Search results

This paper aims to study the impacts of groundwater seepage on artificial freezing process of gravel strata, the temperature field characteristics of the strata, and the strata process, closure time and thickness evolution mechanism of the frozen wall.

In this paper several laboratory model tests were conducted, considering different groundwater seepage rate.

The results show that there is a significant coupling effect between the cold diffusion of artificial freezing pipes and groundwater seepage; when there is no seepage, temperature fields upstream and downstream of the gravel strata are symmetrically distributed, and the thickness of the frozen soil column/frozen wall is consistent during artificial freezing; groundwater seepage causes significant asymmetry in the temperature fields upstream and downstream of the gravel strata, and the greater the seepage rate, the more obvious the asymmetry; the frozen wall closure time increases linearly with the increase in the groundwater seepage rate, and specifically, the time length under seepage rate of 5.00 m d⁻¹ is 3.2 times longer than that under no seepage; due to the erosion from groundwater seepage, the thickness of the upstream frozen wall decreases linearly with the seepage velocity, while that of the downstream frozen wall increases linearly, resulting in a saddle-shaped frozen wall.

The research results are beneficial to the optimum design and risk control of artificial freezing process in gravel strata.

This study aims to provide a series of drivers that prompt the blockchain technology (BT) adoption decisions in circular supply chain finance (SCF) and also assesses their degrees of influence and interrelationships, which leads to the construction of a theoretical model depicting the influence mechanism of BT adoption decisions in circular SCF.

This study mainly uses the technology-organization-environment (TOE) framework, which focuses on the aspects based on the nature of innovation, intra-organizational characteristics and extra environmental consideration, to identify the drivers of blockchain adoption in circular SCF context, while the significance and causality of the drivers are explained using interpreting structural models (ISMs) and the decision-making trial and evaluation laboratory (DEMATEL) method.

The findings of this study indicate that government policy and technological comparative advantage are the underlying reasons for BT adoption decisions, management commitment and financial expectations are the critical drivers of BT adoption decisions while other factors are the receivers of the mechanism.

This study provides theoretical references and empirical insights that influence the technology adoption decisions of both BT and circular SCF by practitioners.

The theoretical research contributes significantly to current research and knowledge in both BT and circular SCF fields, especially by extending the existing TOE model by combining relevant enablers from technological, organizational and external environmental aspects with the financial performance objectives of circular SCF services, which refer to the optimization of the financial resources flows and financing efficiency.

The track impedance is one of the most important parameters in designing the track circuit which is widely used in the railway signal control system to detect the presence of a train. This paper aims to calculate the ballastless track impedance by taking account of the influence of reinforcement bars.

This paper proposes a two-step decomposition approach to calculate the ballastless track impedance. The basic idea is evaluating the track impedance without the reinforcement bars by using two-dimensional (2D) finite element method (FEM), and the incremental impedance, because of the reinforcement bar, is calculated by the partial element equivalent circuit (PEEC) method.

The numerical examples show that the proposed approach can guarantee the accuracy and largely reduce the computing time, at least 20 times, compared with the direct three-dimensional (3D) FEM method.

The study provides a fast approach to calculate the ballastless track impedance. However, compared with the 3D FEM method, the results are less accurate because of the approximation and assumption adopted in the method. A future study should pay more attention to improve accuracy of the model.

A fast approach is proposed to calculate the ballastless track impedance taking account of the influence of the reinforcement bars. The computing time can be largely reduced by using the method. With the proposed approach, the influence of insulation of the reinforcement bars on track impedance can be analyzed.

This is a special issue of Chinese Management Studies and this study aims to engage with debates on innovation in China and to provide new insights for innovation research in the context of China, seeking to develop a greater understanding of the concept of “innovation with Chinese characteristics”.

This study reviews the Chinese innovation management literature in general and the selected papers in this special issue in particular and proposes two new directions for future research.

The nine papers that constitute this special issue present research on important aspects of innovation in China, ranging from the effectiveness of government subsidisation for innovation, the impact of fiscal decentralisation on innovation, the role of management behaviour in promoting (or discouraging) innovation and the effects of differing business models on innovation. These papers shed valuable new light on the theory and practice of innovation in China. The papers are discussed in the context of four primary arguments about innovation management in China identified from the broader literature in the field. These relate to the pattern of China’s innovation performance over time, the reasons for its effectiveness, the role of alliances and influences of indigenous factors. It is also shown that management of the internationalisation of innovation and of efficient internal innovation are two important directions for future research on Chinese innovation in an era of de-globalisation.

The studies presented here provide valuable contributions to theory building in innovation research, as well as some important ideas for directions of future research on innovation in China in the new era of de-globalisation.

The purpose of this paper is to gain an in-depth understanding of the research progress, hotspots and future trends in the field of functional clothing.

The records of 4,153 pieces of literature related to functional clothing were retrieved from Web of Science by using a comprehensive retrieval strategy. A piece of software, CiteSpace was used as a tool to visualize the results of specific terms, such as author, institution and keyword. By analyzing the knowledge maps with several indicators, the intellectual basis and research fronts for the functional clothing domain could then be demonstrated.

The result indicated that functional clothing was a popular research field, with approximately 500 papers published worldwide in 2020. Its main research area was material science and involved public environmental and occupational health, engineering, etc. showing the characteristic of multi-interdisciplinary. Textile Research Journal and International Journal of Clothing Science and Technology were the top two journals in this field. The USA, China, Australia, England and Germany have been active and frequently cooperating with each other. Donghua University, the Hong Kong Polytechnic University and NASA, with the largest number of publications, were identified as the main research drivers. According to the co-citation analysis, thermal stress, nanogenerator and electrospinning were the topics of most cited articles during the past 20 years.

The findings identified smart clothing and protective clothing to be the research frontiers in the field of functional clothing, which deserved further study in the future.

The outcomes offered an overview of the research status and future trends of the functional clothing field. It could not only provide scholars with convenience in identifying research hotspots and building potential cooperation in the follow-up research, but also assist beginners in searching core scholars and literature of great significance.

The purpose of this study is to predict the thermal protective performance (TPP) of flame-retardant fabric more economically using machine learning and analyze the factors affecting the TPP using model visualization.

A total of 13 machine learning models were trained by collecting 414 datasets of typical flame-retardant fabric from current literature. The optimal performance model was used for feature importance ranking and correlation variable analysis through model visualization.

Five models with better performance were screened, all of which showed R2 greater than 0.96 and root mean squared error less than 3.0. Heat map results revealed that the TPP of fabrics differed significantly under different types of thermal exposure. The effect of fabric weight was more apparent in the flame or low thermal radiation environment. The increase in fabric weight, fabric thickness, air gap width and relative humidity of the air gap improved the TPP of the fabric.

The findings suggested that the visual analysis method of machine learning can intuitively understand the change trend and range of second-degree burn time under the influence of multiple variables. The established models can be used to predict the TPP of fabrics, providing a reference for researchers to carry out relevant research.

The findings of this study contribute directional insights for optimizing the structure of thermal protective clothing, and introduce innovative perspectives and methodologies for advancing heat transfer modeling in thermal protective clothing.

At present, carbonated drinks such as cola are especially favored by the younger generation. But because of its acid, it often leads to tooth demineralization, resulting in “cola tooth”. However, the influence of cola on the corrosion resistance of passive film of TiA10 alloy restorative materials is rarely reported. The purpose of this study was to analysis the corrosion resistance, composition of the passive film of TA10 alloy in different concentrations of Cola.

The passive behavior of TA10 alloy in artificial saliva (AS) and Cola was studied by means of potentiodynamic polarization, electrochemical impedance spectroscopy, cyclic voltammetry, Mott-Schottky techniques and combined with X-ray photoelectron spectroscopy and Auger electron spectroscopy (AES) surface analysis.

With the increase of cola content, the self-corrosion current density of the alloy increases sharply, and the corrosion resistance of the passive film is the best in AS, while Rp in cola is reduced to half of that in AS. The thickness of the passive film in AS, AS +cola and cola is about 9.5 nm, 7.5 nm and 6 nm, respectively. The passive film in cola has more defects and the carrier density is 1.55 times as high as that in AS. Cola can weaken the formation process of the protected oxide, promote the formation of high valence Ti-oxides and increase the content of Mo-oxides in the passive film.

These results have important guiding significance for the safe use of the alloy in the complex oral environments.