2018
DOI: 10.1016/j.jngse.2018.03.011
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Crater formation by the rupture of underground natural gas pipelines: A probabilistic-based model

Abstract: A model to predict crater dimensions given a LOC in underground pipelines is proposed • The model implements 57 real accidents of natural gas underground pipelines • The approach proposes worst, mean and less severe scenarios to support decision-making • Some applications in Domino effect scenarios and Right-of-Way distances were discussed

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Cited by 7 publications
(4 citation statements)
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References 23 publications
(43 reference statements)
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“…Logarithmic and cubic root transformations were used, as certain features such as k and T had more comprehensive ranges (i.e., greater than 10:1); see Figure 3 . These types of transformations have been successfully applied in previous works [ 82 , 83 ] to help stabilize the variance of the data [ 84 ].…”
Section: Comparison Of Rheological Parametersmentioning
confidence: 99%
“…Logarithmic and cubic root transformations were used, as certain features such as k and T had more comprehensive ranges (i.e., greater than 10:1); see Figure 3 . These types of transformations have been successfully applied in previous works [ 82 , 83 ] to help stabilize the variance of the data [ 84 ].…”
Section: Comparison Of Rheological Parametersmentioning
confidence: 99%
“…Once the best predictors are selected, the best regressions were obtained based on the minimum RSE, maximum adjusted 2 , and modified versions of the Akaike Information Criteria (AIC) and the Bayesian Information Criteria (BIC) previously used by Amaya-Gómez et al (2018). In what follows, the best regressions are described in more detail, which in all cases omit the intercept in Eq.…”
Section: Multivariate Regression Of the Crater Dimensionsmentioning
confidence: 99%
“…The preliminary predictions show interesting results of the crater width and depth, bearing in mind that the reported dimensions account the effects from the two failures, whereas these predictions consider them separately. For more in-depth analyses of these accidents, please refer to the approach proposed in Amaya-Gómez et al (2018). The records and correlation factors proposed in this paper can be used to identify preliminary domino effect scenarios based on some safety distances.…”
Section: Domino Effect Sequencesmentioning
confidence: 99%
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