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This paper aims to improve the anti-corrosion of oil transportation pipelines.

The authors provide a simple, efficient and inexpensive one-pot method for the novel thiadiazole derivatives synthesized using 2-substituted [1, 3, 4] thiadiazole, P₂O₅ and chloroacetic acid as materials by using XH-200A computer microwave solid-liquid phase synthesizer. The results showed that microwave heating can finish the reaction sufficiently in 20 min, and the optimal addition reaction conditions were n([1, 3, 4] thiadiazole):n(chloroacetic acid):P₂O₅ = 1:1.2:1.3. Under such conditions, the yield of the title products was 54 per cent.

The structure of the title compounds were all confirmed by Fourier transform infrared spectroscopy and ¹H nuclear magnetic resonance spectroscopy. Water-based inhibitors corrosion behaviors on the stainless steel (SS) surface in 1 mol/L HCl solution at room temperature were also studied by weight loss methods and polarization curves. The results of the curves showed that an appropriate amount of 2a (40 ppm) can improve the anti-corrosion efficiency, whereas an excessive amount of 2a (e.g. 50 ppm) may not significantly increase the anti-corrosion efficiency.

In view of continuation of our studies, this paper presents microwave-assisted one-pot synthesis of 2-substitued [1, 3, 4] thiadiazole derivatives, and its anti-corrosion performance was tested by weight loss methods and polarization curves.

Unlike previous research that primarily utilized structural equation modelling (SEM) to evaluate safety hazards in subway projects, this research aims to utilize a hybrid approach to investigate and scrutinize the key indicators of safety hazards leading to accidents, thereby hindering the progress of subway projects in China, taking into cognizance the multiple stakeholder’s perspective.

By administering a survey questionnaire to 373 highly involved stakeholders in subway projects spanning Changsha, Beijing and Qingdao, China, our approach incorporated a four-staged composite amalgamation of exploratory factor analysis (EFA), confirmatory factor analysis (CFA), covariance-based structural equation modelling (CB-SEM) and artificial neural network (ANN) to develop an optimized model that determines the causal relationships and interactions among safety hazards in subway construction projects.

The optimized model delineated the influence of individual safety hazards on subway projects. The feasibility and applicability of the model developed was demonstrated on an actual subway project under construction in Changsha city. The outcomes revealed that the progress of subway projects is significantly influenced by risks associated with project management, environmental factors, subterranean conditions and technical hazards. In contrast, risks related to construction and human factors did not exhibit a significant impact on subway construction progress.

While our study provides valuable insights, it is important to acknowledge the limitation of relying on theoretical approaches without empirical validation from experiments or the field. In future research, we plan to address this limitation by assessing the SEM using empirical data. This will involve a comprehensive comparison of outcomes derived from CB-SEM with those obtained through SEM-ANN methods. Such an empirical validation process is crucial for enhancing the overall efficiency and robustness of the proposed methodologies.

The established hybrid model revealed complex non-linear connections among indicators in the intricate project, enabling the recognition of primary hazards and offering direction to improve management of safety in the construction of subways.