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In order to solve the corrosion problems in the South China Sea, the purpose of this paper was to study the main influences of corrosion including temperature, H₂S content and corrosion inhibitor content in CO₂/H₂S oil field-produced water.

The corrosion products formed on the steel surface were observed and analyzed using scanning electron microscope (SEM) and X-ray diffraction (XRD).

The results indicate that temperature significantly influences the corrosion rate, which is a maximum at 70°C. The corrosion rate decreases as H₂S content increases which is less than 10 mg/L, but then it increases rapidly. The FeCO₃/Fe_xS_y protective film and a corrosion inhibition also were considered.

A mixture containing an imidazoline derivate and an organic amine can enhance the corrosion resistance of the corrosion product film.

A mixture containing an imidazoline derivate and an organic amine can enhance the corrosion product film corrosion resistance.

Imidazoline is one kind of environmentally safe agent which can be used in the ocean.

The corrosion can be controlled to a satisfactory extent in the presence of a mixture containing an imidazoline derivate and an organic amine.

The purpose of this paper is to propose a novel non-probabilistic reliability-based topology optimization (NRBTO) method for continuum structural design under interval uncertainties of load and material parameters based on the technology of 3D printing or additive manufacturing.

First, the uncertainty quantification analysis is accomplished by interval Taylor extension to determine boundary rules of concerned displacement responses. Based on the interval interference theory, a novel reliability index, named as the optimization feature distance, is then introduced to construct non-probabilistic reliability constraints. To circumvent convergence difficulties in solving large-scale variable optimization problems, the gradient-based method of moving asymptotes is also used, in which the sensitivity expressions of the present reliability measurements with respect to design variables are deduced by combination of the adjoint vector scheme and interval mathematics.

The main findings of this paper should lie in that new non-probabilistic reliability index, i.e. the optimization feature distance which is defined and further incorporated in continuum topology optimization issues. Besides, a novel concurrent design strategy under consideration of macro-micro integration is presented by using the developed RBTO methodology.

Uncertainty propagation analysis based on the interval Taylor extension method is conducted. Novel reliability index of the optimization feature distance is defined. Expressions of the adjoint vectors between interval bounds of displacement responses and the relative density are deduced. New NRBTO method subjected to continuum structures is developed and further solved by MMA algorithms.

The aim of this study is to first investigate the surface integrity of cylindrical rollers under grinding process and then design a reasonable superfinishing process that improve the anti-fatigue performance of cylindrical rollers by optimization of the surface integrity.

First, the white and dark layers produced by the grinding process is analyzed by microscope. Then, the influence of oilstone pressure on the stock removal, surface precision and crowned profile are explored. Finally, an optimal superfinishing process and a novel turnaround device are designed to improve surface integrity.

The experimental results show that as the oilstone pressure increases, the stock removal first increases and then remains stable. This hints that the stock removal of a single-time superfinishing process has an upper limit. In the current conditions, the maximum stock removal is 6 µm. Double-time superfinishing process and the turnover device can effectively eliminate the white and dark layers and improve the symmetric of roller profile. In addition, the surface precision is also improved.

The surface integrity of bearing rollers is very important to the application of industry field. The findings and the methods in the study can be helpful to improve the surface integrity of the bearing rollers.

Recently, the concept of financial technology (FinTech) has attracted extensive attention from international organisations and regulators, in particular, how to achieve a “win–win” situation between financial institutions' FinTech innovation and effective regulation has become a hot topic. This study purposes to explore the evolutionary game relationship between FinTech innovation and regulation by constructing both static and dynamic earmarking game models.

A simulation experiment was conducted using primary data obtained from a commercial bank in China.

The results of the theoretical analysis of evolutionary game models were consistent with the corresponding simulation results, proving the validity of the proposed evolutionary game models. It was also found that the dynamic earmarking game model was more stable and effective than the static earmarking game model in promoting FinTech innovation and regulation. Furthermore, when the regulators utilised a dynamic earmarking mechanism, the evolutionary path of financial institutions and regulators' behaviour strategies took the shape of a spiral and eventually converged to a central point, indicating the existence of an evolutionary stable strategy and Nash equilibrium. Finally, because the behaviour strategies of financial institutions were mainly influenced by the regulators' policies, the regulators were inspired to adjust the corresponding regulation policies on FinTech innovation.

This study bridges the knowledge gap in the existing literature on financial innovation and regulation, in particular by establishing evolutionary game models from the perspective of financial earmarking policies. Also, the case study for simulation experiments can gain a more intuitive insight into FinTech innovation and financial earmarking policies.

This research aimed to examine the current status of artificial intelligence's (AI's) integration into Chinese adult education, by analyzing the influences that AI has had on current adult education practices in China and by discussing the opportunities and challenges that adult education in China is faced with under the rapid AI development in the past 12 years.

This research employed systematic literature analysis. CNKI (China National Knowledge Infrastructure) Chinese Journals Full-text Database was used to collect scholarly publications on the use of AI in adult education in China that was published in the past decade. Data analysis included the following steps: identifying key words and phrases, detecting underlying meanings, searching for logical connections and relationships, collecting and connecting evidence to the research questions, and drawing logical and credible conclusions.

The findings indicated that AI has been gradually integrated into Chinese adult education through innovations and explorations and AI's influence is broad and profound. More specifically, the following five main themes were identified. The field's understanding of AI technology and AI's influence on adult education has evolved and become more comprehensive; AI challenges traditional Chinese adult education practices by helping to actualize personalized learning and precision education; AI transforms adult learning resource development; AI helps to turn learning environment into an open intelligent learning system; and lastly, AI urges the shift of adult educator's role in adult learning.

This study is not without limitations. Contextualized in China, this study shares the limitations with other single country studies. One such limitation is “cumulation” issue. This study should be replicated in other country contexts to further validate the generalizability of the five main themes identified in this research.

The five themes identified in this study can help understand the promises and challenges that AI brings to the field of adult education in China. These five themes can also serve as an integrated lens through which one can make sense of AI's integration into other countries' adult education practices.

This paper fulfills an identified need of understanding the current status of AI's integration into and influence on the field of adult education in China.

Prediction problems raised in uncertain environments require different solution approaches such as grey prediction models, which consider uncertainty in information and also enable the use of small data sets. The purpose of this paper is to investigate the comparative performances of grey prediction models (GM) and Markov chain integrated grey models in a demand prediction problem.

The modeling process of grey models is initially described, and then an integrated model called the Grey-Markov model is presented for the convenience of applications. The analyses are conducted on a monthly demand prediction problem to demonstrate the modeling accuracies of the GM (1,1), GM (2,1), GM (1,1)-Markov, and GM (2,1)-Markov models.

Numerical results reveal that the Grey-Markov model based on GM (2,1) achieves better prediction performance than the other models.

It is thought that the methodology and the findings of the study will be a significant reference for both academics and executives who struggle with similar demand prediction problems in their fields of interest.

The novelty of this study comes from the fact that the GM (2,1)-Markov model has been first used for demand prediction. Furthermore, the GM (2,1)-Markov model represents a relatively new approach, and this is the second paper that addresses the GM (2,1)-Markov model in any area.

Using computer technology to realize ferrographic intelligent fault diagnosis technology is fundamental research to inspect the operation of mechanical equipment. This study aims to effectively improve the technology of deep learning technology in the field of ferrographic image recognition.

This paper proposes a binocular image classification model to solve ferrographic image classification problems.

This paper creatively proposes a binocular model (BesNet model). The model presents a more extreme situation. On the one hand, the model is almost unable to identify cutting wear particles. On the other hand, the model can achieve 100% accuracy in identifying Chunky and Nonferrous wear particles. The BesNet model is a bionic model of the human eye, and the used training image is a specially processed parallax image. After combining the MCECNN model, it is changed to BMECNN model, and its classification accuracy has reached the highest level in the industry.

The work presented in this thesis is original, except as acknowledged in the text. The material has not been submitted, either in whole or in part, for a degree at this or any other university. The BesNet model developed in this article is a brand new system for ferrographic image recognition. The BesNet model adopts a method of imitating the eyes to view ferrography images, and its image processing method is also unique. After combining the MCECNN model, it is changed to BMECNN model, and its classification accuracy has reached the highest level in the industry.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0150/

Gas pipelines are facing serious risk because of the factors such as long service life, complex working condition and most importantly, corrosion. As one of the main failure reasons of gas pipeline, corrosion poses a great threat to its stable operation. Therefore, it is necessary to analyze the reliability of gas pipelines with corrosion defect. This paper uses the corresponding methods to predict the residual strength and residual life of pipelines.

In this paper, ASME-B31G revised criteria and finite element numerical analysis software are used to analyze the reliability of a special dangerous section of a gas gathering pipeline, and the failure pressure and stress concentration of the pipeline under three failure criteria are obtained. Furthermore, combined with the predicted corrosion rate of the pipeline, the residual service life of the pipeline is calculated.

This paper verifies the feasibility of ASME-B31G revised criteria and finite element numerical analysis methods for reliability analysis of gas pipelines with corrosion defect. According to the calculation results, the maximum safe internal pressure of the pipeline is 9.53 Mpa, and the residual life of the pipeline under the current operating pressure is 38.41 years, meeting the requirements of safe and reliable operation.

The analysis methods and analysis results provide reference basis for the reliability analysis of corroded pipelines, which is of great practical engineering value for the safe and stable operation of natural gas pipelines.

The purpose of this paper is to focus on the operation strategy of high-performance alliance portfolios by analyzing the effect of alliance portfolios on the performance of focal firms, using post-structuralism of social network theory and contingency theory. In detail, this paper refines alliance portfolios into three dimensions, and studies the moderating role of context on the relation between alliance portfolios and firm performance.

The empirical study was carried out with second-hand data gathered from Internal Revenue Service. In total, this paper gathered data from 506 focal firms in Zhejiang Province from 2001 to 2010 as the sample to test the hypotheses.

Based on the empirical results, the authors find the positive effect of relational dimension (weak alliance portfolios) and partner dimension (the diversity of partners) on performance. The effect of the former will become weaker with the increasing environmental dynamic, while the effect of the latter will become stronger. However, the structural dimension (alliance portfolios size) and relational dimension (new partners) have the negative effect on performance. And the negative effect will become stronger under high environmental dynamic. Moreover, the negative effect of non-local partners on performance becomes stronger when the environmental dynamic is high.

The paper reveals that with the industry transformation caused by “internet +,” companies have been required go beyond traditional dyadic alliance management perspective. That is to say, individual alliance relationship should be seen as a part of a much broader picture of alliance portfolio. As such, the framework may help companies to manage their alliance portfolios by matching high-performance alliance portfolios to the external environment to produce a synergistic effect (Lea et al., 2006; Tritos et al., 2013; Keith et al., 2014) taking the characteristics of the configuration of alliance portfolios into consideration.

The paper presents a model that explains the effect of three dimensions of alliance portfolios on the performance of focal firms in different contexts through empirical study. This paper also integrates post-structuralism of social network theory and contingency theory to enable the understanding on the configuration of alliance portfolios.

Human resources have become a key issue in relation to the strong competition between service firms. Therefore, the purpose of this paper is to explore the relationship between high-performance human resource management (HRM) within this field to firm performance, making a useful attempt to explore the “black box” of enterprise human resources management effect on firm performance.

In order to validate the relationship between high-performance HRM and firm performance, Chinese service industry samples were collected. Structural equation modeling and regression are adopted to estimate the direct effect of high-performance HRM on firm performance and the mediating role of innovation.

The results show that the impacts of high-performance HRM on firm performance are significant. Moreover, innovation plays a partial mediating role between them. Training, work analysis and employee participation has a significantly positive impact on firm performance, while effects of profit sharing, employee development and performance evaluation on enterprise performance is not significant. The results strongly support the hypothesis that innovation holds intermediary variables between high-performance HRM and firm performance.

Studying the relationship between high-performance HRM and firm performance can help Chinese enterprises more reasonable and effective learning foreign advanced management ideas and methods. And then can help Chinese enterprises to establish a high-performance HRM system that is suitable for Chinese enterprises; the research can help enterprises to identify meaningful practice of human resources management, outstanding keys, and perfect the HRM system of enterprises; research on innovation and innovative thinking is conducive to develop employees’ innovation motive, promote employee’ innovative behavior, and improve firm performance.

This paper takes innovation as a mediating variable into the model and studies the intermediary role of innovation.