Particle Erosion In Elbows Research Articles

A Novel Trajectory-Based Mechanistic Model for Predicting Solid Particle Erosion in Elbows

Abstract 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 rates accurately, especially for geometries such as elbows. Mechanistic models aim at predicting erosion accurately with low computational cost. In this study, a new particle trajectories-based mechanistic model is proposed to address the issues of liquid-dominated flows and the effect of particle size. Detailed flow and particle information for a standard elbow with water and air and different particle sizes are extracted from computational fluid dynamics (CFD) and analyzed to obtain a representative trajectory. The developed model includes various components that are sensitive to the particle size and flow conditions and accounts for the angle of impact and the turbulence in the flow. The proposed model is examined against CFD predictions for different pipe and particle sizes, and velocities with air, water, high-pressure air, and high-viscosity liquid. In comparison to an available mechanistic model, the new model provides relatively lower errors in predicting maximum erosion for many flow conditions. Moreover, the proposed model is found to be more consistent with CFD data for high-pressure air and higher-viscosity liquids. The model is further validated with experimental data for various conditions. Comparisons against numerical and experimental data suggest that the proposed model provides a significant improvement for liquid–solid flows and small particles.

Integrated Similarity Criteria of Particle Erosion in Elbows Under Gas and Gas-Mist Flow Conditions

AbstractSolid particle erosion has been a long-standing concern in oil-and-gas production and transportation systems, particularly in elbows of pipelines. Since it is difficult to exactly reproduce field conditions in the laboratory to study erosion, it is necessary to develop similarity criteria which ensure that lab results are representative of field conditions. Building on a previous work by the authors on similarity criteria that cover flow-field properties and particle-following behavior in gas and gas-mist flows, this work adds a similarity criterion for particle-rebounding and target material hardness. This new expanded set of criteria is validated using computational fluid dynamics by mapping five classic model tests to field cases—at different pipe diameters and pressures, with duplex stainless steel as the target material—and then comparing dimensionless maximum penetration rates and their angular locations. The analysis of errors demonstrates that the proposed criteria perform well in mapping laboratory data to field conditions.

Random forest regression prediction of solid particle Erosion in elbows

Solid particle erosion is an inevitable problem in oil and gas production and transportation systems, and it can cause severe damage in pipe fittings in which the flow direction changes suddenly. Erosion occurs in a variety of fittings, and one common fitting which is one of the most vulnerable to erosion is the elbow. Repair and/or replacement of pipe fittings in the appropriate period can avoid catastrophic disasters such as hydrocarbon release events. Therefore, accurate prediction of erosion is a subject of interest for the oil and gas industry. Both experimental and modeling approaches have been conducted in the past under different flow conditions and materials. The goal of this study is to use relevant experimental parameters as predictor variables and utilize a machine learning algorithm to predict erosion rate and validate the prediction under different conditions with test data. It is assumed that important parameters in erosion magnitude are material characteristics, pipe diameter, particles properties and size and carrier fluid properties. 201 experimental data points with a broad range of conditions were selected for the analysis. Predicted erosion rates through different machine learning techniques were compared, and Random Forest regression model was selected as an effective and alternative approach for erosion prediction. This method was examined on data points and compared with experimental results. Good agreement was observed in this method with experiments which provides the framework for a new way to predict solid particle erosion which is simpler yet accurate in comparison with available prediction models.

Similarity criteria of the solid particle erosion in elbows between model experiments and engineering for dry gas and gas–mist flows

Solid particle erosion in elbows is a prominent problem encountered in hydrocarbon transportation pipelines, especially for dry gas and gas–mist flows. There is great difference in flow conditions between model experiments and engineering. A set of similarity criteria is proposed to analyze the corresponding relationship between engineering conditions and that in laboratory tests. The similarity criteria aim at building a procedure that can predict the maximum penetration rate and its position in engineering conditions through the corresponding experimental design, reducing the heavy monitoring work in field circumstances. Principal dimensionless numbers on the flow field and particle response behaviors are presented to make up the similarity relationship between engineering cases and laboratory tests, respectively for dry gas and gas–mist flows. For several typical lab tests from the literature, each of them is extrapolated to a series of similar engineering cases which vary in pipe diameter and operating pressure. Then the typical laboratory tests and the corresponding engineering cases are calculated by the validated CFD method and four classic empirical or semi-empirical models to get the dimensionless penetration rates and maximum erosion positions, which are the two dimensionless similarity judgment numbers. The judgment numbers show good equivalence trends for the same series of laboratory test and its corresponding engineering cases. The similarity criteria developed in this study are verified and prove to be rational and efficient in predicting erosion in engineering through model experimental design.

CFD simulation of sand particle erosion in gas-dominant multiphase flow

A method for exploration of erosion in multiphase flow can be Computational Fluid Dynamics (CFD). A key advantage of utilizing CFD is that it can deliver a great deal of information such as the effects of different parameters on erosion, maximum erosion rate, and areas susceptible to erosion damage.The current work used a computational fluid dynamics (CFD) approach to study sand particle erosion in elbows, while the carrier fluid was multiphase flow of low, medium, and high gas flow rates. First, ANSYS MultiFluid VOF model was employed to simulate air–water multiphase flow with superficial gas velocities of 10.1, 18.3, and 27.1 m/s, while superficial liquid velocity was 0.3 m/s in all cases examined. The CFD data were validated against some experimental data previously obtained by a wire-mesh sensor.In the next step, particle tracking and erosion modeling were performed. Specifically, erosion in air–water flow with sand particles of two different sizes (150 and 300 μm) in a 76.2 mm elbow was simulated and compared with experimental data formerly obtained by an ultrasonic technique. Six different erosion equations were employed to discover which equation provides the best predictions. A good agreement was found between CFD results and the experimental data.

Numerical analyses of the solid particle erosion in elbows for annular flow

Solid particle erosion in pipelines is a severe problem involved in hydrocarbon transportation and hence an important topic in flow assurance. A simplified CFD-based procedure is proposed to calculate the penetration rates in elbows for annular flow. This new method overcomes the disadvantages of current empirical or semi-empirical models. The procedure consists of three main sections: flow modeling, particle tracking, and penetration calculation. The k–ε model is employed to analyze the flow field in the core area of the pipe based on the assumption that the gas–liquid interface is regarded as an actual pipe wall. Then a Lagrangian method is adopted to track trajectories of the entrained droplets and sand particles in the core area, and the velocity decay of sand particles across the liquid film is calculated combined with the film thickness correlation. Based on the knowledge of the flow field and the particle motion, penetration rates are calculated by introducing the solid particle erosion equation. By comparing with experimental data available from the literature, the new method is proved to be reasonable in simplifying the simulation of annular flow field and shows good accuracy in erosion prediction. A better agreement between predicted erosion rates and experimental data can be made when applied to larger curvature radius elbows.

Combination of CFD and DOE to analyse solid particle erosion in elbows

Solid particle erosion is a major concern in the engineering industry, particularly where transport of slurry flow is involved. Such flow regimes are characteristic of those in alumina refinement plants. The entrainment of particulate matter, for example sand, in the Bayer liquor can cause severe erosion in pipe fittings, especially in those which redirect the flow. The considerable costs involved in the maintenance and replacement of these eroded components led to an interest in research into erosion prediction by numerical methods at Rusal Aughinish alumina refinery, Limerick, Ireland, and the University of Limerick. The first stage of this study focused on the use of computational fluid dynamics (CFD) to simulate solid particle erosion in elbows. Subsequently an analysis of the factors that affect erosion of elbows was performed using design of experiments (DOE) techniques. Combining CFD with DOE harnesses the computational power of CFD in the most efficient manner for prediction of elbow erosion. An analysis of the factors that affect the erosion of elbows was undertaken with the intention of producing an erosion prediction model.

Modeling Solid Particle Erosion in Elbows and Plugged Tees

Predicted erosion patterns on the surface of a pipe fitting can now be obtained using a technique implemented into a computational fluid dynamics (CFD) code. This comprehensive erosion prediction procedure consists of 1) generation of a flow field simulation, 2) computation of a large number of particle trajectories inside the flow field, and 3) erosion model equations applied as particles impinge the walls of the geometry. Other quantities related to erosion, namely the particle deposition rate as well as local average impingement angle and velocity components, are also stored in the procedure. All predicted quantities (flow solution, particle trajectories, and erosion profiles) are analyzed using a three-dimensional visualization tool that was also developed. The current work focuses on two pipe fittings commonly used in the oil and gas production industry: elbows and plugged tees. First, the flow field and erosion predictions are evaluated through comparisons with experimental data. Erosion predictions yield trends and locations of maximum wear that are consistent with experimental observations. Next, two 90-deg pipe elbows with centerline curvature-to-diameter ratios of 1.5 and 5.0 are analyzed under prescribed erosive conditions. Predicted erosion results are presented in the form of surface contours. Finally, a simulated plugged tee geometry placed under erosive conditions is studied and erosion rates are compared to that of the two elbow test cases.

A Procedure to Predict Solid Particle Erosion in Elbows and Tees

Abstract A semi-empirical procedure has been developed for predicting erosion rates in pipe geometries, such as elbows and tees. The procedure can be used to estimate safe operating conditions and velocities in oil and gas production where sand is present. In the proposed procedure, a concept is introduced that allows determination of erosion rate for different pipe geometries. In the procedure, based on empirical observations, the erosion rate is related to the impact velocity of sand particles on a pipe fitting wall. A simplified particle tracking model is developed and is used to estimate the impact velocity of sand particles moving in a stagnation region near the pipe wall. A new concept of equivalent stagnation length allows the simplified procedure to be applicable to actual pipe geometries. The “equivalent stagnation regions” of an elbow and a tee geometry of different sizes are obtained from experimental data for small pipe diameters, and a computational model is used to extend the procedure to larger pipe diameters. Currently, the prediction method applies to mild steel and accounts for the effects of sand size, shape, and density; fluid density, viscosity, and flow speed; and pipe size and shape. The proposed method has been verified for gas and liquid flows through several comparisons with experimental data reported in the literature. The results of the model accurately predict the effects of sand size and fluid viscosity observed in the experiments. Furthermore, predicted erosion rates showed good agreement with experimental data for gas, liquid, and gas-liquid flows in several 50.8-mm (2-in.) elbows and tees.