Search Results (232)

In cybersecurity, constructing an accurate knowledge graph is vital for discovering key entities and relationships in security incidents buried in vast unstructured threat reports. Traditional knowledge-graph construction pipelines based on handcrafted rules or conventional machine learning models falter when the data scale and linguistic variety grow. GraphRAG, a retrieval-augmented generation (RAG) framework that splits documents into fixed-length chunks and then retrieves the most relevant ones for generation, offers a scalable alternative yet still suffers from fragmentation and semantic gaps that erode graph integrity. To resolve these issues, this paper proposes SC-LKM, a cybersecurity knowledge-graph construction method that couples the GraphRAG backbone with hierarchical semantic chunking. SC-LKM applies semantic chunking to build a cybersecurity knowledge graph that avoids the fragmentation and inconsistency seen in prior work. The semantic chunking method first respects the native document hierarchy and then refines boundaries with topic similarity and named-entity continuity, maintaining logical coherence while limiting information loss during the fine-grained processing of unstructured text. SC-LKM further integrates the semantic comprehension capacity of Qwen2.5-14B-Instruct, markedly boosting extraction accuracy and reasoning quality. Experimental results show that SC-LKM surpasses baseline systems in entity-recognition coverage, topology density, and semantic consistency. Full article

This study analyzed the probability of damage in heat transport pipelines buried in urban areas using pipeline attribute information and damage history data and developed an AI-based predictive model. A dataset was constructed by collecting spatial and attribute data of pipelines and defining basic units according to specific standards. Damage trends were analyzed based on pipeline attributes, and correlation analysis was performed to identify influential factors. These factors were applied to three machine learning algorithms: Random Forest, eXtreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). The model with optimal performance was selected by comparing evaluation indicators including the F2-score, accuracy, and area under the curve (AUC). The LightGBM model trained on data from pipelines in use for over 20 years showed the best performance (F2-score = 0.804, AUC = 0.837). This model was used to generate a risk map visualizing the probability of pipeline damage. The map can aid in the efficient management of urban heat transport systems by enabling preemptive maintenance in high-risk areas. Incorporating external environmental data and auxiliary facility information in future models could further enhance reliability and support the development of a more effective maintenance decision-making system. Full article

Stray-current and soft-water leaching can induce severe corrosion in reinforced concrete structures and buried metal pipelines within subway environments. The effects of water-to-binder ratio (W/C), modulus of sodium silicate (Ms), and alkali content (AC) on the mechanical properties of fly-ash-based geopolymer (FAG) at various curing ages were investigated. The influence of curing temperature and high-temperature curing duration on the development of mechanical performance were examined, and the optimal curing regime was determined. Furthermore, based on the mix design of FAG resistant to coupled erosion from stray-current and soft-water, the effects of stray-current intensity and erosion duration on the coupled erosion behavior were analyzed. The results indicated that FAG exhibited slow strength development under ambient conditions. However, thermal curing at 80 °C for 24 h markedly improved early-age strength. The compressive strength of FAG exhibited an increase followed by a decrease with increasing W/B, Ms, and AC, with optimal ranges identified as 0.28–0.34, 1.0–1.6, and 4–7%, respectively. Soft-water alone caused limited leaching, while the presence of stray-current significantly accelerated degradation, with corrosion rates increasing by 4.1 and 7.2 times under 20 V and 40 V, respectively. The coupled corrosion effect was found to weaken over time and with increasing current intensity. Under coupled leaching conditions, compressive strength loss of FAG was primarily influenced by AC, with lesser contributions from W/B and Ms. The optimal mix proportion for corrosion resistance was determined to be W/B of 0.30, Ms of 1.2, and AC of 6%, under which the compressive strength after corrosion achieved the highest value, thereby significantly improving the durability of FAG in harsh environments such as stray-current zones in subways. Full article

To address the difficulty of locating small-hole leaks in buried natural gas pipelines, this study conducted a comprehensive theoretical and numerical analysis of the acoustic characteristics associated with such leakage events. A coupled flow–acoustic simulation framework was developed, integrating gas compressibility via the realizable k-ε and Large Eddy Simulation (LES) turbulence models, the Peng–Robinson equation of state, a broadband noise source model, and the Ffowcs Williams–Hawkings (FW-H) acoustic analogy. The effects of pipeline operating pressure (2–10 MPa), leakage hole diameter (1–6 mm), soil type (sandy, loam, and clay), and leakage orientation on the flow field, acoustic source behavior, and sound field distribution were systematically investigated. The results indicate that the leakage hole size and soil medium exert significant influence on both flow dynamics and acoustic propagation, while the pipeline pressure mainly affects the strength of the acoustic source. The leakage direction was found to have only a minor impact on the overall results. The leakage noise is primarily composed of dipole sources arising from gas–solid interactions and quadrupole sources generated by turbulent flow, with the frequency spectrum concentrated in the low-frequency range of 0–500 Hz. This research elucidates the acoustic characteristics of pipeline leakage under various conditions and provides a theoretical foundation for optimal sensor deployment and accurate localization in buried pipeline leak detection systems. Full article

This study investigates the mechanical behavior and safety performance of buried natural gas pipelines crossing seismically active fault zones and liquefaction-prone areas, with particular application to the China–Russia East-Route Natural Gas Pipeline. The research combines experimental testing, numerical simulation, and machine learning to develop an advanced framework for pipeline safety assessment under seismic loading conditions. A series of large-scale pipe–soil interaction experiments were conducted under seismic-frequency cyclic loading, leading to the development of a modified soil spring model that accurately captures the nonlinear soil-resistance characteristics during seismic events. Unlike prior studies focusing on static or specific seismic conditions, this work uniquely integrates real cyclic loading test data to develop a frequency-dependent soil spring model, significantly enhancing the physical basis for dynamic soil–pipeline interaction simulation. Finite element analyses were systematically performed to evaluate pipeline response under liquefaction-induced ground displacement, considering key influencing factors including liquefaction zone length, seismic wave frequency content, operational pressure, and pipe wall thickness. An innovative machine learning-based predictive model was developed by integrating LightGBM, XGBoost, and CatBoost algorithms, achieving remarkable prediction accuracy for pipeline strain (R² > 0.999, MAPE < 1%). This high accuracy represents a significant improvement over conventional analytical methods and enables rapid safety assessment. The findings provide robust theoretical support for pipeline routing and seismic design in high-risk zones, enhancing the safety and reliability of energy infrastructure. Full article

Jacking-pipe construction has the advantages of high mechanization, low environmental impact and fast construction speed. It is widely used in the project of underground pipeline under river. However, jacking-pipe grouting under shallow burial conditions is prone to cause surface bubbling problems. Based on the jacking-pipe project of Meichong Lake in Changfeng County, Hefei, this paper discussed the mechanism of grouting surface leakage, and defined the relationship between the critical pressure of jacking-pipe grouting and the ultimate pressure of shear damage of mud jacket. Mechanical model of surface leakage from shallow buried jacking-pipe grouting was established. A general mathematical expression for the grouting critical pressure was derived and a sensitivity analysis was performed. A numerical model was established based on the background engineering, and multiple sets of grouting pressure conditions for simulation and analysis were set up. The results showed that the cohesive force $c$, the angle of internal friction $\phi$, and the overburden thickness $h_s$ were all approximately linearly and positively correlated with the critical pressure of grouting. When the grouting pressure was less than 197.54 kPa the surface settlement increased. When this value was exceeded the surface displacement changed from settlement to uplift and the risk of slurry bubbling increased significantly. The theoretical calculation matched the value of grouting critical pressure from numerical simulation. The actual grouting pressure in the project was lower than the theoretical grouting critical pressure value and no slurry bubbling occurred during construction, which had verified the reliability of the theoretical model. This study can provide theoretical basis and investigation ideas for the setting of reasonable grouting pressure in similar projects. Full article

Internal soil erosion caused by water infiltration around defective buried pipes poses a significant threat to the long-term stability of underground infrastructures such as pipelines and highway culverts. This study employs a coupled computational fluid dynamics–discrete element method (CFD–DEM) framework to simulate the detachment, transport, and redistribution of soil particles under varying infiltration pressures and pipe defect geometries. Using ANSYS Fluent (CFD) and Rocky (DEM), the simulation resolves both the fluid flow field and granular particle dynamics, capturing erosion cavity formation, void evolution, and soil particle transport in three dimensions. The results reveal that increased infiltration pressure and defect size in the buried pipe significantly accelerate the process of erosion and sinkhole formation, leading to potentially unstable subsurface conditions. Visualization of particle migration, sinkhole development, and soil velocity distributions provides insight into the mechanisms driving localized failure. The findings highlight the importance of considering fluid–particle interactions and defect characteristics in the design and maintenance of buried structures, offering a predictive basis for assessing erosion risk and infrastructure vulnerability. Full article

With the rapid development of urban rail transit, the impact of shield tunneling on existing pipelines is increasing. To protect pipeline safety, this research focuses on the complex pipelines in the Shaluo shield tunneling section, utilizing FLAC3D numerical simulation software to investigate the deformation characteristics of cast iron pipelines during shield construction. Additionally, it quantifies the influence of pipeline materials on deformation and establishes the pipeline safety risk grading system. Safety assessment of pipelines based on the research. The research indicates that (1) The deformation difference between the tops of the pressure and pressureless pipeline is less than 1 mm, suggesting that pipeline deformation is minimally influenced by pressure. The deformation is the largest at the entrance and gradually decreases along the direction of excavation, indicating that the deformation has an obvious hysteresis effect. (2) The threefold variation in maximum deformation among pipelines of different materials during shield tunneling indicates the high sensitivity of pipeline material properties to shield construction processes. (3) By analyzing and discussing the literature and local norms, the deformation value of the pipeline is taken as the evaluation index. And the pipeline assessment system is established. (4) Cast iron pipelines at the start of the shield have the highest safety, and concrete pipelines at the beginning of the shield are the lowest. Full article

Urban water supply pipelines play a critical role in ensuring the continuous delivery of water, and their failure during earthquakes can result in significant societal disruptions. This study proposes a seismic damage prediction method for urban buried water supply pipelines affected by seismic wave propagation, grounded in empirical data from past earthquake events. The method integrates key influencing factors, including pipeline material, diameter, joint type, age, and soil corrosivity. To enhance its practical applicability and address the challenge of quantifying soil corrosivity, a simplified classification approach is introduced. The proposed model is validated using observed pipeline damage data from the 2008 Wenchuan earthquake, with predicted results showing relatively good agreement with actual failure patterns, thereby demonstrating the model’s reliability for seismic risk assessment. Furthermore, the model is applied to assess potential earthquake-induced damage to buried pipelines in the city center of Ganzhou, and the corresponding results are presented. The findings support earthquake risk mitigation and the protection of urban infrastructure, while also providing valuable guidance for the replacement of aging pipelines and the enhancement of urban disaster resilience. Full article

Ground-penetrating radar (GPR) plays a critical role in detecting underground targets, particularly locating and characterizing leaks in buried pipelines. However, the complex nature of GPR images related to pipeline leaks, combined with the limitations of existing neural network-based inversion methods, such as insufficient feature extraction and low inversion accuracy, poses significant challenges for effective leakage reconstruction. To address these challenges, this paper proposes an enhanced UNet++-based model: the Multi-Scale Directional Network PlusPlus (MSDNet++). The network employs an encoder–decoder architecture, in which the encoder incorporates multi-scale directional convolutions with coordinate attention to extract and compress features across different scales effectively. The decoder fuses multi-level features through dense skip connections and further enhances the representation of critical information via coordinate attention, enabling the accurate inversion of dielectric constant images. Experimental results on both simulated and real-world data demonstrate that MSDNet++ can accurately invert the location and extent of buried pipeline leaks from GPR B-scan images. Full article

Accurate localization of buried water pipelines in rural areas is crucial for maintenance and leak management but is often hindered by outdated maps and the limitations of traditional geophysical methods. This study aimed to develop and validate a multi-source remote-sensing workflow, integrating UAV (unmanned aerial vehicle)-borne near-infrared (NIR) surveys, multi-temporal Sentinel-2 imagery, and historical Google Earth orthophotos to precisely map pipeline locations and establish a surface baseline for future monitoring. Each dataset was processed within a unified least-squares framework to delineate pipeline axes from surface anomalies (vegetation stress, soil discoloration, and proxies) and rigorously quantify positional uncertainty, with findings validated against RTK-GNSS (Real-Time Kinematic—Global Navigation Satellite System) surveys of an excavated trench. The combined approach yielded sub-meter accuracy (±0.3 m) with UAV data, meter-scale precision (≈±1 m) with Google Earth, and precision up to several meters (±13.0 m) with Sentinel-2, significantly improving upon inaccurate legacy maps (up to a 300 m divergence) and successfully guiding excavation to locate a pipeline segment. The methodology demonstrated seasonal variability in detection capabilities, with optimal UAV-based identification occurring during early-vegetation growth phases (NDVI, Normalized Difference Vegetation Index ≈ 0.30–0.45) and post-harvest periods. A Sentinel-2 analysis of 221 cloud-free scenes revealed persistent soil discoloration patterns spanning 15–30 m in width, while Google Earth historical imagery provided crucial bridging data with intermediate spatial and temporal resolution. Ground-truth validation confirmed the pipeline location within 0.4 m of the Google Earth-derived position. This integrated, cost-effective workflow provides a transferable methodology for enhanced pipeline mapping and establishes a vital baseline of surface signatures, enabling more effective future monitoring and proactive maintenance to detect leaks or structural failures. This methodology is particularly valuable for water utility companies, municipal infrastructure managers, consulting engineers specializing in buried utilities, and remote-sensing practitioners working in pipeline detection and monitoring applications. Full article

Pipe–soil interaction encompasses the study of stress distributions and deformation mechanisms occurring between buried pipelines and their surrounding soil. Understanding the mechanical behavior of this coupled system is essential for the analysis of deformation patterns and failure modes in buried pipelines, thereby providing critical guidance for construction design and risk assessment protocols. Traditional analytical approaches have relied on classical mechanics theories and experimental methodologies; however, these approaches often incorporate excessive simplifications and assumptions that inadequately represent the complex properties of both soil and pipeline structures. Numerical simulation methodologies have emerged as viable alternatives for investigating pipe–soil interaction. Among these numerical approaches, Smoothed Particle Hydrodynamics (SPH)—an advanced Lagrangian meshless particle method—offers distinct advantages in modeling complex behaviors, including free surfaces, deformable boundaries, and large deformation scenarios that characterize pipe–soil interaction. This research establishes a pipe–soil interaction model for buried pipelines utilizing the SPH method, incorporating elastic–plastic constitutive relationships to represent soil behavior. The investigation examines lateral interaction mechanisms, vertical interaction responses in sandy soils, and the parametric influence of various soil properties on pipe–soil interaction characteristics. This study contributes insights into the application of meshfree numerical simulation techniques for pipe–soil interaction analysis, offering both engineering utility and theoretical advancement for pipeline infrastructure design and safety assessment. Full article

Acoustic methods are a promising direction when determining the position of buried non-metallic pipelines. Under difficult soil conditions, one of the most effective methods is the vibroacoustic method, which has a maximum range of application when acoustic waves propagate through the transported medium. However, due to limited energy input into the pipeline, signal detection at significant distances from the source becomes challenging. This article considers the mechanism of acoustic oscillations attenuation in pipes and suggests possible directions for optimization of the investigated technology. The evaluation of mathematical modeling methods for the investigated process is conducted, and the key signal attenuation relationships are presented. The analysis allowed us to establish that the vibroacoustic method has the potential of increasing the efficiency by approximately 10–20%. Full article

Horizontal directional drilling (HDD) can be utilized in a submarine cable landing operation to solve the problems of a deficient buried depth and a limited route. In this study, a numerical model of the pullback process of a submarine cable using HDD technology is established based on the commercial finite element method platform OrcaFlex 11.3, which is validated using the in situ measured data of an HDD operation project for a pipeline. The effects of the crossing length, incident angle, and pullback velocity of the cable on the effective tension in the cable are investigated and analyzed. The results indicate that an increase in the crossing length and incident angle can significantly enhance the tension in the cable. Under the specific conditions in the Zhoushan islands, the maximum crossing length and incident angle are 1700 m and 35°, respectively. The pullback velocity has a minor influence on the tension in the cable, and an extremely large velocity might lock the cable during its pullback operation. The permissible values derived in this study can provide valuable information to similar engineering cases and projects. Full article

Unstable sandy soils pose significant challenges for buried pipelines due to soil–infrastructure interaction, leading to settlement that increases the risk of displacement and stress-induced fractures. In earthquake-prone regions, seismic-induced ground deformation further threatens underground infrastructure. Fiber-reinforced polymer (FRP) composites have emerged as a sustainable alternative to conventional piling materials, addressing durability issues in deep foundations. This paper introduces novel explicit models for predicting the maximum settlement of oil pipelines supported by concrete or polymer micropiles under seismic loading. Using genetic programming (GP), this study develops closed-form expressions based on simplified input parameters—micropile dimensions, pile spacing, soil properties, and peak ground acceleration—improving the models’ practicality for engineering applications. The models were evaluated using a dataset of 610 data points and demonstrated good accuracy across different conditions, achieving coefficients of determination (R²) as high as 0.92, among good values for other evaluation metrics. These findings contribute to a robust, practical tool for mitigating seismic risks in pipeline design, highlighting the potential of FRP micropiles for enhancing infrastructure resilience under challenging geotechnical scenarios. Full article