Study on Failure Behavior of Steel Wire-Adhesive Resin Interface Based on Inverse Optimization Algorithm

HU Jun-yan, CHENG Biao, ZHANG Jian, LIU Wen-jun, SHI Jun

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Plastics Science and Technology ›› 2024, Vol. 52 ›› Issue (06) : 77-83. DOI: 10.15925/j.cnki.issn1005-3360.2024.06.015
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Study on Failure Behavior of Steel Wire-Adhesive Resin Interface Based on Inverse Optimization Algorithm

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Abstract

The steel wire winding reinforced plastic composite pipe (PSP) has excellent comprehensive performance and has been widely used in petroleum, chemical industry, water supply and other industries. However, in the extreme environment of high temperature and high pressure, the interface debonding failure occurs between the steel wire inside the pipe and the hot melt adhesive. In order to study the failure behavior of the bonding interface between steel wire and hot melt adhesive, the paper conducted a single steel wire/hot melt adhesive sample drawing test, established a single steel wire drawing finite element model consistent with the test loading process. Based on the cohesion theory to simulate the bonding effect between steel wire and hot melt adhesive, an ABAQUS-Python-MATLAB interactive program was developed according to the inverse optimization calculation concept, to achieve automatic comparison between each round of tensile force-displacement calculation curves and experimental curves, as well as continuous optimization of interface parameters. The inversion cohesion parameters were substituted into the drawing models with different buried depths. The calculation results of the peak value of the drawing force and the corresponding displacement were in good agreement with the test results. The inversion parameters can reflect the bonding effect of the wire and hot melt adhesive.

Key words

PSP / Steel-plastic interface / Finite element model / Cohesive / Iterative calculation

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HU Jun-yan , CHENG Biao , ZHANG Jian , et al . Study on Failure Behavior of Steel Wire-Adhesive Resin Interface Based on Inverse Optimization Algorithm. Plastics Science and Technology. 2024, 52(06): 77-83 https://doi.org/10.15925/j.cnki.issn1005-3360.2024.06.015

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