The problem of sand production in oil wells during oil extraction has seriously affected the stability and increase in oil and gas production. Despite the excellent sand control performance and technical advantages demonstrated by the expandable sand screen (ESS), its frequent collapse failure has disrupted the normal production of oil wells. Therefore, a systematic study on the collapse strength of the ESS was conducted. Through postexpansion tensile tests, the hardening law of 316L material under different expansion ratios was obtained. A three-dimensional finite-element model of the ESS was established. The influence of material hardening, nonuniform external pressure, and slot structure parameters on the collapse strength of the ESS was analyzed. The results show that (1) the higher the expansion rate of 316L material, the more significant the plastic hardening phenomenon becomes. By considering the plastic hardening of the material, waste can be avoided in the design and selection of the base pipe. (2) The pressure required for the slots of the expanded base pipe to close completely depends on the maximum external pressure and is not affected by the size of the pressure difference. The greater the degree of uniform external pressure, the faster the base pipe collapses, and the more severe the collapse becomes. (3) It is recommended that the slot length be designed as 100 mm. The slot width should be less than 5 mm, and it is recommended that the slot width be designed as 4 mm. The optimal slot arrangement is staggered slots. The research results can provide a theoretical basis for the structural optimization and collapse strength mechanism of expandable sand screens.

Drainage infrastructure, particularly reinforced concrete pipes, faces significant degradation due to microbially induced concrete corrosion in sulfuric acid environments, leading to substantial economic and safety concerns. However, existing research predominantly relies on small-scale specimens, and current failure prediction models for full-scale pipes lack comprehensive experimental validation, thereby hindering accurate service life prediction and the development of practical design guidelines. This study addresses these critical gaps by conducting full-scale experimental investigations into the mechanical performance and deformation characteristics of reinforced concrete pipes exposed to a 5% sulfuric acid environment over durations of 0, 30, 60, and 90 days. Utilizing a specialized sulfuric acid corrosion setup and a three-edge bearing test system, our findings reveal that sulfuric acid corrosion induces significant phase-dependent and nonlinear changes in pipe performance. We observe a complex evolution of crack development, transitioning from initial uniform circumferential cracking to a coexistence of mixed and longitudinal cracks, ultimately forming an interconnected network. Crucially, the failure mode shifts from being dominated by structural integrity to material degradation, with the inner ring deteriorating more rapidly. Pearson correlation analysis further demonstrates a strong positive relationship between elliptical deformation and load-bearing capacity, reflecting a significant weakening of pipe stiffness and durability. By employing full-scale experiments and simulating realistic corrosion conditions, this research provides a robust reference for the reliability assessment and service life prediction of concrete pipe structures in sulfuric acid environments, offering valuable insights for engineering design optimization and maintenance strategies. Crucially, these findings offer a direct scientific basis for calibrating predictive models and enhancing the practical engineering standards used in pipeline design and maintenance.

A large number of flexible pipeline structures exist under roadways. When the cover thickness over the pipeline is limited, effects of live loads can be more pronounced on the structure, especially when a relatively heavy vehicle is moving at low speeds or comes to stop over it. There is a need to address the topic of this paper because only a small number of publications made about buried flexible pipes have paid attention to their performances under static live loads. In this paper, first a few published field tests are examined to find out how shallowly buried flexible pipes respond differently to live loads than to the dead loads. In the second part of the paper, new equations are derived so that the deflection responses of a shallowly installed flexible pipe can be estimated under a static live load. The new equations fill a gap that currently exists in the AASHTO LRFD Bridge Design Specifications. The new deflection equations produced mixed results when their estimates were compared to the field test pipe deflection measurements reported in the literature. This may be partially because of the way the loading tests were carried out in the field. The new equations point out the importance of having a stiff layer above the pipe when the cover thickness is very limited.

The length of parallel pipelines for transporting petroleum is continuously increasing. Leaks or explosions in these pipelines can cause devastating consequences. Therefore, this paper focuses on oil pool fires caused by pipeline leaks, specifically examining a segment of the China-Myanmar parallel pipelines. Numerical simulations of fire and explosion scenarios are conducted to investigate the impacts of oil leakage and fire accidents on the adjacent natural gas pipeline. The results indicate that oil vapor concentration and the size of leakage apertures are the two most critical factors influencing such accidents. Risk levels are ranked from highest to lowest as thermal radiation intensity, temperature difference, and explosion shock wave. Notably, thermal radiation poses the greatest hazard, with its risk level potentially reaching Level I. Finally, this paper recommends that the safety distance determined by thermal radiation be given special consideration during the design phase of parallel pipelines.

To effectively manage the elevated pressure and flow rates encountered in the initial stages of shale gas extraction, throttling often is employed to modulate these parameters and mitigate bottom-well pressure losses. A mixed-integer nonlinear programming (MINLP) model is proposed that synergistically integrates a correlation mechanism between wellhead pressure and production rate and throttling disturbance constraints with shale gas system pressurization optimization. The model, guided by a cost-minimization objective function, incorporates pipeline pressure, flow rate limitations, compressor specifications, and throttling disturbance constraints. Empirical validation, based on a 2-year timeline, indicated that the optimization strategies produced by the coupled throttling disturbance framework offer superior and more economically efficient solutions than conventional methods. Compared with the actual pressurization scenario, the optimized scheme operated with 245 kW less power, the daily volume of gas handled by the compressor was reduced by 370,000 m3, and the compressor unit cost was CNY 266×104 less, and it centralized pressurization locations. This work demonstrates that the integrated throttling disturbance and correlation mechanism between pressure and production rate serves as a robust tool for optimizing pressurization schemes in shale gas operations.

Welding of long-distance pipelines is a crucial step to ensure the safe operation of pipelines. In mountainous regions, the actual welding efficiency is often significantly lower than the theoretical efficiency, and the lack of standardized guidelines for on-site selection leads to a general preference for more mature semiautomatic welding combinations. This tendency hinders the broader adoption of automated welding technology for pipelines. To address this issue, we established cost functions for individual welds and total welding costs, clarifying the proportion of labor, equipment, and material costs in different welding methods. We developed a total welding cost function for various welding methods, forming an economic welding matrix to recommend welding techniques suitable for different terrains and construction segment lengths, providing a reference for selecting on-site welding methods. Additionally, an economic model for welding natural gas pipelines in mountainous areas was established from the perspective of engineering economics. This model not only considers the direct costs of the welding process but also reflects the impact of terrain and project scale on economic efficiency, offering guidance for selecting welding methods in complex environments. Finally, the accuracy of the economic model was validated using a specific construction segment.

The CorLAS model is widely used in the pipeline industry for predicting the failure pressure of pipelines with axial surface cracks, primarily due to its low computational and moderate prediction accuracy compared to other alternative models. Despite its popularity, recent studies have reported that the CorLAS model is associated with a high coefficient of variation (CoV) of model error, which can undermine the confidence in reliability-based assessment of burst pressure of pipelines using CorLAS. Recently, machine learning techniques, such as artificial neural networks (ANN), have been successfully used to develop predictive models based on large datasets. Experimental burst testing involves significant costs and complex setups and is subject to strict regulatory constraints. As a result, publicly available datasets are limited, making developing ANN models based on experimental data infeasible. To address this issue, a sufficiently large database is generated using the extended finite-element method (XFEM), which has proven to be a powerful and effective approach to simulating crack growth. This study develops a hybrid ANN-XFEM predictive framework for failure pressure estimation in pipelines with axial cracks, improving upon existing empirical models such as CorLAS. A synthetic dataset of 498 XFEM simulations was generated, covering four pipeline grades (X52, X60, X65, and X80) with varying diameter-to-thickness ratios (D/t=40–90), crack depths (a/t=0.4–0.8), and crack lengths (L2/Dt=1–18). The trained ANN model achieved a mean absolute error of 0.43 and a CoV of 4.76%, significantly outperforming CorLAS (CoV=14%). These findings offer a computationally efficient alternative to full-scale burst testing and high-fidelity XFEM simulations, enabling real-time integrity assessment and predictive maintenance for pipeline operators.

Deterioration due to pitting corrosion is one of the main causes of cast iron and steel pipe failure; however, few studies report on how corrosion pit geometry influences the mechanical response of buried pipelines. In this paper, a series of four-point bending tests were used as proxies for buried pipe tests to investigate the strain distributions around simulated corrosion pits. Three corrosion pit geometries were used to investigate the influence of pit geometry on local strain distributions at the invert of the pipe arising from longitudinal bending: (1) a cylindrical perforation all the way through the pipe wall; (2) a cylindrical pit extending partially through the pipe wall and having a flat bottom; and (3) a spherical pit extending partially through the pipe wall. Distributed fiber-optic strain sensors were used to measure the longitudinal strains along the crown, springlines, and invert of the pipe and circumferential strains around the simulated corrosion pits. Different longitudinal strain distributions were observed across the top of these pits on the exterior surface of the pipe and under the pit on the interior surface. The maximum longitudinal tensile strains measured on the two samples with simulated pits that partially penetrated the pipe wall were about 2.5 times higher than an intact specimen. For the circumferential strains, comparisons were made to strains calculated using the Kirsch solution for a flat plate with a circular hole. Although the calculated values of maximum tensile hoop strain were similar to the experimental measurements obtained from the perforated samples, the distributed strain measurements around the pits were different from the calculated distributions. This is because the traverse strains (the strains 90° from the longitudinal direction at the invert of the pipe) near the pit are more compressive than those assumed when imposing uniaxial stress or uniaxial strain conditions in the Kirsch solution; when biaxial strain fields are imposed in the Kirsch theory, as obtained from three-dimensional numerical analyses, the closed-form solution provides effective estimates of stress and strain around perforations. Finally, comparisons were made to strain measurements from a buried pipe subjected to longitudinal bending, and these indicate that four-point bending tests can capture critical peak tensile strains that would lead to failure, but not the full distributed strain profile.

This paper proposes a novel pipeline burst pressure prediction model, transformer–bidirectional long short-term memory (BiLSTM)–Gaussian noise (GN) model (TBGN), to address the complex nonlinear coupling of elastic-plastic deformation and fracture damage in pipelines with axial cracks on the external surface. The study collected 180 full-scale burst test data sets for cracked pipes to build a comprehensive failure database. Based on the transformer-BiLSTM algorithm and the failure experimental database, an intelligent predictive model for pipeline burst pressure was developed. This model is integrated with the GN model to compute the optimal safety factor through a multidimensional performance evaluation system, balancing the trade-off between predictive risk and excessive conservatism. The resulting framework is termed the TBGN model. The performance of the TBGN model is thoroughly evaluated in comparison with the GN model and several established failure assessment models. Results indicate that the TBGN model outperforms its counterparts in various metrics. Its prediction accuracy (PA) follows a normal distribution, with a concentrated spread. In addition, its key indicators, such as the coefficient of variation (0.113) and correlation coefficient (0.012), reveal minimal dispersion in the prediction results, with no significant correlation between PA and the experimental burst pressure. The PA values predominantly fall within the 0.6 to 1 range, ensuring a robust safety margin without excessive conservatism. Furthermore, the mean PA deviates from 1 by only 0.179, confirming the model’s high accuracy. Overall, the TBGN model achieves a total performance score of 0.928, which is 110.39% higher than the classical models. The TBGN model is capable of effectively assessing the coupled failure resulting from the interaction between fracture and yield failure, thereby providing an accurate and reliable prediction of the burst pressure for pipelines exhibiting axial cracks on their external surface.