a better understanding of the relationship between contractual flexibility, types of conflicts in megaprojects and a reliable reference for the project manager to effectively deal with these related issues. This implies the contracting parties strengthen communication and cooperation to establish a trust mechanism, while reducing the negative influence of project conflicts and enhancing the positive effect of contractual flexibility.

Few studies have investigated the effects of contractual flexibility on conflict and project success in megaprojects; this study contributes significant theoretical and practical insights to contract management and conflict management and provides a reliable reference to achieve project success.

The purpose of this paper is to develop a categorization of sharing practices from a structured interdisciplinary literature review on the Sharing Economy. Instead of striving for a new definition, the authors distinguish nine types of sharing practices and provide an overview of prior investigations on sharing practices across three levels of analysis and 15 research areas. The structured analysis is translated into opportunities for future research on the Sharing Economy.

The study follows a structured literature review approach to uncover practices related to the Sharing Economy and similar phenomena. The authors analyze 210 articles from a broad number of disciplines, and develop a categorizing framework for Sharing Economy practices.

The paper identifies nine different types of sharing practices and provides a structured way for analyzing, comparing and positioning research on the Sharing Economy and related phenomena.

The categorization of sharing practices and the embedded interdisciplinary overview of studies on the Sharing Economy help to explain potentially contradictory research results and uncovers opportunities for future research in the topic area.

Given the variety of disciplines dealing with the Sharing Economy and the plenitude of definitions and related concepts, the categorization and research overview provides a consolidated view of the knowledge in the topic area and an effective tool for identifying paths for future research.

Crack detection of pavement is a critical task in the periodic survey. Efficient, effective and consistent tracking of the road conditions by identifying and locating crack contributes to establishing an appropriate road maintenance and repair strategy from the promptly informed managers but still remaining a significant challenge. This research seeks to propose practical solutions for targeting the automatic crack detection from images with efficient productivity and cost-effectiveness, thereby improving the pavement performance.

This research applies a novel deep learning method named TransUnet for crack detection, which is structured based on Transformer, combined with convolutional neural networks as encoder by leveraging a global self-attention mechanism to better extract features for enhancing automatic identification. Afterward, the detected cracks are used to quantify morphological features from five indicators, such as length, mean width, maximum width, area and ratio. Those analyses can provide valuable information for engineers to assess the pavement condition with efficient productivity.

In the training process, the TransUnet is fed by a crack dataset generated by the data augmentation with a resolution of 224 × 224 pixels. Subsequently, a test set containing 80 new images is used for crack detection task based on the best selected TransUnet with a learning rate of 0.01 and a batch size of 1, achieving an accuracy of 0.8927, a precision of 0.8813, a recall of 0.8904, an F1-measure and dice of 0.8813, and a Mean Intersection over Union of 0.8082, respectively. Comparisons with several state-of-the-art methods indicate that the developed approach in this research outperforms with greater efficiency and higher reliability.

The developed approach combines TransUnet with an integrated quantification algorithm for crack detection and quantification, performing excellently in terms of comparisons and evaluation metrics, which can provide solutions with potentially serving as the basis for an automated, cost-effective pavement condition assessment scheme.

A series of examples illustrates the application and results of the method previously given for improving the conditioning of the primary redundancies. The transformation matrix giving locally orthogonal redundancies for the parent station is used also to generate the primary self‐equilibrating stress systems for sections with different (but related) geometry and varying ring stiffness. A double‐cell cross‐section is also treated and a brief investigation shows that the general methods developed for establishing primary redundancies in the fuselage can be usefully and economically applied to certain kinds of wing structure. Preparatory to a detailed discussion of cut‐outs and modifications in the fuselage structure, the necessary general theory is collected and summarized.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.