Prediction of Optimal Process Parameters in Tribocorrosion Inhibition of Steel Pipes Using Response Surface Methodology

被引:0
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作者
Jitendra Narayan Panda
Edwin Yanez Orquera
Brandon Christopher Wong
Philip Egberts
机构
[1] University of Calgary,Department of Mechanical and Manufacturing Engineering
来源
Tribology Letters | 2021年 / 69卷
关键词
Tribocorrosion; Corrosion inhibitor; Friction and wear; Response surface methodology (RSM);
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学科分类号
摘要
Wear corrosion is a significant problem impacting the lifetime of steel pipes used in hydraulic fracturing operations. To improve the lifetime of these steel pipes, the present work examines the effect and optimization of three propriety corrosion inhibitors (Dynarate, DWP, and CalGuard), as well as their concentration, on the tribocorrosion behavior of AISI 4715 steels used to carry fracking liquid from their storage pool to the geological formation. The wear and corrosion behavior of AISI 4715 steel was investigated using a reciprocating tribometer integrated with a three-probe electrochemical apparatus. Response surface methodology (RSM) was applied to statistically model the effects of various concentrations of Dynarate, DWP, and CalGuard, along with their combinations, on the average coefficient of friction (COF), as well as the total wear loss of the steel and optimize them. The overall results revealed that Dynarate significantly decreased the COF (0.147) and wear rate (0.3 mm/year) with an inhibition efficiency of 480% at a concentration of 1%. To investigate the effectiveness of the regression model at predicting the wear rate, the samples were characterized using 3D optical profilometer and scanning probe microscopy to describe the effect of various additive on the surface morphology of steel. The surface topography measurements indicated the worn regions for the samples where the Dynarate additive was used were smoother compared with those having the DWP and CalGuard additives.
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