Applying probabilistic fracture mechanics on the reliability estimation and lifetime of spherical pressure vessels for storage of liquefied petroleum gas

Purpose Models for determining the reliability and failure probability of a pressure vessel have been the subject of several studies based on probabilistic fracture mechanics (PFM). Possible failures in pressure vessels, usually catastrophic, have motivated researchers in this area, whose purpose was to improve the physical integrity of the vessel and, consequently, increase the safety and reduce costs in the oil industry. Design/methodology/approach The model approaches the reliability estimation and lifetime or remaining lifetime of spherical pressure vessels for storage of liquefied petroleum gas (LPG) by applying PFM. It selects data for all necessary variables for the model, adjusts the database to an acceptable probability distribution and then establishes a failure model to evaluate the failure probability and reliability according to the chosen criterion. It employs the Monte Carlo simulation technique. Findings This work can conclude that the influence of the environment on the lifetime or remaining lifetime of spherical pressure vessels for storage of LPG, when for the same steel (X65), sometimes exposed to air and sometimes to an environment containing H2S, significantly reduces reliability. Originality/value This work evaluates the behavior of the cyclic stresses along the vessel wall through meridional and latitudinal coordinates, according to the support type of the spherical pressure vessel. When combined with small amounts of H2S , it may accelerate fatigue crack propagation, since LPG can contain water and hydrogen sulfide (H2S), a combination that is rarely found in specialized literature.

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Publication Details

Journal
International Journal of Structural Integrity
Published
2025-10-18
DOI
https://doi.org/10.1108/ijsi-05-2025-0135
Primary Topic
Data Analysis with R
Type
article
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article

Applying probabilistic fracture mechanics on the reliability estimation and lifetime of spherical pressure vessels for storage of liquefied petroleum gas

International Journal of Structural Integrity
Data Analysis with R
article

Applying probabilistic fracture mechanics on the reliability estimation and lifetime of spherical pressure vessels for storage of liquefied petroleum gas

article en

Abstract

Purpose Models for determining the reliability and failure probability of a pressure vessel have been the subject of several studies based on probabilistic fracture mechanics (PFM). Possible failures in pressure vessels, usually catastrophic, have motivated researchers in this area, whose purpose was to improve the physical integrity of the vessel and, consequently, increase the safety and reduce costs in the oil industry. Design/methodology/approach The model approaches the reliability estimation and lifetime or remaining lifetime of spherical pressure vessels for storage of liquefied petroleum gas (LPG) by applying PFM. It selects data for all necessary variables for the model, adjusts the database to an acceptable probability distribution and then establishes a failure model to evaluate the failure probability and reliability according to the chosen criterion. It employs the Monte Carlo simulation technique. Findings This work can conclude that the influence of the environment on the lifetime or remaining lifetime of spherical pressure vessels for storage of LPG, when for the same steel (X65), sometimes exposed to air and sometimes to an environment containing H2S, significantly reduces reliability. Originality/value This work evaluates the behavior of the cyclic stresses along the vessel wall through meridional and latitudinal coordinates, according to the support type of the spherical pressure vessel. When combined with small amounts of H2S , it may accelerate fatigue crack propagation, since LPG can contain water and hydrogen sulfide (H2S), a combination that is rarely found in specialized literature.

International Journal of Structural Integrity
Universidade Federal do Espírito Santo (BR)
Openalex Percentile: Top 23%
Data Analysis with R
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