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Imperfections or uneven surfaces of welded areas due to uncertain errors such as equipment, weld quality, or mechanical damage may cause defects or anomalies such as corrosion or cracks and lead to other failures such as burst or leakage. Corrosion tends to occur at the uneven area due to the stagnation of the hydrocarbons for a long period, which directly can reduce the strength of the pipeline itself. This paper proposes a framework that incorporates structural reliability analysis (SRA) to analyze the safety and integrity levels of corroded girth welded API 5L X56 pipeline. By developing the limit state functions (LSFs) with reference to previous studies and existing codes and standards, the assessment was divided into two sections: assessing the pipeline as a single pipeline, and as sectional parts (girth welded area) of the pipeline. The probabilistic evaluation was carried out using Monte Carlo simulation (MCS), and the obtained results were compared in terms of the failure probability, Pf. The results demonstrated that two burst pressure models—the Shell-92 and Zhang et al. models—are highly conservative based on the failure probability, whereas the pipeline corrosion failure criterion (PCORRC) gives the most reasonable results for both general corroded and girth welded pipeline scenarios. The findings of this work also indicate that the failure probability in sectional pipes is more reliable than that in entire pipes due to the consideration of corrosion distributions in the pipeline. [ABSTRACT FROM AUTHOR]

Subsea pipelines are delicate infrastructures with high importance to the oil and gas industry. These structures are surrounded by an extreme environment, in which free spanning is a major issue that can lead to several unwanted events such as local buckling or vortex-induced vibration. Moreover, corrosion is inevitable problem to these structures. All these problems highly reduce the safety levels of subsea pipelines. Hence, this paper proposes a new framework for the probabilistic analysis of subsea pipelines subjected to both free spanning and corrosion degradation. For the subsea pipeline, new limit state functions are developed that include failure modes due to corrosion degradation and spanning loads caused by the maximum bending stress. In addition, new probabilistic burst pressure models for corroded pipelines have been included, taking into consideration pipeline steel grade strength as well as the surrounding uncertainty. The importance sampling method is proposed to estimate the reliability analysis results in terms of failure probability and reliability index. The proposed framework is applied on a real case study of API 5 L X65 subsea pipeline. The impact of several parameters on the reliability analysis outcome are investigated and discussed through several scenarios. Results indicate the importance of early-inspection data for planning the suitable operating regime of the pipeline in terms of internal pressure, which can be used to estimate the allowable critical spanning lengths and corrosion defect geometries to alert the appropriate actions to avoid failures. • The assessment of subsea pipeline exposed to spanning loads and corrosion degradation is introduced. • Importance sampling method is proposed for estimating the failure probability results. • The framework is demonstrated using inspection data from an API 5 L X65 subsea pipeline. • The impact of crucial factors on the case study's reliability analysis results is examined. [ABSTRACT FROM AUTHOR]

The estimation of the failure probability for complex systems is a crucial issue for sustainability. Reliability analysis methods are needed to be developed to provide accurate estimations of the safety levels for the complex systems and structures of today. In this paper, a novel hybrid framework for the reliability analysis of engineering systems and structures is extended to reduce the computational burden. The proposed hybrid framework is named as SVR–CFORM and consists of coupling two parts: the first is an enhanced first-order reliability method (FORM) using nonlinear conjugate map (CFORM); the second is an artificial intelligence technique called support vector regression (SVR). The conjugate FORM (CFORM) is adaptively formulated to improve the robustness of the original iterative FORM algorithm, whereas the SVR technique is used to enhance the efficiency of the reliability analysis by reducing the computational burden. The performance of the proposed SVR–CFORM formulation is compared in terms of efficiency and robustness with several FORM formulas (i.e. HL–RF, directional stability transformation method, conjugate HL–RF and finite step length) through different numerical/structural reliability examples. Results indicate that the proposed SVR–CFORM formulation is more accurate and efficient than other reliability methods. Based on the comparative analysis results, the SVR technique can highly reduce the computational costs and accurately model the response of complex performance functions, while the iterative CFORM formulation found to provide stable and robust reliability index results compared to the others reliability methods. • A novel FORM based reliability method is developed for robust analyses of nonlinear problems. • The conjugate FORM is combined with SVR as a robust and efficient MPP search method. • The proposed SVR–CFORM is compared with several reliability methods. • The low-computational cost with stable results is captured using SVR–CFORM compared to other FORM formulas. [ABSTRACT FROM AUTHOR]

The use of composite flexible pipelines seems reliable and promising to the oil and gas industry to transport hydrocarbons as it is one of the best alternatives to overcome the major problem of corrosion in conventional carbon steel pipelines. However, throughout the years of operation, composite flexible pipelines can also degrade and tend to experience failures such as cracking, delamination and buckling due to several external or internal factors. It is crucial to periodically inspect and monitor the actual condition of composite pipelines in order to determine their safety and integrity throughout their design life. Therefore, with the scientometric and systematic review method, this paper aims to provide insight and future direction on the reliability and integrity assessment of composite pipelines that may be beneficial to pipeline operators as well as researchers or scholars within this field of expertise. Discussion on the common failure drivers, modes and mechanisms are detailed to better understand the relationship between the failure, reliability and integrity of composite flexible pipelines. A brief discussion about the available inspection and monitoring techniques for composite pipelines is also reported. From this comprehensive review, it is found that available approaches for the structural reliability analysis and integrity assessments of composite flexible pipelines are mainly based on quantitative risk-based inspection (QRBI) to produce a more reliable risk interpretation. Nevertheless, combining multiple inspection techniques and employing machine learning methodologies can aid in improving the real-time damage evaluation and safety performance of composite flexible pipes. • A scientometric review of 184 peer-reviewed articles on composite pipes in the oil and gas industry is being done. • A thorough examination of failure drivers, failure modes, and failure mechanisms is provided. • The evaluation discusses inspection and monitoring methodologies, as well as safety procedures. • Research gab and future directions for dealing with them are also offered. [ABSTRACT FROM AUTHOR]

Reinforced concrete (RC) beams are basic elements used in the construction of various structures and infrastructural systems. When exposed to harsh environmental conditions, the integrity of RC beams could be compromised as a result of various deterioration mechanisms. One of the most common deterioration mechanisms is the formation of different types of corrosion in the steel reinforcements of the beams, which could impact the overall reliability of the beam. Existing classical reliability analysis methods have shown unstable results when used for the assessment of highly nonlinear problems, such as corroded RC beams. To that end, the main purpose of this paper is to explore the use of a structural reliability method for the multi-state assessment of corroded RC beams. To do so, an improved reliability method, namely the three-term conjugate map (TCM) based on the first order reliability method (FORM), is used. The application of the TCM method to identify the multi-state failure of RC beams is validated against various well-known structural reliability-based FORM formulations. The limit state function (LSF) for corroded RC beams is formulated in accordance with two corrosion types, namely uniform and pitting corrosion, and with consideration of brittle fracture due to the pit-to-crack transition probability. The time-dependent reliability analyses conducted in this study are also used to assess the influence of various parameters on the resulting failure probability of the corroded beams. The results show that the nominal bar diameter, corrosion initiation rate, and the external loads have an important influence on the safety of these structures. In addition, the proposed method is shown to outperform other reliability-based FORM formulations in predicting the level of reliability in RC beams. [ABSTRACT FROM AUTHOR]

Computing the sensitivity vector in the traditional first order reliability method may provide inaccurate reliability outcomes for discrete performance functions and inefficient computation burden for high-dimensional problems. In this study, two improved particle swarm optimization algorithms are proposed to enhance the convergence rate with global optimal results during the structural reliability analysis. The abilities for convergence speed and global convergence of the particle swarm optimization algorithm are improved using a novel hybrid method called particle swarm optimization-based harmony search algorithm (PSO–HS), and enhanced particle swarm optimization (EPSO). The proposed methods use a dynamic self-adaptive term to execute the local adjusting process. Using twelve numerical-based engineering problems, the structural reliability frameworks developed based on modified versions of particle swarm optimization algorithms are compared to numerous FORM algorithms and the current metaheuristic methods. Results indicated that the novel proposed methods using the improved PSO algorithms are more robust and efficient than the analytical FORM methods for solving high-dimensional engineering problems. Furthermore, compared to the previous metaheuristic approaches, the suggested methods enabled faster convergence. • Two optimization algorithms are proposed as novel hybrid FORM in structural reliability analysis. • Local adjusting process is proposed in hybrid FORM methods of EPSO and PSO–HS. • PSO–HS and EPSO compared with PSO, HS, IHS, IPSO, LS-PSO and six FORM algorithms. • Proposed methods are more efficient than FORM for high-dimensional problems. [ABSTRACT FROM AUTHOR]