Numerical Analysis and Strength Evaluation of an Exposed River Crossing Pipeline with Casing Under Flood Load

Pipelines in service always experience complicated loadings induced by operational and environmental conditions. Flood is one of the common natural hazard threats for buried steel pipelines. One exposed river crossing X70 gas pipeline induced by flood erosion was used as a prototype for this study. A mechanical model was established considering the field loading conditions. Morison equations were adopted to calculate distributional hydrodynamic loads on spanning pipe caused by flood flow. Nonlinear soil constraint on pipe was considered using discrete nonlinear soil springs. An explicit solution of bending stiffness for pipe segment with casing was derived and applied to the numerical model. The von Mises yield criterion was used as failure criteria of the X70 pipe. Stress behavior of the pipe were analyzed by a rigorous finite element model established by the general-purpose Finite-Element package ABAQUS, with 3D pipe elements and pipe-soil interaction elements simulating pipe and soil constraints on pipe, respectively. Results show that, the pipe is safe at present, as the maximum von Mises stress in pipe with the field parameters is 185.57 MPa. The critical flow velocity of the pipe is 5.8 m/s with the present spanning length. The critical spanning length of the pipe is 467 m with the present flow velocity. The failure pipe sections locate at the connection point of the bare pipe and the pipe with casing or the supporting point of the bare pipe on riverbed

Leveraging data mining, active learning, and domain adaptation for efficient discovery of advanced oxygen evolution electrocatalysts

Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study presents a multistage machine learning (ML) approach to streamline the discovery and optimization of complex multimetallic catalysts. Our method integrates data mining, active learning, and domain adaptation throughout the materials discovery process. Unlike traditional trial-and-error methods, this approach systematically narrows the exploration space using domain knowledge with minimized reliance on subjective intuition. Then, the active learning module efficiently refines element composition and synthesis conditions through iterative experimental feedback. The process culminated in the discovery of a promising Ru-Mn-Ca-Pr oxide catalyst. Our workflow also enhances theoretical simulations with domain adaptation strategy, providing deeper mechanistic insights aligned with experimental findings. By leveraging diverse data sources and multiple ML strategies, we demonstrate an efficient pathway for electrocatalyst discovery and optimization. This comprehensive, data-driven approach represents a paradigm shift and potentially benchmark in electrocatalysts research

Safety assessment on girth welds of large-diameter X80 pipelines in water network area

As the soil in the water network area is soft and has large water content, it is very easy to settle, which applies an axial load to the pipeline, and the girth weld under the action of tensile load has a higher risk of failure. In order to ensure the intrinsic safety of the pipeline, a nonlinear finite element method was adopted to establish a numerical calculation model for the axial stress and strain of the pipeline under sudden settlement of soft soil based on the X80 pipeline with a diameter of 1 422 mm in the water network area, and thus the influence of different settlement displacements of soft soil on the size and distribution of the axial load of pipeline under the most unfavorable sudden displacement condition was studied. On this basis, the safety of pipeline welds at different locations in the soft soil settlement area was evaluated according to the Guide to Methods for Assessing the Acceptability of Flaws in Metallic Structures (BS 7910-2019). Meanwhile, the influence of external load conditions and weld misalignment was analyzed, which indicates that the increase of misalignment leads to an increase in the load ratio and toughness ratio used in the assessment, with the conservativeness reduced for the safety of pipeline. If the critical Crack Tip Opening Displacement (CTOD) is taken to be 0.25 mm in the current standard, and the level-1 assessment curve is adopted, the welds of X80 pipeline in the water network area are always in a safe state. If the level-2 assessment curve is used, the X80 pipeline weld is in a critical safe state when the critical CTOD is reduced to 0.08 mm and the settlement displacement takes the maximum value of 1 m

Study on residual strength of oil and gas pipeline with corrosion defects under bending load

The significance of oil and gas pipelines in the exploration and production of oil and gas resources is well-documented. However, these pipelines are subject to a number of challenges that can compromise their integrity and operational efficiency. These challenges include structural defects, geological disasters such as earthquakes, landslides, debris flows, and land subsidence, as well as external forces such as dynamic impact forces, shear forces, extrusion forces, and uneven settlement forces. These defects can be exacerbated, thereby increasing the risk of pipeline failure. To accurately evaluate the pipeline’s bearing capacity and safety, the study developed a nonlinear numerical simulation software called ABAQUS, utilising the Python programming language for analysis. Utilising this model, a systematic study of the dimensional characteristics of corrosion defects (including length, width, and depth) and the influence of pipe material (steel type) on residual strength has been conducted. The results demonstrate that an increase in the length and depth ratios of corrosion defects will result in a substantial decrease in the ultimate rupture pressure of pipelines. The integrity evaluation of oil and gas pipelines has revealed that the width of corrosion defects does not appear to have a discernible impact on residual strength. A thorough analysis of the experimental data reveals that, while the width is influenced by numerous factors, there is no statistically significant variation in the residual strength of corroded defect pipelines with different widths under standard test conditions. If the size and location of corrosion defects remain constant, upgrading the steel grade has been demonstrated to have a substantial impact on the pipeline’s residual strength

Dynamic structural evolution of iron catalysts involving competitive oxidation and carburization during CO2 hydrogenation

Identifying the dynamic structure of heterogeneous catalysts is crucial for the rational design of new ones. In this contribution, the structural evolution of Fe(0) catalysts during CO2 hydrogenation to hydrocarbons has been investigated by using several (quasi) in situ techniques. Upon initial reduction, Fe species are carburized to Fe3C and then to Fe5C2. The by-product of CO2 hydrogenation, H2O, oxidizes the iron carbide to Fe3O4. The formation of Fe3O4@(Fe5C2+Fe3O4) core-shell structure was observed at steady state, and the surface composition depends on the balance of oxidation and carburization, where water plays a key role in the oxidation. The performance of CO2 hydrogenation was also correlated with the dynamic surface structure. Theoretical calculations and controll experiments reveal the interdependence between the phase transition and reactive environment. We also suggest a practical way to tune the competitive reactions to maintain an Fe5C2-rich surface for a desired C2+ productivity

Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts

Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study introduces a novel, multi-stage machine learning (ML) approach to streamline the discovery and optimization of complex multi-metallic catalysts. Our method integrates data mining, active learning, and domain adaptation throughout the materials discovery process. Unlike traditional trial-and-error methods, this approach systematically narrows the exploration space using domain knowledge with minimized reliance on subjective intuition. Then the active learning module efficiently refines element composition and synthesis conditions through iterative experimental feedback. The process culminated in the discovery of a promising Ru-Mn-Ca-Pr oxide catalyst. Our workflow also enhances theoretical simulations with domain adaptation strategy, providing deeper mechanistic insights aligned with experimental findings. By leveraging diverse data sources and multiple ML strategies, we establish an efficient pathway for electrocatalyst discovery and optimization. This comprehensive, data-driven approach represents a paradigm shift and potentially new benchmark in electrocatalysts research.95 pages (main text 37 pages; supplementary materials 58 pages); 38 figures (main text 6 figures; supplementary materials 32 figures

Optimization of IMU-based bending strain solving algorithm and full-scale experimental validation

Objective The pipe bending strain identification technology based on an inertial mapping unit (IMU) in-line detector has seen extensive applications in China and abroad. IMUs obtain bending strains along entire pipelines through a solving process, using pitch angles and heading angles acquired by a gyroscope. However, deviations from the detection path may occur during the practical in-line detector operation, due to the sizes of IMUs and other factors, leading to inevitable errors between the bending strains identified by IMUs and the actual pipeline conditions. Methods A simulation model was developed for IMU in-line detectors based on their actual size, without abnormal vibrations and other interferences. In addition, a simulation database was created for pipelines with a diameter of 508 mm under varying bending strain conditions. Moreover, a solving algorithm optimized through an ANNExtraTree deep learning model was introduced. These tools were leveraged for error analysis and to delve into the bending strain solving algorithm. Furthermore, full-scale pulling experiments were conducted on pipeline bending strains, to verify the feasibility and accuracy of the optimized solving algorithm. Results This study revealed that as pipeline bending strain increased, the errors between IMU detections and true bending strains grew. The mean square error, error covariance and error standard deviation of the bending strain data derived from the optimized solving process decreased from 0.007 0, 0.004 9, 0.070 2 to 0.001 2, 0.001 6, 0.012 6 respectively, while the coefficient of determination, indicating correlation, rose from 0.443 to 0.981. Furthermore, the full-scale pulling experiments conducted to validate the algorithm revealed substantial reductions in errors between bending strains computed by the optimized solving algorithm and those detected by a strain gauge at 79.6%, 79.4%, and 76.0%, respectively. Conclusion The proposed optimized solving algorithm is verified feasible and accurate through finite element simulations and full-scale pulling experiments. The study findings provide technical support and guidance for accurately identifying bending strains along pipelines based on IMU

A closed-form solution for stress analysis of hollow circular cylinder structure under non-uniform external load and its engineering application

Hollow circular cylinder structures are widely used in industry for their high bearing capacity. In some engineering cases, these structures are always subjected to complicated non-uniform external loads. For example, casings used for oil production are subjected to non-uniform ground stresses. In this study, a generalized closed-form analytical solution for stress analysis of hollow circular cylinder under non-uniform external load was derived. The common non-uniform external load was decomposed by Fourier series under the principle of superposition by theory of elasticity. Analytical solutions for stress results of sine or cosine series external load problems were obtained by the semi-inverse method. A baseline analysis of a casing under non-uniform ground stress was presented using the proposed analytical method and the finite element method to validate the accuracy of the proposed analytical model. A parametric analysis was conducted finally to discuss the effects of non-uniform coefficients on the stress results. Results show that, the hollow circular cylinder structure’s anti-collapse capacity will be strongly weakened, when the non-uniform coefficient increases. This proposed analytical model can be referenced in strength verification of hollow circular cylinder structures in engineering practice.</jats:p

Local Buckling Behavior and Plastic Deformation Capacity of High-Strength Pipe at Strike-Slip Fault Crossing

As a typical hazard threat for buried pipelines, an active fault can induce large plastic deformation in a pipe, leading to rupture failure. The mechanical behavior of high-strength X80 pipeline subjected to strike-slip fault displacements was investigated in detail in the presented study with parametric analysis performed by the finite element model, which simulates pipe and soil constraints on pipe by shell and nonlinear spring elements respectively. Accuracy of the numerical model was validated by previous full-scale experimental results. Insight of local buckling response of high-strength pipe under compressive strike-slip fault was revealed. Effects of the pipe-fault intersection angle, pipe operation pressure, pipe wall thickness, soil parameters and pipe buried depth on critical section axial force in buckled area, critical fault displacement, critical compressive strain and post buckling response were elucidated comprehensively. In addition, feasibility of some common buckling failure criteria (i.e., the CSA Z662 model proposed by Canadian Standard association, the UOA model proposed by University of Alberta and the CRES-GB50470 model proposed by Center of Reliable Energy System) was discussed by comparing with numerical results. This study can be referenced for performance-based design and assessment of buried high-strength pipe in geo-hazard areas