|Title:||Pipeline mechanical properties determination using non-destructive method with consideration of microstructural changes|
|Other Titles:||Визначення механічних характеристик трубопроводів неруйнівним методом з урахуванням мікроструктурних змін|
|Authors:||Karpash, M. O.|
Dotsenko, Ye. R.
Karpash, O. M.
|Publisher:||Ivano-Frankivsk National Technical University of Oil and Gas|
|Citation:||Karpash, M. O. Pipeline mechanical properties determination using non-destructive method with consideration of microstructural changes = Визначення механічних характеристик трубопроводів неруйнівним методом з урахуванням мікроструктурних змін / M. O. Karpash, Ye. R. Dotsenko, O. M. Karpash // Journal of Hydrocarbon Power Engineering. - 2014. - Vol. 1, № 2. - C. 115-122.|
|Abstract:||Existing pipeline networks used for transportation of oil and gas are being exposed for operation for decades resulting in serious material degradation process occurs in such cases. In this research results of experimental investigation aimed at determination of the electrical resistivity of structural steels used in gas transmission pipelines with the help of the developed experimental unit that implements the four-point method was studied. Multi-parameter approach was utilized in the study while neural networks were used for non-linear approximation of yield strength of pipelines as a function of hardness and electrical resistivity. Samples with special heat-treatment for microstructure distinguishing as well as a number of samples taken from the long-term used pipelines were selected. Destructive tensile testing was performed for all samples under investigation and results were used as references in the study. It was shown that the four-point method can be used to overall metal structures, since the measured value of electrical resistivity does not affect the whole width of the object of control, but only so-called conditional effective width. Under the conditional effective width of the sample should be understood that part of the sample, in which the density of direct current passing through the object, is the largest and which actually affects the measured value of electrical resistivity. Combined measurement of the hardness together with electrical resistivity after neural network processing showed to achieve 26 MPa accuracy for yield strength determination at real-life pipelines.|
|Appears in Collections:||Journal of Hydrocarbon Power Engineering. - 2014. - Vol. 1, № 2|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.