Search results

When hydrogen evolution reaction occurs on a metal surface, on the one hand, the generated hydrogen atom may penetrate into the metal that causes the hydrogen embrittlement failure of materials; on the other hand, the hydrogen generation may increase the local pressure in the coating and cause coating blistering. The purpose of this study is to study the effect of NaCl concentration and pH on hydrogen evolution reaction of X60 steel.

A cathodic polarization curve 257E-2V vs OCP and EIS was obtained by conventional three-electrode system in different NaCl concentrations, 257E3.5 and pH. Second, various parameters such as hydrogen evolution, over-potential current–density polarization resistance and capacitance of double electric layer were obtained based on fitting of the experimental data. Finally, the reaction mechanism was determined by Tafel curves.

It was concluded that in different NaCl concentrations, diffusion layer induced by concentration polarization affects the diffusion process of H+ ions, which makes over-potential increase. Under great effect of concentration polarization, the reaction is different in acid and alkaline environments, and the dielectric layer shows the characteristic of meta-alkaline adsorption, which makes difference in mechanism.

This research not only has theoretical significance but also gains utilization prospect. Ultimately, this research could be applied to clear hydrogen evolution process and protect long-distance pipeline against delamination.

Surveillance is the emerging concept in the current technology, as it plays a vital role in monitoring keen activities at the nooks and corner of the world. Among which moving object identifying and tracking by means of computer vision techniques is the major part in surveillance. If we consider moving object detection in video analysis is the initial step among the various computer applications. The main drawbacks of the existing object tracking method is a time-consuming approach if the video contains a high volume of information. There arise certain issues in choosing the optimum tracking technique for this huge volume of data. Further, the situation becomes worse when the tracked object varies orientation over time and also it is difficult to predict multiple objects at the same time. In order to overcome these issues here, we have intended to propose an effective method for object detection and movement tracking. In this paper, we proposed robust video object detection and tracking technique. The proposed technique is divided into three phases namely detection phase, tracking phase and evaluation phase in which detection phase contains Foreground segmentation and Noise reduction. Mixture of Adaptive Gaussian (MoAG) model is proposed to achieve the efficient foreground segmentation. In addition to it the fuzzy morphological filter model is implemented for removing the noise present in the foreground segmented frames. Moving object tracking is achieved by the blob detection which comes under tracking phase. Finally, the evaluation phase has feature extraction and classification. Texture based and quality based features are extracted from the processed frames which is given for classification. For classification we are using J48 ie, decision tree based classifier. The performance of the proposed technique is analyzed with existing techniques k-NN and MLP in terms of precision, recall, f-measure and ROC.

The entrepreneurial ecosystem within Chinese vocational colleges offers a unique platform to investigate the interplay between entrepreneurial passion, education and intention. This study aims to assess the effect of entrepreneurial education on alertness, passion and mindset, in turn, on entrepreneurial orientation and intentions. In addition, the study examines the mediating role of the entrepreneurial mindset between entrepreneurial passion and education; and to identify the moderating effect of entrepreneurial self-efficacy between entrepreneurial orientation and intentions.

Using a cross-sectional methodology based on self-reported data from students across various Chinese vocational colleges, the study used a quantitative method to derive its findings.

The results highlighted a strong positive effect of entrepreneurial education on passion, mindset and alertness. The study also found that an increased emphasis on entrepreneurial education fostered a proactive entrepreneurial orientation, a significant predictor of entrepreneurial intentions. The entrepreneurial mindset played a pivotal mediating role, enhancing the direct effects observed. Moreover, students with higher entrepreneurial self-efficacy exhibited a more substantial inclination towards entrepreneurial intentions, further buttressed by their orientation.

This study underscores the critical role of fostering passion, education and self-efficacy in cultivating entrepreneurial intentions among students in Chinese vocational colleges, offering valuable theoretical and managerial implications for educators and policymakers alike.

To construct a scientific and reasonable indicator system, it is necessary to design a set of standardized indicator primary selection and optimization inspection process. The purpose of this paper is to provide theoretical guidance and reference standards for the indicator system design process, laying a solid foundation for the application of the indicator system, by systematically exploring the expert evaluation method to optimize the index system to enhance its credibility and reliability, to improve its resolution and accuracy and reduce its objectivity and randomness.

The paper is based on system theory and statistics, and it designs the main line of “relevant theoretical analysis – identification of indicators – expert assignment and quality inspection” to achieve the design and optimization of the indicator system. First, the theoretical basis analysis, relevant factor analysis and physical process description are used to clarify the comprehensive evaluation problem and the correlation mechanism. Second, the system structure analysis, hierarchical decomposition and indicator set identification are used to complete the initial establishment of the indicator system. Third, based on expert assignment method, such as Delphi assignments, statistical analysis, t-test and non-parametric test are used to complete the expert assignment quality diagnosis of a single index, the reliability and validity test is used to perform single-index assignment correction and consistency test is used for KENDALL coordination coefficient and F-test multi-indicator expert assignment quality diagnosis.

Compared with the traditional index system construction method, the optimization process used in the study standardizes the process of index establishment, reduces subjectivity and randomness, and enhances objectivity and scientificity.

The innovation point and value of the paper are embodied in three aspects. First, the system design process of the combined indicator system, the multi-dimensional index screening and system optimization are carried out to ensure that the index system is scientific, reasonable and comprehensive. Second, the experts’ background is comprehensively evaluated. The objectivity and reliability of experts’ assignment are analyzed and improved on the basis of traditional methods. Third, aim at the quality of expert assignment, conduct t-test, non-parametric test of single index, and multi-optimal test of coordination and importance of multiple indicators, enhance experts the practicality of assignment and ensures the quality of expert assignment.

The purpose of this study is to elucidate the effects of electric-arc-induced ablation on the corrosion behavior of pipeline steel in neutral and high pH environments.

Electrochemical testing, an atmospheric-pressure immersion experiment and various techniques (e.g. scanning electron microscopy, energy dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy) were used to examine the effects of electric-arc-induced ablation on the corrosion behavior of pipeline steel in neutral and high pH environment.

Electric-arc-induced ablation occurred preferentially in areas of inclusion. The corrosion resistance of an ablation pit was lower than that of non-ablation areas. In the neutral soil solution, general corrosion was the dominant corrosion that affected pipeline steel; the effect of ablation was small but pitting corrosion could still be induced. In a high pH environment, the samples without ablation were passivated, whereas the samples with ablation pits could not be passivated; the ablation pits were likely to develop pitting corrosion.

Electric-arc-induced ablation can reduce the corrosion resistance of pipeline steel under high-voltage direct current interference.

The purpose of this paper is to provide high-efficiency and high-power hybrid energy source for an urban electric vehicle. A power management strategy based on fuzzy logic has been introduced for battery-ultracapacitor (UC) energy storage.

The paper describes the design and construction of on-board hybrid source. The proposed energy storage system consists of battery, UCs and two DC/DC interleaved converters interfacing both storages. A fuzzy-logic controller (FLC) for the hybrid energy source is developed and discussed. Control structure has been tested using a non-mobile experimental setup.

The hybrid energy storage ensures high-power ability. Flexibility and robustness offered by the FLC give an easy accessible method to provide a power management algorithm extended with additional input information from road infrastructure or other vehicles. In the presented research, it was examined that using information related to the topography of the road in the control structure helps to improve hybrid storage performance.

The proposed control algorithm is about to be validated also in an experimental car.

Exploratory studies have been provided to investigate the benefits of energy storage hybridization for electric vehicle. Simulation and experimental results confirm that the combination of lithium batteries and UCs improves performance and reliability of the energy source. To reduce power impulses drawn from the battery, power management algorithm takes into consideration information on slope of a terrain.

The purpose of this paper is to consider a nonlinear problem of minimizing the cost of providing reliable systems. The authors assume that the system consists of several components in series, and for each such component, the cost of the component increases exponentially with its reliability.

In order to solve this nonlinear optimization problem, the authors propose two approaches. The first approach is based on the concept of adjusting the reliability of a pair of components to minimize the cost of the system. The authors call this procedure as reliability adjustment routine (RAR). Proofs of optimality and convergence for the proposed model are also provided. The second approach solves the problem by using a Lagrangian multiplier. A procedure is developed to obtain the maximum step size to achieve the desired optimal solution in minimum iterations. Proposed approaches are efficient and give exact solutions.

Proposed methods enable a decision maker to allocate reliability to the components in series while minimizing the total cost of the system. The developed procedures are illustrated using a numerical example. Although an exponential relationship between the component cost and reliability is assumed, this can be extended to various other nonlinear distributions.

This cost optimization problem, subject to system component reliability values, assumes the near practical nonlinear pattern of cost vs reliability. Such problems are complex to solve. The authors provide a unique approach called RAR to solve such convoluted problems. The authors also provide an approach to solve such problems by using a Lagrangian multiplier method. Various proofs have been worked out to substantiate the work.