Reliability analysis of low, mid and high-grade strength corroded pipes based on plastic flow theory using adaptive nonlinear conjugate map

Seghier, Mohamed El Amine Ben; Keshtegar, Behrooz; Bouali, Elahmoune

doi:10.1016/j.engfailanal.2018.03.029

Cited by 62 publications

(18 citation statements)

References 40 publications

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“…Most of the structures are continuously subjected to different types of loadings during their service life, such as static, pseudostatic and dynamic loading conditions, especially marine structures like offshore platforms and offshore pipelines 1 . Regarding this latter, the static and pseudostatic loads are resulting mainly from the internal pressure, own weight and thermal variations 2 . In addition, dynamic loads can be caused by fluid–pipe interactions (internal and external flows), impacts due to fluid hammer or foreign objects 3 .…”

Section: Introductionmentioning

confidence: 99%

Novel hybridized adaptive neuro‐fuzzy inference system models based particle swarm optimization and genetic algorithms for accurate prediction of stress intensity factor

Seghier

Carvalho

Keshtegar

et al. 2020

Fatigue Fract Eng Mat Struct

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The aim of this study is to develop a new framework for the prediction of stress intensity factor (SIF) using newly developed hybrid artificial intelligence (AI) models. To do so, an adaptive neuro-fuzzy inference system optimized by two meta-heuristic algorithms as genetic algorithm (ANFIS-GA) and particle swarm optimization (ANFIS-PSO) is proposed. Moreover, a database composed of 150 SIF values obtained using the finite element method (FEM) calculations is used for training and validating the two proposed AI models. The efficiency and accuracy of the proposed AI models were investigated through several assessment criteria. Results showed the outperformance of the ANFIS-PSO model for accurate prediction of SIF values with R 2 = 0.9913, root mean square error (RMSE) = 23.6 and mean absolute error (MAE) = 18.07, whereas both AI models indicate a robust performance in the presence of input variability. Overall, the performed study provides a hybrid AI framework that can serve as an efficient numerical tool for SIF prediction and analysis.

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Section: Introductionmentioning

confidence: 99%

Novel hybridized adaptive neuro‐fuzzy inference system models based particle swarm optimization and genetic algorithms for accurate prediction of stress intensity factor

Seghier

Carvalho

Keshtegar

et al. 2020

Fatigue Fract Eng Mat Struct

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“…However, using a large test database in not enough for accuracy of a proposed model and it is also necessary to establish the reliability of such a database using an efficient reliability method [41]. Recently, the conjugate search direction with adaptive formulation was developed for enhancement of the accuracy and efficiency of the FORM [42][43][44]. The literature review has shown that no study has been conducted to date on the application of a conjugate search direction method based on FORM (CFORM) on the reliability analysis of test databases of FRP-confined concrete.…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis of FRP-Confined Concrete at Ultimate using Conjugate Search Direction Method

et al. 2020

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In this paper compressive strength and ultimate strain results in the current database of fiber-reinforced polymer (FRP)-confined concrete are used to determine the reliability of their design space. The Lognormal, Normal, Frechet, Gumbel, and Weibull distributions are selected to evaluate the probabilistic characteristics of six FRP material categories. Following this, safety levels of the database are determined based on a probabilistic model. An iterative reliability method is developed with conjugate search direction for evaluating the reliability. The results show that Lognormal and Gumbel distributions provide best probability distribution for model errors of strength and strain enhancement ratios. The developed conjugate reliability method provides improved robustness over the existing reliability methods owing to its faster convergence to stable results. The results reveal that the part of the database containing normal strength concrete (NSC) heavily confined (i.e., actual confinement ratio (flu,a/f’co) > 0.5) by low and normal modulus carbon fibers (i.e., fiber elastic modulus (Ef) ≤ 260 GPa) and moderately confined (i.e., 0.3 ≤ flu,a/f’co ≤ 0.5) by aramid fibers exhibits a very high safety level. The segments of the database with a low and moderate safety level have been identified as i) NSC moderately and heavily confined by higher modulus glass fibers (i.e., Ef > 60 GPa), ii) high strength concrete (HSC) moderately and heavily confined (i.e., flu,a/f’co > 0.3) by glass fibers, iii) HSC lightly confined (i.e., flu,a/f’co ≤ 0.2) by carbon fibers, and iv) HSC lightly confined by aramid fibers. Additional experimental studies are required on these segments of the database before they can be used reliably for design and modeling purposes.

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“…Probabilistic methods are widely used when evaluating the structural performance due to theirs advantages. Different mechanisms failure are studied using Probabilistic methods such as corroded pipelines in [6][7][8] in comparing to deterministic methods or assessment again target reliability using calibration safely factor, it gives many advantages. The large number of input parameter involved in structural analysis, evaluation of failure probability can be optimized using probabilistic methods.…”

Section: Introductionmentioning

confidence: 99%

Effect of shape factor on structural reliability analysis of a surface cracked pipeline-parametric study

Guillal

Abdelbaki

Bensghier

et al. 2019

Frattura Ed Integrità Strutturale

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The variation of crack shape factor (a/c) during propagation has an important role on calculation of the stress intensity factor (SIF), where imprecise estimation of this latter can lead us to an inaccurate prediction of failure probabilities. For the case of external cracked surface pipeline carried oil and gas products, such estimation can results undesired fault decisions like excessive repairs action or inspection planning. In this paper, the structural integrity analysis of pipeline with semi elliptical crack on the external surface is evaluated. Reliability calculations expressed in term of reliability index β are carried out based on Monte Carlo simulation and First Order reliability Method (FORM). The crack shape factors are varied to cover a variety of geometries from shallow to deep cracks while fatigue crack growth is assumed in depth direction. For SIF estimation, surface and deep point are considered. Results of the analysis indicate that for a constant crack depth a/t, the reliability index is strongly affected by a/c ratio and the trend is not similar in deep and surface point for different crack shapes.

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Reliability analysis of low, mid and high-grade strength corroded pipes based on plastic flow theory using adaptive nonlinear conjugate map

Cited by 62 publications

References 40 publications

Novel hybridized adaptive neuro‐fuzzy inference system models based particle swarm optimization and genetic algorithms for accurate prediction of stress intensity factor

Novel hybridized adaptive neuro‐fuzzy inference system models based particle swarm optimization and genetic algorithms for accurate prediction of stress intensity factor

Reliability Analysis of FRP-Confined Concrete at Ultimate using Conjugate Search Direction Method

Effect of shape factor on structural reliability analysis of a surface cracked pipeline-parametric study

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