Search results

This paper aims to propose a diverless weld bead maintenance welding technology to prevent the leakage of subsea oil and gas pipeline and solve the key problems in the maintenance of subsea pipeline.

Based on the analysis of the cross-section of the fillet weld, the multi-layer and multi-pass welding path planning of the submarine pipeline sleeve fillet weld is studied, and thus a multi-layer and multi-pass welding path planning strategy is proposed. A welding seam filling method is designed, and the end position of the welding gun is planned, which provides a theoretical basis for the motion control of the maintenance system.

The trajectory planning and adjustment of multi-layer and multi-pass fillet welding and the motion stability control of the rotating mechanism are realized.

It provides the basis for the prototype design of the submarine pipeline maintenance and welding robot system, and also lays the foundation for the in-depth research on the intelligent maintenance system of submarine pipeline.

The maintenance of diverless subsea pipeline is a new type of maintenance method, which can solve the problem of large amount of subsea maintenance work with high efficiency.

The purpose of this paper is to characterize and understand the effects of polymer binder, thixotropic agent, solvent and organic medium content on the rheological properties of silver pastes for screen printing front electrode films of solar cells.

Dispersions of silver particles (surface modified with oleic acid) in ethyl cellulose (EC) polymer solutions with and without thixotropic agent were prepared, and yield stress values were measured by setting shear stress to characterize the inter-particle interaction strength of pastes. Steady-state flow, three interval thixotropy shear test and oscillatory measurements were conducted to study the effect of EC polymer and thixotropic agent on viscosity, structure rebuilding and viscoelastic properties of electrode pastes. The effect of solvent was studied by investigating the steady viscosity of cellulose acetate butyrate (CAB) polymer solutions and Ag dispersions.

Weak flocculation network of silver particles was produced because of depletion flocculation. Besides the interaction between thixotropic agent micelles, EC polymer also has a significant interaction with thixotropic agent. Merely increasing EC polymer or thixotropic agent content is not the best way to prevent the layer printed from laying down. The effect of solvent on the viscosity of paste is mainly attributed to the difference of hydromechanics radius and configuration of CAB polymer in solvents. With the increase of organic medium content, the properties of electrode pastes were converted from rigidity to flexibility.

It is still a challenge to obtain high-quality front electrode films for crystalline silicon solar cells by screen printing, because of the difficulty in reducing shadowing losses while ensuring a low series resistance and high filling factor. The paste rheological properties are the key properties related to the paste’s passing ability through the meshes and resistance of paste spreading on the substrate. Organic medium as an important component of the paste is acknowledged to be used to tailor the paste’s rheological properties and have a great role in screen printing.

This paper aims to propose a train timetable rescheduling (TTR) approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.

Firstly, a single-train trajectory optimization (STTO) model is constructed based on train dynamics and operating conditions. The train kinematics parameters, including acceleration, speed and time at each position, are calculated to predict the arrival times in the train timetable. A STTO algorithm is developed to optimize a single-train time-efficient driving strategy. Then, a TTR approach based on multi-train tracking optimization (TTR-MTTO) is proposed with mutual information. The constraints of temporary speed restriction (TSR) and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train. The multi-train trajectories at each position are optimized to generate a time-efficient train timetable.

The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF. The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay (TTD). As for the TSR scenario, the proposed TTR-MTTO can reduce TTD by 60.60% compared with the traditional TTR approach with dispatchers’ experience. Moreover, TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.

With the cooperative relationship and mutual information between train rescheduling and control, the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.

This paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.

The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.

This paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

To optimize train operations, dispatchers currently rely on experience for quick adjustments when delays occur. However, delay predictions often involve imprecise shifts based on known delay times. Real-time and accurate train delay predictions, facilitated by data-driven neural network models, can significantly reduce dispatcher stress and improve adjustment plans. Leveraging current train operation data, these models enable swift and precise predictions, addressing challenges posed by train delays in high-speed rail networks during unforeseen events.

This paper proposes CBLA-net, a neural network architecture for predicting late arrival times. It combines CNN, Bi-LSTM, and attention mechanisms to extract features, handle time series data, and enhance information utilization. Trained on operational data from the Beijing-Tianjin line, it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.

This study evaluates our model's predictive performance using two data approaches: one considering full data and another focusing only on late arrivals. Results show precise and rapid predictions. Training with full data achieves a MAE of approximately 0.54 minutes and a RMSE of 0.65 minutes, surpassing the model trained solely on delay data (MAE: is about 1.02 min, RMSE: is about 1.52 min). Despite superior overall performance with full data, the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals. For enhanced adaptability to real-world train operations, training with full data is recommended.

This paper introduces a novel neural network model, CBLA-net, for predicting train delay times. It innovatively compares and analyzes the model's performance using both full data and delay data formats. Additionally, the evaluation of the network's predictive capabilities considers different scenarios, providing a comprehensive demonstration of the model's predictive performance.

This study aims to examine the effects of technology-, organisation- and environment-readiness, smart economic development, change valence, social cohesion and quality of life on citizenship in the context of smart cities.

The study employed a customized questionnaire which was completed by 280 residents of China’s first-tier cities. This study tested the framework using the partial least squares structural equation modelling (PLS-SEM) technique.

The results indicated that smart economy development, social cohesion, change valence, technological readiness, organizational readiness and environmental readiness have a significant impact on the quality of life. Quality of life has a positive impact on citizenship.

This study adds new insights to smart city academic discussions. The study addresses a critical gap identified in existing literature which urges the need for a balance between user-centric, organization-centric and technology-centric approaches. It offers a fresh perspective on how the smart economy, social cohesion and readiness factors are interlinked. These elements together shape urban living experiences. For policymakers and urban planners, our findings provide clear guidance. They highlight the complex dynamics that must be considered to build more unified, inclusive and sustainable smart cities.

We are the first to investigate the relationship between seasoned equity offerings (SEOs) and anchoring on historical high prices in China.

We use the ratio of the recent closing price to its historical high in the previous 12–60 months (anchoring-high-price ratio) to study its impact on the market timing of SEOs.

Empirical results show that the anchoring-high-price ratio significantly and positively affects the probability of additional stock issuances. Contrary to the USA market, the Chinese stock market reacts negatively to the SEOs at historical highs. Moreover, the anchoring-high-price ratio exacerbates the negative effect of announcements and leads to long-term underperformance. Finally, we investigate the impact of the anchoring-high-price ratio on a company’s capital structure, showing that the additional issuance anchoring on historical highs reduces the company’s leverage ratio in the long run. Overall, our findings support the anchoring theory and can help understand better the anchoring behavior of managers and the company’s decision on additional stock issuances.

We are the first to use the anchoring-high-price ratio to study the timing of SEOs. We find that the anchoring-high-price ratio positively affects the probability of SEOs. Unlike the USA, the Chinese stock market reacts negatively to SEOs at high prices. SEOs anchoring on historical highs reduce a firm’s leverage ratio in the long run. Finally, our results support the anchoring theory.

The purpose of this paper is to explore and examine, in a systematic manner, possible preventive measures that commercial parties can take in order to prevent or reduce documentary letter of credit (L/C) fraud in international transactions.

In the context of international transactions, considering documentary L/C fraud as a risk, the paper searched preventive measures that different parties involved can adopt, from both business perspective and legal perspective.

The paper provides a number of specific measures which buyers, sellers, and banks in international L/C transactions can take in business to reduce L/C fraud. The option of banks providing additional services of checking further the validity or authenticity of some documents under the L/C, by charging additional prices, has reflected the needs of some business parties. However, this is proposed to be optional rather than compulsory for banks. The lawyers can also play an important role by adopting preventive legal mentality to help and provide advice to different parties in applying the preventive and proactive approach. More importantly, the author recommends that buyers or sellers maintain close cooperation with their banks and lawyers in implementing preventive and proactive measures.

The paper can be a helpful source of advice for business enterprises likely to be involved in international documentary L/C transactions.

This paper fulfils the gap of a holistic study on how to prevent international documentary letter of credit fraud.

This paper aims to compare the Greek and Chinese rhetorical traditions and explore their influences on today’s business and marketing communication across relevant cultures. In particular, it uses the Aristotelian persuasive orientations as reference points to introduce the Chinese rhetoric, and interpret cultural differences in persuasion from a historical and sociocultural perspective. It has been found that Greek and Chinese rhetoric and persuasion were developed to meet the needs of the social and cultural environments and this rule still applies to today’s business communication. The logical approach has been emphasised in the English rhetorical tradition while both qing (emotional approach) and li (logical approach) are the focus of persuasion in the Chinese tradition. This difference is also the root of cultural differences in modern business communication. Findings from both English and Chinese texts and data are examined to substantiate our focal argument.