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To explore the economical and reasonable semi-rigid permeable base layer ratio, solve the problems caused by rainwater washing over the pavement base layer on the slope, improve its drainage function, improve the water stability and service life of the roadbed pavement and promote the application of semi-rigid permeable base layer materials in the construction of asphalt pavement in cold regions.

In this study, three semi-rigid base course materials were designed, the mechanical strength and drainage properties were tested and the effect and correlation of air voids on their performance indexes were analyzed.

It was found that increasing the cement content increased the strength but reduced the air voids and water permeability coefficient. The permeability performance of the sandless material was superior to the dense; the performance of the two sandless materials was basically the same when the cement content was 7%. Overall, the skeleton void (sand-containing) type gradation between the sandless and dense types is more suitable as permeable semi-rigid base material; its gradation is relatively continuous, with cement content? 4.5%, strength? 1.5 MPa, water permeability coefficient? 0.8 cm/s and voids of 18–20%.

The study of permeable semi-rigid base material with large air voids could help to solve the problems of water damage and freeze-thaw damage of the base layer of asphalt pavements in cold regions and ensure the comfort and durability of asphalt pavements while having good economic and social benefits.

The purpose of this paper is to predict the effect of bra pad specifications on breast deformation during jumping using a finite element (FE) method. Breast deformation is a key concern for women during exercise and can be effectively controlled with sports bras. In most studies, the deformation of breasts when wearing a sports bra is measured using motion capture devices to judge their effectiveness. However, the operation of such devices is highly complex and time-consuming. Computer-aided technology is an efficient way to simulate these experiments.

In this study, the breast model was obtained using three-dimensional (3D) scanning. Assembling models were obtained for FE analysis using reverse engineering and computer-aided design (CAD) software. The breast deformation results were obtained by completing pre-processing, solving and post-processing in the FE simulation software. To extend the application of these models, pads of different sizes and thicknesses within the bra were constructed to simulate the effect of pads on breast deformation.

The calculated root mean square errors were <1%, which indicated good agreement between the FE and experimental data in all the models. Nipple deformation was always the largest in most models. The smallest deformation occurred at the superior position of breasts in all models. In addition, larger pads were not effective in reducing breast deformation; however, thicker pads were.

The method developed in this study provides an effective way to predict breast deformation in multiple positions and is convenient for designing compression bras.

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

In order to solve the problems faced by First Order Reliability Method (FORM) and First Order Saddlepoint Approximation (FOSA) in structural reliability optimization, this paper aims to propose a new Reliability-based Design Optimization (RBDO) strategy for offshore engineering structures based on Original Probabilistic Model (OPM) decoupling strategy. The application of this innovative technique to other maritime structures has the potential to substantially improve their design process by optimizing cost and enhancing structural reliability.

In the strategy proposed by this paper, sequential optimization and reliability assessment method and surrogate model are used to improve the efficiency for solving RBDO. The strategy is applied to the analysis of two marine engineering structure cases of ship cargo hold structure and frame ring of underwater skirt pile gripper. The effectiveness of the method is proved by comparing the original design and the optimized results.

In this paper, the proposed new RBDO strategy is used to optimize the design of the ship cargo hold structure and the frame ring of the underwater skirt pile gripper. According to the results obtained, compared with the original design, the structure of optimization design has better reliability and stability, and reduces the risk of failure. This optimization can also better balance the relationship between performance and cost. Therefore, it is recommended for related RBDO problems in the field of marine engineering.

In view of the limitations of FORM and FOSA that may produce multiple MPPs for a single performance function, the new RBDO strategy proposed in this study provides valuable insights and robust methods for the optimization design of offshore engineering structures. It emphasizes the importance of combining advanced MPP search technology and integrating SORA and surrogate models to achieve more economical and reliable design.

The tribological properties of muscovite and its thermal-treated products as lubricant additives in lithium grease were investigated. The effect of thermal temperature on the crystal structure and tribological properties of muscovite was studied. This study aims to explore the tribological mechanism of muscovite and optimize a proper thermal activation temperature, thus further improving the tribological properties.

The crystal structure of muscovite samples was characterized by SEM, TG-DSC, XRD and FTIR. The tribological properties of grease samples were investigated using a four-ball tribotester and the worn surface was analyzed by SEM and EDS.

The excellent tribological properties of muscovite can be ascribed to the layer structure and lubricant film formed on the worn surface. Thermal temperature at 500-600°C increases the surface activity and oxygen releasing capability, and thus favors the formation of lubricant film and accordingly further improves the tribological properties. However, the layer structure is destroyed and hard phases such as alumina and amorphous appear after thermal temperature activated beyond 1000°C, as it results in the aggravation of friction and wear.

To the authors’ knowledge, it is the first to study the effect of thermal temperature on the crystal structure and tribological properties of muscovite. The tribological mechanism of muscovite particle and its thermal-treated products was disclosed.

As an advanced calculation methodology, reliability-based multidisciplinary design optimization (RBMDO) has been widely acknowledged for the design problems of modern complex engineering systems, not only because of the accurate evaluation of the impact of uncertain factors but also the relatively good balance between economy and safety of performance. However, with the increasing complexity of engineering technology, the proposed RBMDO method gradually cannot effectively solve the higher nonlinear coupled multidisciplinary uncertainty design optimization problems, which limits the engineering application of RBMDO. Many valuable works have been done in the RBMDO field in recent decades to tackle the above challenges. This study is to review these studies systematically, highlight the research opportunities and challenges, and attempt to guide future research efforts.

This study presents a comprehensive review of the RBMDO theory, mainly including the reliability analysis methods of different uncertainties and the decoupling strategies of RBMDO.

First, the multidisciplinary design optimization (MDO) preliminaries are given. The basic MDO concepts and the corresponding mathematical formulas are illustrated. Then, the procedures of three RBMDO methods with different reliability analysis strategies are introduced in detail. These RBMDO methods were proposed for the design optimization problems under different uncertainty types. Furtherly, an optimization problem for a certain operating condition of a turbine runner blade is introduced to illustrate the engineering application of the above method. Finally, three aspects of future challenges for RBMDO, namely, time-varying uncertainty analysis; high-precision surrogate models, and verification, validation and accreditation (VVA) for the model, are discussed followed by the conclusion.

The scope of this study is to introduce the RBMDO theory systematically. Three commonly used RBMDO-SORA methods are reviewed comprehensively, including the methods' general procedures and mathematical models.

With the analysis of the causes of corruption, this study aims to investigate specific anti-corruption measures that can be implemented to reform the political system and the social climate of China.

This study examines 97 severe corruption cases of high-ranking officials in China, which occurred between 2012 and 2015. As this insinuates that both institutional and social corruption are major problems in China, the analysis delves into multiple facts of corruption, including different types, four primary underlying causes, and suggestions regarding the implementation of three significant governmental shifts that focus on investigation, prevention tactics and legal regulations.

China’s corruption is not only individual-based but also it has developed into institutional corruption and social corruption. Besides human nature and instinct, the causes of corruption can be organised into four categories, namely, social customs, social transitions, institutional designs and institutional operations. For the removed high-ranking officials, the formation of interest chains was an important underlying cause behind their corruption.

This study makes a significant contribution to the literature because this study provides a well-rounded approach to a complex issue by highlighting the significance of democracy and the rule of law as ways to regulate human behaviour to combat future corruption.

This study aims to investigate the structural characteristics, spatial evolution paths and internal driving mechanisms of the knowledge transfer (KT) network in China’s patent-intensive industries (PIIs). The authors' goal is to provide valuable insights to inform policy-making that fosters the development of relevant industries. The authors also aim to offer a fresh perspective for future spatiotemporal studies on industrial KT and innovation networks.

In this study, the authors analyze the patent transfer (PT) data of listed companies in China’s information and communication technology (ICT) industry, spanning from 2010 to 2021. The authors use social network analysis and the quadratic assignment procedure (QAP) method to explore the problem of China’s PIIs KT from the perspectives of technical characteristics evolution, network and spatial evolution and internal driving mechanisms.

The results indicate that the knowledge fields involved in the PT of China’s ICT industry primarily focus on digital information transmission technology. From 2010 to 2021, the scale of the ICT industry’s KT network expanded rapidly. However, the polarization of industrial knowledge distribution is becoming more serious. QAP regression analysis shows that economic proximity and geographical proximity do not affect KT activities. The similarity of knowledge application capacity, innovation capacity and technology demand categories in various regions has a certain degree of impact on KT in the ICT industry.

The current research on PIIs mainly focuses on measuring economic contributions and innovation efficiency, but less on KT in PIIs. This study explores KT in PIIs from the perspectives of technological characteristics, network and spatial evolution. The authors propose a theoretical framework to understand the internal driving mechanisms of industrial KT networks.

Absorptive capacity, technological collaboration and servitization are analyzed to establish ways to overcome the balance between products and services in manufacturing companies. A fresh perspective is introduced by presenting a framework for innovation strategy, moving beyond product-based R&D.

The hypotheses are tested using data on Spanish firms in the high-tech chemical and pharmaceutical industries through ordinary least squares regression analysis. The sample consists of 112 manufacturing firms included in the Spanish Survey of Business Strategies.

The results show that absorptive capacity facilitates servitization and that technological collaboration moderates the relationship between absorptive capacity and servitization. The synergies between absorptive capacity and technological collaboration for servitization are recognized from the perspective of open innovation as a way of resolving the trade-off between products and services.

Future research should introduce more sources of collaboration by broadening the value chain perspective. Other approaches to innovation may also be considered, including relationships to process innovation.

The results can provide meaningful guidance for companies to determine the key opportunities of servitization driven by absorptive capacity, and the best ways to leverage open innovation and collaboration strategies to exploit such approaches.

This research enriches theories on servitization, open innovation and innovative behavior. Open innovation strategy should be linked to greater servitization activity and should support an open service strategy. This approach is crucial for building innovation capabilities through technological collaboration.