Reliability Of Pipelines Research Articles

Prediction of the internal corrosion rate for oil and gas pipelines and influence factor analysis with interpretable ensemble learning

Corrosion is one of the major threats to the safety and reliability of oil and gas pipelines, making accurate prediction of corrosion rate crucial for pipeline maintenance and repairment. Traditional prediction methods often ignore more critical factors and lack interpretability, which hinders the practical application. Here, an interpretable ensemble machine learning framework is proposed, not only improving prediction performance, but also enhancing interpretability for predicting the internal corrosion rate of oil and gas pipelines. In this work, ExtraTreeRegression model has demonstrated superior prediction accuracy relative to the other five machine learning models, and the determination coefficient of the ExtraTreeRegression model achieves 0.93 after feature engineering. Then, Shapley Additive exPlanations (SHAP) values is utilized to visually interpret the model locally and globally to help account for the contributions of the input features. Furthermore, the accumulated local effect (ALE) successfully explains how the features affect the internal corrosion rate of oil and gas pipelines. By collecting corrosion data of oil and gas pipeline and performing feature engineering and data preprocessing, we construct a comprehensive and reliable prediction model with interpretability. Experimental results demonstrate that the proposed interpretable ensemble machine learning approach outperforms other models in both accuracy and interpretability, providing valuable insights for pipeline management decisions.

RadMLBench: A dataset collection for benchmarking in radiomics

BackgroundNew machine learning methods and techniques are frequently introduced in radiomics, but they are often tested on a single dataset, which makes it challenging to assess their true benefit. Currently, there is a lack of a larger, publicly accessible dataset collection on which such assessments could be performed. In this study, a collection of radiomics datasets with binary outcomes in tabular form was curated to allow benchmarking of machine learning methods and techniques. MethodsA variety of journals and online sources were searched to identify tabular radiomics data with binary outcomes, which were then compiled into a homogeneous data collection that is easily accessible via Python. To illustrate the utility of the dataset collection, it was applied to investigate whether feature decorrelation prior to feature selection could improve predictive performance in a radiomics pipeline. ResultsA total of 50 radiomic datasets were collected, with sample sizes ranging from 51 to 969 and 101 to 11165 features. Using this data, it was observed that decorrelating features did not yield any significant improvement on average. ConclusionsA large collection of datasets, easily accessible via Python, suitable for benchmarking and evaluating new machine learning techniques and methods was curated. Its utility was exemplified by demonstrating that feature decorrelation prior to feature selection does not, on average, lead to significant performance gains and could be omitted, thereby increasing the robustness and reliability of the radiomics pipeline.

TO THE ISSUE OF SOIL VARIOUS TYPES INFLUENCE ON PIPELINE LONGITUDINAL MOVEMENT

Achieving and maintaining the required reliability of the linear part of the main gas pipelines is of great importance. Emergency destruction usually leads to large gas leaks into the atmosphere and undersupply to consumers, significant costs for the restoration of main gas pipelines. The rise in cost of repair work on main gas pipelines directly depends on the difficult conditions of the route. Special technical solutions are to be used for achieving the necessary stability and reliability of pipelines on low-bearing soils. Thus, on operating gas pipelines at variable temperatures of the transported product, their longitudinal movements occur, resulting in longitudinal forces appearance and correspondingly in increase of gas pipeline stress state and their possible destruction. The significant period of time of increase in gas pipeline movements indicates that these changes in pipeline position occur due to the rheological properties of soils. An analysis of the stress state of such sections of gas pipelines is necessary to assess their operational reliability and, as a result, the timing and methods of repair. This article discusses the maximum values of longitudinal displacements of a pipeline laid in various soils and the deflection values corresponding to these models for potentially dangerous sections.

A quantitative assessment of the rehabilitative impact of Kevlar liners on offshore pipelines

Offshore pipelines transport oil and natural gas that contain different corrosive contaminants, leading to internal corrosions. The presence of internal metal loss problems can significantly degrade the load-bearing capacity and reliability of pipelines over time. To address this issue, a Kevlar liner, offering a more accessible and cost-effective solution, is employed for repairing corroded pipelines. However, a quantitative assessment of the rehabilitating effect of Kevlar liner has been lacking. This study performed an investigation of the burst pressure of internal corroded pipelines reinforced with the Kevlar liner through a combination of experimental testing and finite element numerical simulations. While previous research primarily concentrated on single external defect, this study has investigated the burst pressure of pipelines in the presence of both single and dual internal corrosion defects. The results indicated that the presence of two corrosion defects further decreases the burst pressure of the pipelines. This study examined the reinforcement mechanism of Kevlar liner, revealing that it largely postpones the stress development in the corrosion zone and thereby enhances the ultimate internal pressure load-bearing capacity of the pipelines. Moreover, the contact stress resulting from the friction between the Kevlar liner and the steel pipeline contributes to the overall improvement in the load-bearing capacity of the corroded offshore pipelines.

FEATURES OF CALCULATING LONGITUDINAL DISPLACEMENTS OF PIPELINES LAID IN HETEROGENEOUS SOILS

Achieving and maintaining the required reliability of the linear part of the main gas pipelines is of particular importance. Emergency destruction usually leads to large gas leaks into the atmosphere and undersupply to consumers, significant costs for the restoration of main gas pipelines. The difficulty and cost of carrying out repairs of main gas pipelines directly depends on the difficult conditions of the route and special technical solutions are needed to achieve the stability and reliability of pipelines on low-bearing soils. Thus, on existing gas pipelines, their longitudinal movements occur under the action of longitudinal forces, which leads to an increase in the stress state of gas pipelines and even the destruction of pipes. The significant time duration of the increase in gas pipeline movements indicates that these movements occur due to the rheological properties of soils. An analysis of the stress state of such sections of gas pipelines is necessary to assess their reliability, timing and methods of repair.

A probabilistic framework for external pitting corrosion growth modelling for buried steel pipelines considering soil properties

This paper introduces a novel framework for developing reliable probabilistic predictive corrosion growth models for buried steel pipelines using pipeline inspection data. The framework adopts a power-law function of time model formulation, accounting for nonconstant damage growth rates, and considers the correlation between defect depth and length growth models. The proposed framework explicitly incorporates local influential soil properties in the model formulation; thus, it requires no segmentation and homogenous defect growth assumption and provides defect-specific growth models. The framework is applicable regardless of the availability of matched or non-matched defect data. For corrosion initiation time estimation, two different approaches are proposed: one is to use a Poisson process to account for defect occurrence, which can also predict newly generated defects since the last inspection, and the other is to use multivariate linear regression of soil and pipe properties. The statistics of unknown model parameters are assessed using a Bayesian updating framework in which the model error can be incorporated. The proposed framework is applied using two different sets of data: one set of inline inspection (ILI) data and one set of field excavation data. A case study is conducted, where time-dependent system reliability of an in-service pipeline is assessed considering small leak and burst failure modes using the developed defect growth models. The impact of the growth model accuracy on the probability of failure is investigated, and the importance analysis is performed to identify the most influential random variables to the probability of failure.

Risk-based maintenance strategy for oil transfer pipelines using an intuitionistic fuzzy computational approach

The safety and reliability of oil transfer pipelines are crucial, as pipeline failures can severely affect the environment. As pipeline risk management is dynamic and uncertain, traditional maintenance approaches often fall short. This research paper proposes an Intuitive Fuzzy Computational Approach (IFCA) for oil transfer pipeline maintenance (RBM). To develop a targeted and nuanced maintenance plan, Failure Modes and Effects Analysis (FMEA) is employed. Pipeline equipment is hierarchically organised according to their failure mode criticality, which guides maintenance design. This paper leverages the context of an Interval Valued Intuitionistic Fuzzy (IVIF) environment to streamline the hierarchical classification of oil transmission pipeline instruments. The objectives are threefold: (1) to develop an intuitionistic fuzzy risk assessment model, (2) to design a modified algorithm for maintenance prioritisation, and (3) to develop a decision support system. Additionally, the research incorporates the IVIF-SWARA method to enable flexible adjustments in the alignment of the pipeline instruments. By addressing the specific challenges of oil transfer pipelines, this research aims to contribute to advancing the field of pipeline maintenance and risk management. The proposed RBM strategy, underpinned by the IFCA framework, is expected to enhance pipeline reliability and mitigate the risks associated with pipeline failures. Abbreviations: RBM: Risk-Based Maintenance; IFCA: Intuitionistic Fuzzy Computational Approach; FMEA: Failure Modes and Effects Analysis; IVIF: Interval Valued Intuitionistic Fuzzy; SWARA: Stepwise Weight Assessment Ratio Analysis; RCM: Reliability-Centered Maintenance; RBI: Risk-Based Inspection; CBM: Condition-Based Maintenance; IFS: Intuitionistic Fuzzy Set; HFPR: Hesitant Fuzzy Preference Relation; IVIFPHA: Interval-Valued Intuitionistic Fuzzy Power Heronian Aggregation; MCDM: Multi-Criteria Decision-Making; S C O i : Accuracy Function of Occurrence; S C S i : Accuracy Function of Severity; K ( a ~ ) : Failure Probability Index; L W D : Minimum Allowable Weight of The Failure Detection Index; WS, WO, WD: Weight Assigned to The Failure Outcome; RP V j : Relative Priority Value; OREDA: The Offshore Reliable Data Handbook; IVIFPWHA: Interval-Valued Intuitionistic Fuzzy Power Weight Heronian Aggregation

WITHDRAWN: Research on pipeline corrosion prediction based on RF-PSO-BP Algorithm

The transportation of oil and gas relies heavily on pipelines, and pipeline corrosion is a major factor affecting pipeline reliability. It can lead to pipeline failure and other damage. Pipeline corrosion prediction is of great importance for pipeline integrity management and failure prevention. A physical law intervening RF(Random Forest)-PSO(Particle Swarm Optimization)-BP(Back Propagation Neural Network) algorithm is proposed to predict pipeline corrosion rate. The DeWaard physical model is first fitted to the data, and the fitted physical model predicts pipeline corrosion to form a new feature, which is then combined with the features extracted by the RF algorithm to form a new feature that is used as an input metric for the data-driven model. Secondly, the already constructed features are divided into training set and testing set. The training set is used to train the PSO-BP model, and the test set is used to test the accuracy of the model. The model is evaluated using the metrics such as MAE, MBE, MAPE, and R2. To show the superiority of the proposed model, the proposed model is compared with other models. The results show that the proposed model has some advantages in both feature analysis and corrosion prediction, and it has some theoretical guidance for pipeline protection.

Unleashing the Potential of a Hybrid 3D Hydrodynamic Monte Carlo Risk Model for Maritime Structures’ Design in the Imminent Climate Change Era

Submarine pipelines have become integral for transporting resources and drinking water across large bodies. Therefore, ensuring the stability and reliability of these submarine pipelines is crucial. Incorporating climate change impacts into the design of marine structures is paramount to assure their lifetime safety and serviceability. Deterministic design methods may not fully consider the uncertainties and risks related to climate change compared to risk-based design models. The latter approach considers the future risks and uncertainties linked to climate and environmental changes, thus ensuring infrastructure sustainability. This study pioneers a Hybrid 3D Hydrodynamic Monte Carlo Simulation (HMCS) Model to improve the reliability-based design of submarine pipelines, incorporating the effects of climate change. Current design approaches may follow deterministic methods, which may not systematically account for climate change’s comprehensive uncertainties and risks. Similarly, traditional design codes often follow a deterministic approach, lacking in the comprehensive integration of dynamic environmental factors such as wind, waves, currents, and geotechnical conditions, and may not adequately handle the uncertainties, including the long-term effects of climate change. Nowadays, most countries are developing new design codes to modify the risk levels for climate change’s effects, such as sea-level rises, changes in precipitation, or changes in the frequency/intensity of winds/storms/waves in coastal and marine designs. Our model may help these efforts by integrating a comprehensive risk-based approach, utilizing a 3D hydrodynamic model to correlate diverse environmental factors through Monte Carlo Simulations (MCS). The hybrid model can promise the sustainability of marine infrastructure by adapting to future environmental changes and uncertainties. Including such advanced methodologies in the design, codes are encouraged to reinforce the resilience of maritime structures in the climate change era. The present design codes should inevitably be reviewed according to climate change effects, and the hybrid risk-based design model proposed in this research should be included in codes to ensure the reliability of maritime structures. The HMCS model represents a significant advancement over existing risk models by incorporating comprehensive environmental factors, utilizing advanced simulation techniques, and explicitly addressing the impacts of climate change. This innovative approach ensures the development of more resilient and sustainable maritime infrastructure capable of withstanding future environmental uncertainties.

GTFE-Net-BiLSTM-AM: An intelligent feature recognition method for natural gas pipelines

The recognition of pipeline features contributes to its safe management by preventing severe consequences such as leakage resulting from bending deformation and denting under external pressure. However, extracting features of such a facility is complex and challenging when machine learning techniques are applied to feature recognition. Hence, this paper proposes a feature recognition technique for gas pipelines based on Gramian Time Frequency Enhancement Net (GTFE-Net), Bi-directional Long Short-Term Memory (BiLSTM) and attention mechanism (AM), namely GTFE-Net-BiLSTM-AM. Specifically, GTFE-Net is applied to enhance the time-frequency input bending strain signal, which is subsequently incorporated with the BiLSTM model to extract spatio-temporal features. The attention mechanism computes the corresponding weight of output features. The results show that the proposed method's recognition accuracy reaches 93.7%. The comparison study with the existing models validates the proposed method's superiority and shows that its accuracy is higher than that of the existing models (more than 0.9%) or their combined models (more than 1.1%). Overall, the proposed method contributes to the safety, reliability, and operation of natural gas pipelines.

ANALYSIS OF AUTOMATION SYSTEMS FOR MAINTENANCE AND REPAIR OF ELECTRONIC COMPUTING EQUIPMENT

The subject area of maintenance and repair (MRO) of electronic computer equipment (ECT) is described. The study provides a rationale for the creation of a new software product. The work presents the MRO process, examines analogues of software products, and describes their shortcomings. The authors emphasize that today there are no available information and analytical systems (IAS) that meet the necessary requirements, namely software for calculating system reliability. Currently, software analogues are aimed at calculating the reliability of pipelines or at the business part of maintenance and repair. Based on the results of the study, a model of a new software product for calculating reliability was proposed. The context and container schemes of the IAS are presented, and the necessary modules are described. The main purpose of the proposed system is to work with electronic devices. It will allow for new research, for example, checking the convergence of existing methods for calculating the residual life. The ability to integrate intelligent methods will speed up the reporting process. The engineer will remain in the role of supervisor.

ON THE PERFECTION OF THE APPROACH TO THE FORMATION OF A PROGRAM FOR INCREASING THE RELIABILITY OF FIELD PIPELINES IN OC ROSNEFT

The article describes an approach for ranking and selecting field pipelines based on the total cost of ownership of the facility for the purpose of timely repairs and minimization of accidents, as well as its software implementation. The principle of the proposed approach is to apply a technical and economic model of the total cost of ownership of a pipeline, which takes into account the costs of maintaining the pipeline over a long period of time, which include the costs of pipeline maintenance activities, pipeline failures and replacement of pipeline sections. This model allows determining which replacement year corresponds to the minimum accumulated maintenance costs, by varying the year of pipeline replacement from the start of operations to the planning horizon. The model also allows to take into account the impact of operational technological measures on the cost of pipeline ownership and the selection of the optimal year of repair.In order to take into account the level of pipeline accidents in the process of operation on the basis of operational data, a mathematical probabilistic model based on the Weibull distribution was developed. The mathematical model allows to take into account for each pipeline the influence of technical characteristics (diameter, length, wall thickness, material, coating, design features), operating conditions (type of pumped medium, technological mode of pipeline operation) and information on inspection and diagnostics. The accuracy of failure prediction using this model is at least 90 %.The approach to the formation of programs to improve the reliability of field pipelines with regard to optimal repair periods based on the total cost of ownership model is described, taking into account various objectives and constraints, among which the main ones are:- required achievable level of accidents;- acceptable amounts of financing for re-pairs;- permissible physical volumes of repairs along the length.The approach to forming reliability improvement programs described in this article has been implemented in Rosneft's corporate software system RN-SM. The implementation of this software package in production activities is being implemented in 2023–2024.

ToGC: a pipeline to correct gene model for functional excavation of dark GPCRs in Phytophthora sojae1

The accuracy of genomic annotation is crucial for subsequent functional investigations; however, computational protocols used in high-throughput annotation of open reading frames (ORFs) can introduce inconsistencies. These inconsistencies, which lead to non-uniform extension or truncation of sequence ends, pose challenges for downstream analyses. Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive, lacking specific approaches. To address this gap, we developed toGC, a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies. Using toGC, we achieved an accuracy of nearly 100% accuracy in correcting inconsistencies in published P. sojae ORFs. We applied this innovative pipeline to the GPCR-bigrams gene family, which was predicted to have 42 members in the P. sojae genome but lacked experimental validation. By employing toGC, we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and toGC-corrected sequences. Notably, among these were 5 genes (GPCR-TKL9, GPCR-TKL15, GPCR-PDE3, GPCR-AC3, and GPCR-AC4) showed substantial inconsistencies. Experimental gene annotation confirmed the effectiveness of toGC, as sequences obtained through cloning matched those annotated by toGC. Importantly, we discovered two novel GPCRs (GPCR-AC3 and GPCR-AC4), which were previously mispredicted as a single gene. CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production, further confirming their status as two separate genes. In addition to P. sojae, the reliability of the toGC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline. Our findings highlight the utility of toGC for reliable gene model correction, facilitating investigations into biological functions and offering potential applications in diverse species analyses.

Real-Time Monitoring of Data Pipelines: Exploring and Experimentally Proving that the Continuous Monitoring in Data Pipelines Reduces Cost and Elevates Quality

Data pipelines are crucial for processing and transforming data in various domains, including finance, healthcare, and e-commerce. Ensuring the reliability and accuracy of data pipelines is of utmost importance to maintain data integrity and make informed business decisions. In this paper, we explore the significance of continuous monitoring in data pipelines and its contribution to data observability. This work discusses the challenges associated with monitoring data pipelines in real-time, propose a framework for real-time monitoring, and highlight its benefits in enhancing data observability. The findings of this work emphasize the need for organizations to adopt continuous monitoring practices to ensure data quality, detect anomalies, and improve overall system performance.

Environmental safety of main gas pipelines

Analysis of the causes of accidents indicates the prevailing influence of corrosion factors on the structural reliability of main gas pipelines. During operation, main pipelines are exposed to the in-pipe pressure of the pumped product and ground electrolytes, which leads to corrosion-mechanical damage. Moreover, these factors can act in the most unfavorable combinations. This combined action reduces the durability of the material. This leads to much faster destruction of the pipe metal. Therefore, it is necessary to monitor not only general corrosion damage, but also local damage, which, when subjected to mechanical stress, can become a source of corrosion crack. The article discusses the main factors influencing the environmental safety of main gas pipelines, as determining the required level of quality at the time of operation.

THE PLACE OF INSULATION COATINGS IN ENSURING RELIABILITY STEEL UNDERGROUND GAS PIPELINES

The article examines the issue of the place and role of insulating coatings in ensuring the reliability of steel underground gas pipelines. It has been shown that insulation is the main, basic means of protection against corrosion. A reliability model has been proposed for a linear section of a steel underground gas pipeline as a complex technical system consisting of unequal elements: a steel pipe as the main element that determines the operability/inoperability state of the system, and auxiliary protective elements – insulation and electrochemical protection, which reduce the level of corrosive effects of soil on the main element. This increases the degree of similarity of the reliability model to a real technical object, and also makes it possible to build a hierarchical structure of faults of various elements, taking into account their impact on the overall technical condition of the gas pipeline. It is proposed to consider its integrity as the determining physical parameter of the protective coating; the degree of preservation (loss) of integrity and the onset of the limiting state of the insulation should be assessed by the number (density) of defects.

Influence of convective amplification on aeroacoustics oscillations in main gas pipeline

Influence of convective amplification on aeroacoustics oscillations in main gas pipeline

Speed of metal deformation of welded pipe sections in the process of natural tests

It is clear that testing on Menage Charpey samples and other materials, which may not match the durability of pipe walls, does not reflect the real picture of visco-plastic failures, which does not allow the development of a methodology or model for predicting the residual life (failure-free) gas pipelines have a three-year term of operation. At the same time, theoretical and laboratory studies do not always provide sufficient evidence for nutrition, directly related to the reliability and trouble-free operation of pipelines. It is likely that in the laboratory minds of enterprises and scientific foundations, it is important to create and identify all the factors that characterize the growing and widespread use of metal in gas pipelines to represent nature. and testing of cutting gas pipelines with a length of 150-250 m. However, due to the technical complexity of their implementation, in the field Our minds will never again be faced with the need to identify a new set of registration parameters. In addition, the testing of highly labor-intensive procedures, including ensuring the safety of their implementation, requires large material and hourly costs. Serial testing of enclosed pipes in the drains of a specially lined landfill and cutting on this basis is quite consistent with the results of field testing of gas pipelines. Field testing of pipes allows for consistently inexpensive research when testing new types of steel and pipe designs. Therefore, laboratory data need to be verified and necessarily clarified based on the results of pneumatic testing of long-life pipe sections, so that at the present time there is an urgent need to combine laboratory and field tests pipes of the gas pipeline. Such testing is not widespread, but as a result of their experimentation, important information is taken away from the behavior and power of metal in the minds of vantagement and exploitation, those closest to exploitation. Full-scale testing was carried out at a specially trained test site for cutting pipes intended for the construction of main gas pipelines, which made it possible to determine the kinematic and dynamic parameters of the alignment of the model gas pipeline under operating conditions. importance and in minds as close as possible to the operational ones. Analysis of the results of the field (natural) tests is to confirm that from the moment of initiation of the collapse in the central pipe, the fluidity of the main crack (on both sides of the initiator) increases and increases distance approximately 2-3 diameters from the cut, reaching a maximum. Changing the fluidity after tightening the central pipe can be either symmetrical or asymmetrical to the cut in the middle pipe. This is due to the technique of carrying out the experiment and the formation of cracks, including displacements of the cutting edge in the middle of the pipe and various influences on the metal of the pipes in the zone of local tearing. The underlying regularity is that the maximum fluidity is not evident at the crack acceleration stage. It is necessary to note that in order to carry out the experiment, so that the achieved high fluidity of the structure is preserved when the top of the crack enters the final plot. This is ensured by consistent selection of the viscosity of the metal of the central pipe.

Optimizing Big Data Analytics for Reliability and Resilience: A Survey of Techniques and Applications

The advent of big data has revolutionized various industries, enabling organizations to make data- driven decisions and gain valuable insights. However, the sheer volume, velocity, and variety of big data pose significant challenges in ensuring the reliability and resilience of big data analytics pipelines. In this context, optimization techniques play a crucial role in enhancing the reliability and resilience of big data analytics. This paper provides a comprehensive survey of optimization techniques for reliable and resilient big data analytics. The paper first discusses the motivation for optimizing big data analytics for reliability and resilience. Then, it presents a detailed overview of various optimization techniques, including resource optimization, data partitioning, data compression, load balancing, and fault detection and tolerance. Finally, the paper discusses the applications of optimization techniques in various big data analytics domains, such as real-time analytics, fraud detection, recommendation systems, predictive analytics, and risk management.

COMPARATIVE ANALYSIS AND SIMULATION OF WELDING MODES DURING THE CONSTRUCTION OF THE MAIN PIPELINE USING AUTOMATED TECHNOLOGIES

In the present work, the technology of laser welding of the circumferential joints of pipes of the main gas pipeline was studied on the basis of the existing certain experience of its application at the facilities of the gas transmission system and an assessment was made of the possibility of using it as an alternative to automatic arc welding during construction and repair and restoration work. An analysis was made of the use of laser radiation for orbital welding of main pipelines, which showed that the use of this technology makes it possible to increase the productivity of the welding process, to obtain more favorable structures in the seam and in the transition zone, and to ensure a high level of mechanical properties and weld density. Temperature and deformation conditions in the zone of the welded joint help to reduce the likelihood of hot and cold cracking.Modeling of a pipeline section with welded joints made by automatic arc welding and laser welding (hereinafter referred to as LS) was carried out. When modeling welded joints, their geometric parameters for the compared welding technologies were taken into account, as well as the area and volume of the deposited metal, which theoretically correspond to natural values. Loads were applied to the pipe section with a welded seam, imitating three types of mechanical tests: tension, compression and bending, which occur in the case of thermal deformations and soil subsidence during pipeline operation.In the course of the study, stresses were determined in the cross section of a welded joint obtained using two welding technologies, which show the level of mechanical properties of the weld. A comparative analysis and evaluation of the operational reliability of the main gas pipeline with welded joints made by modern automated welding technologies has been carried out.