Structural Analysis and of Braking Block Sleeves on Transit Gas-Pipeline

Magura, Martin; Brodniansky, Ján

doi:10.1016/j.proeng.2012.07.090

Cited by 1 publication

(1 citation statement)

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“…Therefore, it is very important to provide proper tools to the maintenance engineers to detect and avoid conditions which can potentially result in structural failure, and consequently, generating environmental damages and/or economic and human losses. For this reason, analyses of pipelines were performed by many researchers up to present days and a wide range of analytical and numerical models can be found in literature [1]- [3], characterized by different assumptions for pipelines behaviour.…”

Section: Introductionmentioning

confidence: 99%

Coupling of the Boundary Element Method With a Hybrid Method for Inverse Stress Analysis of Pipelines

Portela

Jarek

Lacerda

2019

Boundary Elements and Other Mesh Reduction Methods XLII

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The aim of this work is to develop a numerical tool for structural inverse analysis to obtain boundary conditions and their location. The inverse analysis is performed through an optimization process having as restrictions the information obtained from a direct analysis, representing data which could be obtained from surface monitoring of pipelines. Thus, the numerical models comprehend the solution of two problems: the direct one in which the boundary element method (BEM) is used to obtain the displacements and tractions in the structure, and the inverse problem, in which two optimization models were implemented. The first approach uses the genetic algorithm (GA) method associated with the BEM (GA-BEM), minimizing the residuals between the calculated and the "monitored" relative surface displacements. The second approach is a hybrid method (HM) in which the GA is associated with the Newton-Raphson method for performing the inverse analysis with the BEM (HM-BEM). All tests demonstrated the efficiency of the numerical tools for structural inverse analysis, with the HM approach showing lower computational cost and better accuracy.

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Section: Introductionmentioning

confidence: 99%