Wei Liu

Due to climate change, corrosive conditions, and hydrogen-rich environments, steel energy pipelines inevitably develop a variety of defects. These deficiencies compromise pipeline safety and reliability, and neglecting them may result in pipeline leaks, fractures, and even potentially catastrophic explosions. Although a considerable body of literature reviews the effects of metal-loss defects like corrosion and cracks on pipeline safety and reliability, the impact of geometric deformation, like dents, lacks a comprehensive review. This work employs a hybrid systematic literature review (SLR) and bibliometric analysis (BA) to investigate the current research status of pipeline dent assessment. Four questions are answered: (1) What are the publication distribution characteristics, active journals, production organizations, and production authors related to research on pipeline dents? (2) What criteria have been employed for evaluating the pipeline dent? (3) From what perspective has the integrity of dented pipelines been assessed, and what research approaches have been used? (4) What are the future challenges and prospects of pipeline dent studies? The findings demonstrate that depth-, strain-, and damage-based evaluation criteria are widely employed to assess pipeline dents, each with merits and limitations. Despite the simplicity and ease of use of depth- and strain-based criteria, they are prone to underestimation flaws. In contrast, damage-based criteria, which consider multiple factors, are limited by their complexity and high computational resource requirements. The reliability of dented pipelines is predicted with remaining strength, fatigue life, and failure pressure using theoretical modeling, experimental testing, numerical simulation, or a combination of these methods. Future dent studies should involve refining numerical models, full-scale testing under varied loading conditions, and integrating advanced sensing techniques for real-time inspection.

The natural gas sector, as a pivotal transition fuel, is fundamentally constrained by the “Energy Trilemma”—the intertwined and often competing goals of energy security, affordability, and sustainability. Current research predominantly focuses on the demand side, leaving a significant gap in understanding the synergistic dynamics within production regions, which are critical to resolving this trilemma at its source. To address this gap, this study constructs a “Safety–Economy–Green” (S-E-G) evaluation framework aligned with the trilemma’s dimensions. Utilizing panel data (2011–2021) from four major Chinese natural gas production regions (Sichuan, Chongqing, Shaanxi, and Shanxi). By integrating the Entropy Weight Method, a Coupling Coordination Model, and Kernel Density Estimation, it delineates the system’s synergistic dynamics from both temporal and regional perspectives. The key findings are as follows: (1) Significant disparities and polarization are observed in the S and G dimensions, while the E dimension shows a narrowing gap, with its peak height increasing by 177.8% and bandwidth shrinking by 64.2%. G has emerged as a constraint on overall system coupling coordination. The persistently high coupling degree—rising from 0.87 in 2011 to 0.97 in 2021 while consistently exceeding the coordination degree, which increased from 0.45 to 0.62—underscores the continued need for improvement in synergistic development. (2) The coupling coordination degree of the S-E-G system underwent a three-stage evolution: rapid improvement (2011–2013, from 0.36 to 0.58 at 7.3% annually), fluctuating adjustment (2014–2017, between 0.58 and 0.66), and finally high-level stability (2018–2021, stabilizing at 0.76–0.80). (3) Obvious regional differentiation exists: Sichuan achieved a moderate level of 0.76 by 2021, Shaanxi maintained primary coupling coordination (0.6–0.7), while Chongqing and Shanxi remained marginal, fluctuating between 0.4 and 0.6. Enhancing subsystem coordination and implementing differentiated pathways are therefore essential for these regions’ sustainable development. The study suggests promoting the sustainable development of natural gas production regions by enhancing subsystem coordination and exploring differentiated pathways, thereby providing practical guidance for the energy transition of resource-based regions.

Dents are a common geometric deformation defect in pipelines where the dented section becomes susceptible to local buckling, significantly threatening the integrity and reliability of the pipeline. This paper developed a novel finite element (FE) machine learning (ML)-based approach to analyze and predict the critical buckling moment (CBM) of dented pipelines under combined internal pressure and bending moment (BM) loading. By quantifying the parametric effects on CBM and developing a dataset, an Extreme Learning Machine (ELM) framework through hybrid algorithm integration, combining Bald Eagle Search (BES), Lévy flight, and Simulated Annealing (SA), was proposed to achieve highly accurate CBM predictions. This study offers valuable insights into evaluating the buckling resistance of dented pipelines subjected to complex loading conditions.

Pipeline safety faces a prevalent threat in mountainous areas due to landslides. The advent of landslides introduces the risk of pipeline leaks or ruptures, posing a significant threat to the environment, with the potential for casualties. Throughout the occurrence of landslides, uncertainties abound, yet few studies have addressed the incorporation of uncertainties in assessing pipeline safety. This work proposes a novel hybrid approach to the safety assessment for pipelines under landslides. The use of finite element analysis (FEA) models the pipeline under the action of landslides. The numerical outcomes, combined with unascertained measure theory (UMT), develop a multi-indicator unascertained measure (UM) matrix. Random forest (RF) algorithm is employed to determine the weight of indicators in the matrix. The hybrid application of set pair theory and the UM evaluation vector finally determine the pipeline safety degree and level. The proposed methodology has been well-validated through a case study on an in-service pipeline. The results indicate that the case pipeline safety degree is 2.777, 2.132, 3.132, 3.904, and 2.240, respectively. The corresponding safety level is III, II, III, IV, and II, respectively, which is consistent with the pipeline's actual condition. Different from the conventional safety assessment approach, the proposed methodology demonstrates the enhanced effectiveness, facilitating a more precise evaluation of the pipeline's safety condition.