Experimental study on erosion behavior of fracturing pipeline involving tensile stress and erosion prediction using random forest regression

Erosion-Corrosion in Pipe Flows of Particle-Laden Liquids

“…Yang et al [6] carried out a performance investigation for slurry erosion in highpressure hydraulic fracturing pipelines. Unlike other papers which studied slurry erosion, the effects of tensile stress induced due to internal/external pressure was considered.…”

“…The response of pipeline materials to solid particle impacts depends on the nature of the target material and the treatments to which that material has been subjected. Environmental parameters such as flow velocity [5], pressure [6], temperature, impact angle, solid particle concentration, size and shape are also known to influence erosion [7]. The influence of impact angle depends on the mechanical characteristics of the pipe material.…”

Condition monitoring and temporal‐spatial assessment of composite pipeline transporting potable water

“…RF is characterized by the capability of handling high‐dimensional problems with good accuracy and reliability, a few parameters to be adjusted, insensitivity to noise due to its special sampling and decision‐making mechanism, and the exemption of over‐fitting, leading to its suitability for online condition assessment. RF‐based approaches are increasingly popular for structural condition assessment 42–50 . Some of them focus on deterioration modeling and forecasting of sewer pipelines, 44–46 and in these investigations the input features are the suggested physical sewer characteristics (e.g., age, material, type of effluent, depth, diameter, slope, and type of road) and the output is deterioration level (e.g., four‐grade scale: C1–C4) obtained by using CCTV or GIS records.…”

“…RF-based approaches are increasingly popular for structural condition assessment. [42][43][44][45][46][47][48][49][50] Some of them focus on deterioration modeling and forecasting of sewer pipelines, [44][45][46] and in these investigations the input features are the suggested physical sewer characteristics (e.g., age, material, type of effluent, depth, diameter, slope, and type of road) and the output is deterioration level (e.g., four-grade scale: C1-C4) obtained by using CCTV or GIS records. The results show the RF-based method can identify the critically deteriorating pipelines among all pipelines in a designated area and classify the pipeline conditions into different levels at a high accuracy.…”

“…Yang et al develop a RF regression model for erosion prediction and its performance verification is conducted by using a test rig with several controlled variables (e.g., the impact angle, tensile stress, flow velocity, target material, and particle concentration). 47 Bagriacik et al examine the performance of RF and other three approaches for modeling earthquake damage to water pipelines and identify the important features for earthquake damage detection of water pipelines (e.g., pipe length, peak ground velocity [PGV], liquefaction resistance index [LRI], and pipe material). 48 Ning et al combine acoustic signals and RF method for leak detection of gas pipeline, and prove its effectiveness through lab tests of an experimental system.…”