Continuous impact of solid particles causes severe pipeline wear, and may result in leakage
in directional change areas such as elbows. Accurate prediction of erosion is essential in the …

The ability to predict solid particle erosion is a vital task for the integrity management of
pipelines carrying solid particles in many industries. Usually, the accuracy of predicted …

Solid particle erosion can be a threat to the integrity of pipelines, even at low concentrations.
Erosion correlations are widely used in industries to prevent failures. Although particle …

Solid particle erosion is a common and challenging phenomenon during the production and
transport of particle-containing fluids and it is important to have models for predicting erosion …

Erosion is inevitable in pipeline gathering and transportation systems. Predicting erosion in
typical pipe fittings is pivotal to ensure the safety and efficiency of the equipment. This work …

The aim of this work is to define, implement, test, and validate an AI methodology using
existing machine learning (ML) algorithms to predict sand erosion in 90° elbows for a broad …

Uncertainties are part of any scientific measurements and calculations. As a complex
phenomenon, erosion is affected by many independent parameters and consequently the …

Abstract Machine learning feature has been utilized to demonstrate the importance and
prioritize the parameters in erosion rate prediction. With the expansion of experimental data …

Solid particles can be found in many industrial applications that involve multiphase flow
transport such as oil and gas production and transportation, and mining. Consequently, solid …

Erosion prediction models are important tools for preventing costly failures that can happen
due to solid particle erosion. Various models such as computational models, mechanistic …